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Google's Project Dragonfly was a secret prototype search engine intended to pave the way for the company's return to China; it featured censored search results that complied with Chinese state rules banning searches for topics like "human rights," "student protest" and "Nobel prize."

Leaked details of Dragonfly, reported in The Intercept, paint a picture of a search tool that doesn't merely limit access to information, but also assists Chinese state agents in retaliating against people who sought access to banned information.

In particular, Dragonfly logged each search and associated it with the user's phone number.

Dragonfly was also reportedly built to help the Chinese authorities falsify pollution data by substituting official numbers for observations made by disinterested parties. Pollution is a fraught political topic in China, with citizens frequently upset over the state's failure to keep their air breathable. The Chinese government has a history of falsifying pollution data and suppressing independent figures.

Sources familiar with the project said that prototypes of the search engine linked the search app on a user’s Android smartphone with their phone number. This means individual people’s searches could be easily tracked – and any user seeking out information banned by the government could potentially be at risk of interrogation or detention if security agencies were to obtain the search records from Google.

“This is very problematic from a privacy point of view, because it would allow far more detailed tracking and profiling of people’s behavior,” said Cynthia Wong, senior internet researcher with Human Rights Watch. “Linking searches to a phone number would make it much harder for people to avoid the kind of overreaching government surveillance that is pervasive in China.”

Source: This article was Published boingboing.net

Published in Search Engine

Think of online privacy as a race.

With consumers increasingly focused on how their data and web personas are used by eCommerce and other digital organizations, regulators and lawmakers are moving to get ahead of that political and cultural wave. Payments, commerce, and tech companies, meanwhile, are trying to stay a step ahead of regulators and lawmakers, and tweak or refashion their brands and reputations so they can boast about privacy protections and reduce the risk of losing profit as customers rethink their loyalties.

DuckDuckGo, the no-tracking search engine with a name that reflects a childhood play activity, intends to make the most of the ongoing privacy backlash from consumers. It has raised $10 million in fresh capital — only the second funding round for the 10-year-old, Pennsylvania-based operation —  and has plans to better promote itself to a global audience, while also offering other privacy-protection technology.

It seems foolish to even fantasize about the search engine ever catching up with Google. However, in a new PYMNTS interview, DuckDuckGo Founder Gabriel Weinberg said that, in the coming year, it could end up accounting for a double-digit chunk of search activity.

Optimistic View

His optimism stemmed in large part from the search’s engine growth: Use is up at least 50 percent over the last couple of years, with more than 5.8 billion direct search queries in total so far in 2018, compared with nearly 6 billion for all of 2017. The site’s daily direct traffic averages about 26.2 million. The United States stands as the largest source of DuckDuckGo traffic, followed by such countries as France, Germany, and Canada.

Of course, Google has numbers that dwarf that: about 3.5 billion searches per day. Though DuckDuckGo does not engage in tracking the behavior and habits of consumers online, it does make its money via ad offerings based on the keywords entered by users when searching for something — just as Google does. A consumer on either search engine might type in “car insurance,” for instance, resulting in relevant ads being served up, which in turn can result in revenue for that search engine.

The difference is that DuckDuckGo stops there — it does not sell search data to third parties for advertising (which, of course, cuts out a lucrative source of revenue). The search engine does not store users’ search histories, either.

That limit stands as a big part of the search engine’s appeal in these privacy-sensitive times, according to Weinberg. The search engine, its results compiled from more than 400 sources and its own web crawler, earns revenue from serving ads via the YahooBing network and affiliate relationships with such eCommerce operators as Amazon and eBay. For each user who buys a product that originates with certain DuckDuckGo searches, the site earns a commission on that transaction.

“We are definitely small,” he said, acknowledging the obvious. However, the company turns a profit and has yet to do any major marketing. So far, DuckDuckGo has benefited from word of mouth, essays, blog postings and question-and-answer content published and distributed on Quora and social media sites, he said.

New Funding

The new capital, from OMERS Ventures, a Canadian pension fund, will enable DuckDuckGo to beef up its marketing, among other areas. “We’re not sure what kind of marketing yet,” Weinberg said. “We’re running different kinds of experiments to figure out what works the best.”

DuckDuckGo last raised capital in 2011 — $3 million in seed funding. Since then, the digital landscape has significantly changed, which attracted OMERS. “Issues of privacy and security in the digital world have become increasingly topical and controversial,” the firm said in explaining its investment. “In 2018, these concerns have risen to the forefront of public consciousness. Users are becoming more aware of their personal data and are increasingly concerned with protecting it.”

DuckDuckGo aims to go beyond online searches in further building its pro-privacy brand. It recently launched what OMERS called “a mobile browser and desktop browser extension to their product mix; these products include built-in tracker blocking and smarter encryption.”

Facebook Example

Recent data and consumer trends support that path, Weinberg told PYMNTS. Like others in the space focusing on privacy (or worried about the consumer backlash), he used Facebook as an example.

For those who’ve enjoyed the luxury of a news-light summer away from digital leashes, the story goes like this: The social media platform needs to maintain — or even win back — the trust of consumers who were either shaken by the Cambridge Analytica data sharing scandal or are just increasingly wary of sharing too much information online with a massive corporation. In fact, Pew Research recently reported that 42 percent of Facebook users have taken a break from the platform during the past year, while 54 percent of those 18 and older have adjusted their privacy settings during that time frame. Additionally, 26 percent of U.S. adult consumers said they deleted the Facebook app from their smartphone.

“Awareness is really high,” Weinberg said about online privacy, adding that the company’s own surveys echo findings that a good chunk of consumers are having second thoughts about how their data is used by digital service providers. “People are trying to figure out how to protect themselves online.”

Figuring out answers is taking on an almost existential flavor in digital payments and commerce (which is to say, most of Western daily life). A recent discussion between PYMNTS’ Karen Webster and Sunil Madhu, founder of identity verification and fraud prevention services provider Socure, dug deep into those questions and featured a debate about how much Facebook really has to worry about and analysis of what makes a solid digital ID.

The consumer focus on privacy, and the ongoing backlash — demonstrated in part by Europe’s GDPR and other laws — is no flash in the pan, Weinberg said. This moment of privacy protection effort represents, perhaps, the best opportunity for DuckDuckGo — one that could propel it to capture 5 percent to 10 percent of searches, he said.

Historians will have to figure out and define the various phases of internet development and digital economy growth, and trying to anticipate what they will say is a fun game, but often ends up as a reckless intellectual endeavor. That said, the last few years — don’t forget the Edward Snowden NSA revelations, because Weinberg and other students of online privacy sure don’t — are shaping up as a turning point in how online consumers view privacy.

That will, no doubt, provide an opportunity for a host of businesses — not just DuckDuckGo.

Source: This article was Published pymnts.com
Published in Search Engine

Here's what some marketers are saying about the move to include same meaning queries in exact match close variants.

Marketer reactions to the news that Google is yet again degrading the original intent (much less meaning) of exact match to include “same meaning” close variants is ranging from pessimism to ho-hum to optimism.

Expected impact on performance

“The impact of this will probably be most felt by accounts where exact match has historically been successful and where an exact match of a query made a difference in conversions — hence the reason you’d use exact in the first place,” said digital consultant and President of Netptune MoonJulie Friedman Bacchini.

Friedman Bacchini said the loss of control with exact match defeats the match type’s purpose. Many marketers use exact match to be explicit — exacting — in their targeting and expect a match type called “exact” to be just that.

Brad Geddes, the co-founder of ad testing platform AdAlysis and head of consultancy Certified Knowledge, said one problem with expanding the queries that can trigger an exact match keyword is that past changes have shown it can affect the overall performance of exact match. “The last change meant that our ‘variation matches’ had worse conversion rates than our exact match and that we lowered bids on most exact match terms. This change might just drive us from using it completely, or really hitting the negative keywords.”

Like Geddes, Andy Taylor, associate director of research at performance agency Merkle, also said they saw an increase in traffic assigned as exact match close variants with the last change, “and those close variants generally convert at a lower rate than true exact matches.”

Yet, others who participated in the test see the loosening of the reigns as a positive action.

One of the beta testers for this change was ExtraSpace Storage, a self-storage company in the U.S. with locations in more than 40 states. The company says it saw positive results from the test.

“The search queries were relevant to our industry and almost all of our primary KPIs saw an overall improvement,” said Steph Christensen, senior analyst for paid search at ExtraSpace.

Christensen said that during the test they did not do any keyword management, letting it run in a “normal environment to give it the best chance to provide the truest results.” She says they will continue to watch performance and make adjustments as needed after it’s fully rolled out by the end of October.

Advertisers as machine learning beneficiaries or guinea pigs

A big driver of these changes, of course, is machine learning. The machine learning/artificial intelligence race is on among Google and the other big tech companies.

Google says its machine learning is now good enough to determine when a query has the same intent as a keyword with a high enough rate of success that advertisers will see an overall performance lift.

Another way to look at the move, though, is that by opening up exact match to include same meaning queries, Google gets the benefit of having marketers train its algorithms by taking action on query reports.

Or as Geddes, put it: “Advertisers are basically paying the fee for Google to try and learn intent.”

Geddes’ point is that this change will help Google’s machine learning algorithms improve understanding of intent across millions of queries through advertiser actions and budgets.

“The fact that Google doesn’t understand user intent coupled with how poor their machine learning has been at times, means we might just move completely away from exact match,” says Geddes.

Of the example Google highlighted in its announcement, Geddes says, “If I search for Yosemite camping; I might want a blog article, stories, social media, or a campground. If I search for a campground — I want a campground.” (As an aside, from what I’ve found it appears Google doesn’t even monetize “Yosemite camping” or “Yosemite campground” results pages that it used as examples.)

Expected workflow changes

One big thing Google has emphasized is that these close variants changes allow advertisers to focus on things other than building out giant keyword lists to get their ads to show for relevant queries. Rather than doing a lot of upfront keyword research before launching, the idea is that the management will happen after the campaign runs and accumulates data. Marketers will add negatives and new keywords as appropriate. But this reframing of the management process and what amounts to a new definition of exact match has marketers thinking anew about all match types.

“The further un-exacting of exact match has me looking at phrase match again,” says Friedman Bacchini. “I definitely see it impacting use of negatives and time involved to review SQRs and apply negatives properly and exhaustively”.

Taylor agrees. “This change places more importance on regularly checking for negatives, but that has already been engrained in our management processes for years and won’t be anything new.”

Geddes said that advertisers might come up against negative keyword limits, which he has seen happen on occasion. Rather than relying heavily on adding negatives, he says they may consider only using phrase match going forward.

In addition to having ads trigger for queries that aren’t relevant or don’t convert well, there’s the matter of having the right ad trigger for a query when you have close variants in an account already.

Matt van Wagner, president and founder of search marketing firm Find Me Faster, says the agency will be monitoring the impact before assessing workflow adjustments, but is not anticipating performance lifts.

“We’ll watch search queries and how, or if, traffic shifts from other ad groups as well as CPC levels. We expect this to have neutral impact at best,” says van Wagner, “since we believe we have our keywords set to trigger on searches with other match types.”

Along those lines, Geddes says it will be critical to watch for duplicate queries triggering keywords across an account to make sure the right ad displays. It puts new focus on negative keyword strategies, says Geddes:

Google will show the most specific matching keyword within a campaign; but won’t do it across the account. So if I have both terms in my account as exact match (“Yosemite camping” and “Yosemite campground”), with one a much higher bid than the other, my higher bid keyword will usually show over my actual exact match word in a different campaign. That means that I now need to also copy my exact match keywords from one campaign and make them exact match negatives in another campaigns that is already using exact match just to control ad serving and bidding. I should never have to do that.

Measuring impact can be challenging

The effects of the change will take some time to unfold. Taylor says it took several months to see the impact of the last change to exact match close variants.

It’s difficult to calculate the incremental effect of these changes to close variants, in part says Taylor, because some close variant traffic comes from keywords – close variants or other match types — that are already elsewhere in the account.

“Google gives a nod to this in its recent announcement, saying that ‘Early tests show that advertisers using mostly exact match keywords see 3 percent more exact match clicks and conversions on average, with most coming from queries they aren’t reaching today,’” Taylor highlights with bolding added.

Another complicating factor, particularly for agencies, is that the effects of these changes don’t play out uniformly across accounts. Taylor shares an example:

An advertiser saw traffic on one of its key brand keywords shift to a different brand keyword several months after the close variants change last year.

“The normal reaction might be to use negatives to get that traffic back over to the correct keyword, but we were getting a better CPC and still getting the same traffic volume with the new variation,.

It didn’t make much sense, especially given Google’s continued assertion even in the current announcement that ‘Google Ads will still prefer to use keywords identical to the search query,’ but if the clicks are cheaper, the clicks are cheaper. This also speaks to how there’s not really a universal response to deploy for changes in close variants, aside from being mindful of what queries are coming in and how they’re performing.”

Looking ahead

Performance advertisers go where they get the best results.

“At the end of the day, the question is if poorer converting close variant queries might pull keyword performance down enough to force advertisers to pull back on bids and reduce overall investment,” said Taylor. “Generally speaking, giving sophisticated advertisers greater control to set the appropriate bids for each query (or any other segment) allows for more efficient allocation of spend, which should maximize overall investment in paid search.”

Geddes says their “priority is to make sure our Bing Ads budgets are maxed and that we’re not leaving anything on the table there. If our [Google] results get worse, we’ll also move some budgets to other places. But this might be one where we really have to do another account organization just to get around Google’s decisions.”

After the change has fully rolled out and they have enough data to act on, ExtraSpace’s Christensen said they will evaluate again. “Since we have such a large [account] build, when we do decide to make any changes we will have to show how we can do this at scale and maintain performance.”

Bacchini calls attention to the current misnomer of exact match and said Google should get rid of exact match altogether if it’s going to take away the original control of exact match. “It is particularly sneaky when you think of this move in terms of less sophisticated advertisers,” said Bacchini. “If they did not click on the ‘Learn More’ link below the formatting for entering in match types for keywords, how exactly would they know that Google Ads does not really mean exact?”

Source: This article was Published searchengineland.com By Ginny Marvin

Published in Search Engine

Reverse image search is a technique wherein it allows people to retrieve content that is relevant to a particular image. It is also known as content-based image retrieval a method that eliminates the need for a user to identify keywords that may or may not provide an accurate result. The user only needs to supply the sample image to make a search or query.

We know that Google images can provide us with any photo, but we need to write the keyword or the terms associated with it to be able to proceed with the search. While using a reverse image search tool we will just provide a sample image. It is helpful in locating the source of an image or the content creator, search for the image in terms of popularity, extract details that are related to an image, look for similar images that have higher resolution, locate the web pages where the photo is displayed, and look for manipulated versions of the image.

If you are into social media and you want to find if a person’s account is legit, you can use a reverse image search tool for this purpose. You only have to supply the photo of the person, and it will show you the information that you need to check if the account is legit or not. Verifying account using a reverse image search tool can save you the trouble of being connected with an impostor or scammer. At present, many people are using fake accounts that is why you must be cautious and check the profile of the person first before adding them.

Photographers spend a great deal of money to buy their equipment and to attend workshops. They also exert a lot of time and effort in their craft to be able to produce quality and beautiful pictures that is why it is only right that they get the proper compensation for their work. They can use the reverse image search tool to discover if someone is using their pictures without their permission. By not giving credits to the owner, one can be accused of false ownership.

Whether it is for personal or public use, it should always be a practice to attribute the source of an image. To be able to get the information that you need, you can use a reverse image search from SmallSEOTools.com. This specific website offers many helpful tools that anybody can use online. One of the most popular tools from Small SEO Tools is the reverse image search because it is simple and easy to use. All you have to do is to upload an image or paste the URL where the image is located, and then it will give you the results in a flash. It will show you similar images and their sources.

Also, if you want to get any information about a particular image like a famous person, place or product you can run it through a reverse image search tool. It can help you save a lot of time looking for answers if you want to know more about the photo. You don’t have to go through an intensive research by typing different keywords to get the information that you need from the image.

There are many reverse image search tools on the internet today, but the one that I always use is from SmallSEOTools because it is user-friendly and gives me the results that I need in just a few seconds. Not to mention that this online reverse image search tool is readily available and can be used free of charge.

 Source: This article was Published techworm.net By Payel Dutta

Published in Search Engine

Did you ever need data on a topic you wanted to research, and had a hard time finding it? Wish you could just Google it? Well, now you can do that.

With data science and analytics on the rise and underway to being democratized, the importance of being able to find the right data to investigate hypotheses and derive insights is paramount

What used to be the realm of researchers and geeks is now the bread and butter of an ever-growing array of professionals, organizations, and tools, not to mention self-service enthusiasts.

Even for the most well-organized and data-rich out there, there comes a time when you need to utilize data from sources other than your own. Weather and environmental data is the archetypal example.

Suppose you want to correlate farming data with weather phenomena to predict crops, or you want to research the effect of weather on a phenomenon taking place throughout a historical period. That kind of historical weather data, almost impossible for any single organization to accumulate and curate, is very likely to be readily available by the likes of NOAA and NASA.

Those organizations curate and publish their data on a regular basis through dedicated data portals. So, if you need their data on a regular basis, you are probably familiar with the process of locating the data via those portals. Still, you will have to look at both NOAA and NASA, and potentially other sources, too.

And it gets worse if you don't just need weather data. You have to locate the right sources, and then the right data at those sources. Wouldn't it be much easier if you could just use one search interface and just find everything out there, just like when you Google something on the web? It sure would, and now you can just Google your data, too.

That did not come about out of the blue. Google's love affair with structured data and semantics has been an ongoing one. Some landmarks on this path have been the incorporation of Google's knowledge graph via the acquisition of Metaweb, and support for structured metadata via schema.org.

Anyone doing SEO will tell you just how this has transformed the quality of Google's search and the options content publishers now have available. The ability to markup content using schema.org vocabulary, apart from making possible things such as viewing ratings and the like in web search results, is the closest we have to a mass-scale web of data.

This is exactly how it works for dataset discovery, as well. In a research note published in early 2017 by Google's Natasha Noy and Dan Brickley, who also happen to be among the semantic web community's most prominent members, the development was outlined. The challenges were laid out, and a call to action was issued. The key element is, once more, schema.org.

schemaorgattributes.png 

Schema.org plays a big part in Google's search, and it's also behind the newly added support for dataset search. (Image: Go Live UK)

Schema.org is a controlled vocabulary that describes entities in the real world and their properties. When something described in schema.org is used to annotate content on the web, it lets search engines know what that content is, as well as its properties. So what happened here is that Google turned on support for dataset entities in schema.org, officially available as of today.

The first step was to make it easier to discover tabular data in search, which uses this same metadata along with the linked tabular data to provide answers to queries directly in the search results. This has been available for a while, and now full support for dataset indexing is here.

But is there anything out there to be discovered? How was Google's open call to dataset providers received? ZDNet had a Q&A with Natasha Noy from Google Research about this:

"We were pleasantly surprised by the reception that our call to action found. Perhaps, because we have many examples of other verticals at Google using the schema.org markup (think of jobs, events, and recipes), people trusted that providing this information would be useful.

Furthermore, because the standard is open and used by other companies, we know that many felt that they are doing it because it is 'the right thing to do.' While we reached out to a number of partners to encourage them to provide the markup, we were surprised to find schema.org/dataset on hundreds, if not thousands, of sites.

So, at launch, we already have millions of datasets, although we estimate it is only a fraction of what is out there. Most just marked up their data without ever letting us know."

NOAA's CDO, Ed Kearns, for example, is a strong supporter of this project and helped NOAA make many of its datasets searchable in this tool. "This type of search has long been the dream for many researchers in the open data and science communities," he said. "And for NOAA, whose mission includes the sharing of our data with others, this tool is key to making our data more accessible to an even wider community of users."

Under the hood

In other words, it's quite likely you may find what you are looking for already, and it will be increasingly likely going forward. You can already find data from NASA and NOAA, as well as from academic repositories such as Harvard's Dataverse and Inter-university Consortium for Political and Social Research (ICPSR), and data provided by news organizations, such as ProPublica.

But there are a few gotchas here, as datasets are different from regular web content that you -- and Google -- can read.

To begin with, what exactly is a dataset? Is a single table a dataset? What about a collection of related tables? What about a protein sequence? A set of images? An API that provides access to data? That was challenge No. 1 set out in Google's research note.

Those fundamental questions -- "what is topic X" and "what is the scope of the system" -- are faced by any vocabulary curator and system architect respectively, and Noy said they decided to take a shortcut rather than get lost in semantics:

"We are basically treating anything that data providers call a dataset by marking schema.org/dataset as a dataset. What constitutes a dataset varies widely by discipline and at this point, we found it useful to be open-minded about the definition."

That is a pragmatic way to deal with the question, but what are its implications? Google has developed guidelines for dataset providers to describe their data, but what happens if a publisher mis-characterizes content as being a dataset? Will Google be able to tell it's not a dataset and not list it as such, or at least penalize its ranking?

Noy said this is the case: "While the process is not fool-proof, we hope to improve as we gain more experience once users start using the tool. We work very hard to improve the quality of our results."

google-data-tech-analytics2-ss-1920.jpg

Google and data has always gone hand in hand. Now Google takes things further, by letting you search for data.

Speaking of ranking, how do you actually rank datasets? For documents, it's a combination of content (frequency and position of keywords and other such metrics) and network (authority of the source, links, etc). But what would apply to datasets? And, crucially, how would it even apply?

"We use a combination of web ranking for the pages where datasets come from (which, in turn, uses a variety of signals) and combine it with dataset-specific signals such as quality of metadata, citations, etc," Noy said.

So, it seems dataset content is not really inspected at this point. Besides the fact that this is an open challenge, there is another reason: Not all datasets discovered will be open, and therefore available for inspection.

"The metadata needs to be open, the dataset itself does not need to be. For an analogy, think of a search you do on Google Scholar: It may well take you to a publisher's website where the article is behind a paywall. Our goal is to help users discover where the data is and then access it directly from the provider," Noy said.

First research, then the world?

And what about the rest of the challenges laid out early on in this effort, and the way forward? Noy noted that while they started addressing some, the challenges in that note set a long-term agenda. Hopefully, she added, this work is the first step in that direction.

Identifying datasets, relating them, and propagating metadata among them was a related set of challenges. "You will see", Noy said, "that for many datasets, we list multiple repositories -- this information comes from a number of signals that we use to find replicas of the same dataset across repositories. We do not currently identify other relationships between datasets."

Indeed, when searching for a dataset, if it happens to be found in more than one locations, then all its instances will be listed. But there is also something else, uniquely applicable to datasets -- at least at first sight. A dataset can be related to a publication, as many datasets come from scientific work. A publication may also come with the dataset it produced, so is there a way of correlating those?

Noy said some initial steps were taken: "You will see that if a dataset directly corresponds to a publication, there is a link to the publication right next to the dataset name. We also give an approximate number of publications that reference the dataset. This is an area where we still need to do more research to understand when exactly a publication references a dataset."

pasted-image-0.png

Searching for datasets will retrieve not only multiple results for your query, but also multiple sources for each dataset. (Image: Google)

If you think about it, however, is this really only applicable to science? If you collect data from your sales pipeline and use them to derive insights and produce periodic reports, for example, isn't that conceptually similar to a scientific publication and its supporting dataset?

If data-driven decision making bears many similarities to the scientific process, and data discovery is a key part of this, could we perhaps see this as a first step of Google moving into this realm for commercial purposes as well?

When asked, Noy noted that Google sees scientists, researchers, data journalists, and others who are interested in working with data as the primary audience for this tool. She also added, however, that as Google's other recent initiatives indicate, Google sees these kinds of datasets becoming more prominent throughout Google products.

Either way, this is an important development for anyone interested in finding data out in the wild, and we expect Google to be moving the bar in data search in the coming period. First research, then the world?

Source: This article was Published zdnet.com By George Anadiotis

Published in Search Engine

VirusTotal, which is a product of Chronicle, a company created within Alphabet’s fabled “moonshot factory,” has been described as “Google for malware.”

Earlier this year, Google parent Alphabet unveiled a new, top-level company called Chronicle that would be dedicated to cybersecurity.

Initially created within X, Alphabet’s so-called “moonshot factory” unit, Chronicle has said that it’s developing a security analytics platform for corporate customers, harnessing the company’s strengths in search, artificial intelligence, raw computing, and data storage power. But Chronicle also includes an often-overlooked security product called VirusTotal, sometimes described as “Google for malware.”

Acquired by Google in 2012, the Malaga, Spain, based company was first created by cybersecurity developer Bernardo Quintero in 2004, who’s worked on antivirus technology since he was a teenager. Quintero’s earlier projects included a Spanish-language cybersecurity newsletter and a tool designed to defeat dial-up-era malware that ran up charges calling premium toll hotlines. VirusTotal enables anyone to upload a file they suspect may contain malware to have it scanned by dozens of antivirus tools from vendors like Symantec, TrendMicro, Kaspersky, and Avast.

“When I started [VirusTotal] there were eight or nine antivirus companies working in the first version of the service,” says Quintero.

Now, there are more than 70, and the tool can extract other metadata from files as well, whether it’s a photo or an executable program, studying the uploaded content in secure virtual cloud machines. Security experts can also use the platform to share information about potential new malware files.

“They can have fast access to the malware samples to improve their product,” Quintero says.

VirusTotal played a role in the analysis of the infamous Stuxnet worm, when it collected some of the first samples, and it’s been cited in commercial and academic security research, including recent work on cryptocurrency-stealing malware.

Since Alphabet’s acquisition, VirusTotal has been largely independently managed, but it’s been able to take advantage of the larger company’s cloud computing and search capabilities—some of the same strengths that Alphabet intends to leverage for its larger Chronicle efforts.

“We’ve increased search capabilities,” says Chronicle CEO Stephen Gillett. “We’ve invested a large amount of infrastructure to make scanning faster and better.”

More fundamentally, Alphabet has also helped VirusTotal, which prior to Chronicle’s debut was administratively part of the company’s internal cybersecurity unit, combat denial of service attacks that had threatened it as an independent platform.

“For us, it was a way to perfect our mission,” says Quintero.

VirusTotal Graph [Image: courtesy of VirusTotal]
VirusTotal has also added a data visualization component, called VirusTotal Graph, that can help suss out the relationships between malware files and the URLs and IP addresses that distribute them. And this year, it unveiled a feature called VirusTotal Monitor, which lets legitimate software makers upload their applications and information about them so participating antivirus companies can avoid mistakenly flagging them as malware. The innocuous software samples are stored in a secure, private cloud, and antivirus vendors are only given access to the data if their software begins to mistakenly flag the files as viruses.

Another feature, called VirusTotal Intelligence, lets security researchers sift through the set of uploaded files to find ones matching certain criteria. A bank, for example, could spot malware trying to interact with its websites.

Gillett declined to comment too extensively on plans for Chronicle’s next project, though he emphasized it would also take advantage of Alphabet’s strengths to help customers sift through vast quantities of security data.

“We should be able to help teams search and retrieve useful information and run analysis in minutes, rather than the hours or days it currently takes,” he wrote in a January blog post. “Storage—in far greater amounts and for far lower cost than organizations currently can get it—should help them see patterns that emerge from multiple data sources and over years.”

Chronicle isn’t Alphabet’s only high-profile security project—the company’s Jigsaw unit focuses on tools to make the world safer, including combating misinformation and radicalization, and Google’s Project Zero team has focused on spotting bugs in software before they can do harm. More recently, Alphabet has announced plans to help safeguard elections, including by helping keep Google accounts safe from unauthorized access.

Contributing to cybersecurity in a world where it’s often lacking is an important mission for the company, Gillett says.

“For Alphabet, and for me personally as the founder and CEO of Chronicle, I believe there’s no better moonshot for Alphabet to be going after,” he says.

 Source: This article was Publishedfastcompany.com By Steven Melendez

Published in Internet Privacy

Google has launched Dataset Search, a search engine for finding datasets on the internet. This search engine will be a companion of sorts to Google Scholar, the company’s popular search engine for academic studies and reports. Google Dataset Search will allow users to search through datasets across thousands of repositories on the Web whether it be on a publisher’s site, a digital library, or an author’s personal web page.

Google’s Dataset Search scrapes government databases, public sources, digital libraries, and personal websites to track down the datasets. It also supports multiple languages and will add support for even more soon. The initial release of Dataset Search will cover the environmental and social sciences, government data, and datasets from news organizations like ProPublica. It may soon expand to include more sources.

Google has developed certain guidelines for dataset providers to describe their data in a way that Google can better understand the content of their pages. Anybody who publishes data structured using schema.org markup or similar equivalents described by the W3C, will be traversed by this search engine. Google also mentioned that Data Search will improve as long as data publishers are willing to provide good metadata. If publishers use the open standards to describe their data, more users will find the data that they are looking for.

Natasha Noy, a research scientist at Google AI who helped create Dataset Search, says that “the aim is to unify the tens of thousands of different repositories for datasets online. We want to make that data discoverable, but keep it where it is.”

Ed Kearns, Chief Data Officer at NOAA, is a strong supporter of this project and helped NOAA make many of their datasets searchable in this tool. “This type of search has long been the dream for many researchers in the open data and science communities,” he said.

Source: This article was Published hub.packtpub.com By Sugandha Lahoti

Published in Search Engine

Ten years into its life, Chrome is the most widely-used internet browser in the world. But the stock features aren’t what make it so popular. There’s also a thriving community of developers adding onto the browser with extensions, little pieces of software that add features Google hasn’t dreamt up yet.

The Quartz staff like their extensions. After all, we all spend a borderline unhealthy amount of time on the internet, whether it be researching, writing, or fact-checking stories. Here are the ways our favorites have helped us out:

Clutter/tab maintenance

If you’re like us, you have way too many tabs open. The holy trinity of tab maintenance can help: The Great Suspender pauses tabs after a certain amount of time so they don’t use processing power in the background, OneTab is great for condensing all the tabs you’re keeping open “to read later” into one summary tab, and Clutter Freemakes sure you don’t have duplicate tabs open.

Productivity

Sometimes you want to jot down a quick note but don’t want to open a word processor. Papier turns each new tab’s homepage into a notebook for recording quick thoughts or distraction-free writing. And everything is backed up to Chrome, so you won’t lose it later.

Search

The Personal Blocklist extension, made by Google, filters out certain domains from your searches, so if you don’t like a certain site you don’t need to see it. (Keep qz.com, please.) A Quartz developer says that it’s useful to block out certain unhelpful sites when Googling through a web development problem.

Writing

Sometimes a hand you need with grammar. Grammarly.

News

Use Pocket to save good stories and NewsGuard to fend against bad ones. Quartz science editor Elijah Wolfson also sends longer stories he really wants to read to his Kindle using Push to Kindle. It’s distraction-free reading at its best, with no notifications or ads or messages.

Password management

A password manager is just basic internet hygiene—use one to maintain strong passwords for every one of your internet accounts. The most popular ones are 1Password, LastPass, and Dashlane— there are pros and cons to each, and the Quartz staff uses them all. Just remember the master password—your digital life depends on it.

Archive search

Once it’s on the internet, it lives forever. That’s pretty much due to Archive.org, which stores decades of revisions to websites, as well as preserved copies of sites that don’t exist anymore. The Wayback Machine extension allows you to see saved versions of web pages that have been either taken down or are otherwise unavailable, a boon to any internet historian.

Money Saver

Get around academic paywalls with extensions like Kopernio and Unpaywall, which search for accessible PDFs of the paper online. Or, find out if you’re actually getting a good deal with a price tracker like CamelCamelCamel.

GIFs

My trustiest Chrome extension is called MakeGIF, and it’s very simple. It makes GIFs. It’s particularly good at capturing and converting YouTube videos.

Fun

Inject a little bit of simple internet nostalgia into your life with Tabogotchi, which makes a game out of how many tabs you have open, or Tabby Cat, which generates an internet cat you can virtually pet for every tab you open.

Source: This article was Published qz.com By Dave Gershgorn

Published in Search Engine

If you think a search engine exists as an index to the internet, it’s time to update your thinking.

This column is not about politics. It makes no political judgments and takes no political positions. No, really! Stay with me here.

President Trump this week slammed Google, claiming that the company “rigged” Google News Search results to favor stories and news organizations critical of the president.

To drive home his claim about bias, Trump posted a video on Twitter this week with the hashtag #StopTheBias (which, at the time I wrote this, had 4.36 million views), claiming that Google promoted President Barack Obama’s State of the Union addresses, but stopped the practice when Trump took office.

In a statement issued to the press, a Google spokesperson said that the company did not promote on its homepage either Obama’s or Trump’s first “State of the Union” addresses because technically they are considered mere “addresses to a joint session” of Congress, the idea being that brand-new presidents are not in a position to reveal the “state of the nation.” Google also claimed that it did promote Trump’s second and most recent State of the Union, a claim that screenshots found on social media and pages captured by the site Wayback Machine appear to confirm.

The facts around this incident are being funneled into ongoing, rancorous online political debates, which, in my opinion, isn’t particularly interesting.

What is interesting is the Big Question this conflict brings to the surface.

What is a search engine?

A search engine can be four things.

  • An index to the internet

When Google first launched its search engine in 1996, it was clear what a search engine was: an index of the internet.

Google’s killer innovation was its ability to rank pages in a way that was supposed to reflect the relative relevance or importance of each result.

Both the results and the ranking were supposed to be a reflection or a snapshot of the internet itself, not an index to the information out there in the real world.

  • An arbiter of what’s true

In this view, Google Search would favor information that’s objectively true and de-emphasize links to content that’s objectively untrue.

  • An objective source of information

The objective source idea is that Google makes an attempt to present all sides of contentious issues and all sources of information, without favoring any ideas or sources.

  • A customized, personalized source of information

The personalized source concept says that a search engine gives each user a different set of results based on what that user wants regardless of what’s true, what’s happening on the internet or any other factor.

This is all pretty abstract, so here’s a clarifying thought experiment.

When someone searches Google to find out the shape of the Earth, how should Google approach that query? It depends on what Google believes a search engine is.

(Note that it’s likely that flat-Earth proponents generate, link to and chatter about the idea that the Earth is flat more than people who believe it’s spherical. Let’s assume for the sake of argument that, objectively, the content and activity on the actual internet favors the flat-Earth idea.)

If a search engine is supposed to be an index to the internet, then search results for the shape of the Earth should favor the flat-Earth idea.

If a search engine is supposed to be an arbiter of what’s true, then search results should favor the spherical-Earth idea.

If a search engine is supposed to be an objective source of information, then search results should provide a balanced result that equally represents both flat- and spherical-Earth theories.

And if a search engine is supposed to be a customized, personalized source of information, then the results should favor either the flat-Earth idea or the spherical-Earth idea, depending on who is doing the searching.

I use the shape of the Earth as a proxy or stand-in for the real search results people are conducting.

For example, searches for your company, product, brand or even yourself are still subject to the same confusion over what a search engine is supposed to be.

When your customers, prospective business partners, employees or future prospective employees and others search for information about your organization, what results should they get? Should those results reflect what’s “true,” what’s false but popular, or what’s neutral between the two? Or should it depend on who’s doing the searching?

The truth is that Google tries to make Google Search all four of these things at the same time.

Adding to the complexity of the problem is the fact that search engine results are governed by algorithms, which are trade secrets that are constantly changing.

If you were to ask people, I suspect that most would say that Google Search should be Model No. 1 — an index to the internet — and not get involved in deciding what’s true, what’s false or what’s the answer the user wants to hear.

And yet the world increasingly demands that Google embrace Model No. 2 — to be an arbiter of what’s true.

Governments won’t tolerate an accurate index

Trump has claimed repeatedly that, in general, news media coverage is biased against him. If that’s true, and if Google News Search was a passive index of what the media is actually reporting, wouldn’t it be reasonable for Trump to expect anti-Trump coverage on Google News Search?

By slamming Google News Search as “rigged,” Trump appears to reveal an expectation that Google News should reflect what’s happening in the real world as he sees it, rather than what’s happening on news media websites.

Or it reveals that regardless of the weight of activity in favor of news sources Trump believes are biased against him, Google News Search should provide a balanced and neutral representation of all opinions and sources equally.

The rejection of the search-engine-as-internet-index model is common among governments and political leaders worldwide.

One famous example is the “right to be forgotten” idea, which has been put into practice as law in both the European Union and Argentina. The idea is that information on the internet can unfairly stigmatize a person, and citizens have the right for that information to be “forgotten,” which is to say made non-existent in search engine results.

Let’s say, for example, that a prominent person files for bankruptcy, and that 100 news sites and blogs on the internet record the fact. Twenty years later, well after the person has restored financial solvency, the old information is still available and findable via search engines, causing unfounded stigmatization.

A successful right-to-be-forgotten petition can remove reference to those pages from search results. The pages still exist, but the search engines don’t link to them when anyone searches for the person’s name.

The advocates of right-to-be-forgotten laws clearly believe that a search engine exists to reflect the real world as it is, or as it should be, and does not exist to reflect the internet as it is.

Google was recently caught in a controversy over an assumed return to the Chinese market with a custom China-only search engine that censors internet content in the same way that domestic sites are required to by the Chinese government. Hundreds of Google employees signed a letter in protest.

Google wants to “return” to the Chinese market. The Chinese government would not allow Google to operate a search engine accessible to Chinese citizens that accurately reflected what’s actually on the internet.

The examples go on and on.

What governments tend to have in common is that in political circles, it’s very difficult to find people advocating for the index-to-the-internet conception of what a search engine should be.

Why the search-engine-as-index idea is dead

Google’s self-stated mission is to “organize the world’s information and make it universally accessible and useful.”

Nebulous, yes. But for the purposes of this column, it’s telling that Google says that its mission is to organize, not the internet’s information, but the “world’s.”

The reality is that people search Google Search and other search engines because they want information about the world, not because they want information about what the internet collectively “thinks.”

And, in any event, the point is growing moot.

What the internet “thinks” is increasingly being gamed and manipulated by propagandists, bots, fake news, trolls, conspiracy theorists, and hackers.

Accurately reflecting all this manipulated information in search engines is valuable only to the manipulators.

Also: With each passing day, more information “searching” is happening via virtual assistants such as Google Assistant, Siri, Cortana, and Alexa.

In other words, virtual assistants are becoming the new search engines.

With augmented reality glasses and other highly mobile sources of information, search engines such as Google will have to increasingly become arbiters of what’s true, or supposed to be true, because the public will increasingly demand a single answer for its questions.

That’s why the old initiatives for your company’s presence on the internet — SEO, marketing, social media strategy and all the rest — have new urgency.

With each passing day, search engines exist less to index the internet and more to decide for us all what’s “true” and what’s “not true.”

It’s time to redouble your efforts to make sure that what Google thinks is true about your company really is true.

Source: This article was Published computerworld.com By Mike Elgan

Published in Search Engine

So, Chrome is ten years old. Officially in the double-digits. Soon it’ll be getting wispy chin-hairs and its voice will be cracking. That said, Google’s browser has accomplished a lot in the ten years that it’s been around. It went from a latecomer in the Browser Wars, with just a 1-percent market share early on launch, and now it’s the most-used browser in the world, with around 60-percent market share. We thought we’d take a look back at the few of the ways it became so dominant.

The Omnibox.png

1. The Omnibox

Children, you will not believe it, but once in web browsers, there was a field for entering the web address and a very different field for the search! Can you believe that? What a bunch of dirty animals we were then. However, when Chrome launched in 2008, it really tried to emphasize a "clean, simple, and efficient interface," and one of the options was to combine the URL box and the search box into one. Suddenly, users could enter a web address or simply switch off the search terms in the same place. It has saved a lot of clicks from the start and has only been improved by additional auto-complete capabilities. It's even able to answer questions and solve math problems before pressing Enter. "The Omnibox handles more than just URLs," Google said in its comic announcement to the world. "It also offers suggestions for search queries, top pages you've visited before, pages you've not visited yet but are popular, and more … you'll have a full-text search of your history You will not have to bookmark this page for digital cameras, just enter "digital camera" and quickly come back to it. "Ten years later, and it's amazing how much I still rely on these features, It's worth noting that all of this information went back to Google by default, but you could use other search engines (Yahoo, Ask, etc.) if you wanted.

2. Incognito mode

Google did not invent the concept of private (or more private) surfing. Apple's Safari actually had a privacy mode before Chrome, but that just shows what a good name can do. Incognito mode has become one of the Q tips of … well, there's a reason why some people still refer to it as a "porn mode". However, it can be used for much more, including checking out websites and profiles through the eyes of an anonymous third party or getting around the paywalls of news organizations.

3rd speed

You may forget that the biggest initial benefit of Chrome was not just that it was fast, but also that stupid fast, Thanks to very intelligent programming, Google claimed that Chrome's V8 JavaScript engine could work ten times faster than Safari or Firefox, and approximately 56 times faster than Microsoft's IE7 (then the dominant browser). This kind of speed paved the way for better in-browser applications like email, calendars and spreadsheets, which of course Google would do

Speed.jpg

4. Each tab is a separate process

This is one of those situations that you take away. Chrome has taken the revolutionary approach of making every open tab its own process. This meant that if a website had a berth code that would simply crash one tab and the other 19 open tabs would stay quiet and function normally. As a result, fewer browsers were completely reset, and as long as your computer had sufficient RAM, each tab was much less prone to delays than other browsers at the time. The other side of this coin is that Chrome can make a metric shit sound out of your computer's memory, especially if you tend to have many tabs open at the same time as I am. In the last few years, much has been done in favor of Google to minimize the amount of background tabs that can impact your system and battery life, but there are still many rivers crossing at this front. Other browsers, such as For example, Opera now has this approach, "Every tab is a process," but most are based on the open source Chromium architecture.

5. Make the web less annoying

It's easy to say how much the web sucks today, but the truth is that it used to suck a lot worse. How do you remember videos that automatically hunted stupidities into your eardrum for 30 seconds before you even found out which tab they came from? Chrome has set it up to mute these videos by default for an entire domain. Or how about extremely annoying popup and banner ads? Maybe fake play buttons that have taken you to a sketchy website? Google gave the sites 30 days to settle for a set of web standards. If it did not, Chrome automatically blocked the offensive content. In this way, 60 percent market share can choose to use their influence to get people to change their evil ways.

os.jpg

6. It is the first browser to become an operating system

What is the claim to fame? This small web browser became the basis for a whole operating system. Firefox, IE, Safari, Opera … none of them can claim the same. It is not an insignificant operating system either. Chrome OS runs Chromebooks, which account for approximately 60 percent of all mobile devices shipped to K-12 schools in the United States (as of Q4 2017). This will be a first computer experience for many of these children at a very formative time in their lives. Whether this will pay off for Google, remains to be seen.

Source: This article was Published gizmodo.com By Brent Rose

Published in Search Engine
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