Facebook Buys Startup WhatsApp for $19 Billion

Facebook announced it will buy mobile-messaging startup WhatsApp for US$19 billion in cash and stock. The transaction, notes Reuters, “places the world's largest social network closer to the heart of mobile communications and may bring younger users into the fold.” WhatsApp had 450 million users in five years and is now reportedly adding another million daily. It is billed as an alternative to SMS, allowing users to exchange unlimited text messages at no cost for a year. After a year’s use, a user is required to subscribe to the service, which is now 99 cents for one year. (Reuters)(National Public Radio) 

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Facebook Award Bug Bounty to UK Researcher

Facebook awarded $20,000 to UK security researcher Jack Whitton who found a critical bug in the social network’s text-messaging service that would let attackers access and use someone’s account by sending a message. The attack uses Facebook’s feature that permits users to log in with a telephone number linked to their account. Whitton, who also participates in other bug bounty programs, discovered the hacker can tie his own phone number to the target account, then reset the password with a text message. Whitton posted a detailed accounting of the flaw on his website < http://blog.fin1te.net/post/53949849983/hijacking-a-facebook-account-with-sms >.
(BBC)(Help Net Security)(fin1te -- Whitton website)

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App protects Facebook users from hackers

ScienceDaily (Oct. 8, 2012) — Cyber-crime is expanding to the fertile grounds of social networks and University of California, Riverside engineers are fighting it.

A recent four-month experiment conducted by several UC Riverside engineering professors and graduate students found that the application they created to detect spam and malware posts on Facebook users' walls was highly accurate, fast and efficient.

The researchers also introduced the new term "socware" -- pronounced "sock-where" -- to describe a combination of "social malware," encompassing all criminal and parasitic behavior on online social networks.

Their free application, MyPageKeeper, successfully flagged 97 percent of socware during the experiment. In addition, it was only incorrect -- flagging posts of socware that did not fit into those categories -- 0.005 percent of the time.

The researchers also found that it took an average of .0046 seconds to classify a post, which is far quicker than the 1.9 seconds it takes using the traditional approach of web site crawling. MyPageKeeper's more efficient classification also translates to lower costs, cutting expenses by up to 40 times.

"This is really the perfect recipe for socware detection to be viable at scale: high accuracy, fast, and cheap," said Harsha V. Madhyastha, an assistant professor of computer science and engineering at UC Riverside's Bourns College of Engineering.

Madhyastha conducted the research with Michalis Faloutsos, a professor of computer science and engineering, and Md Sazzadur Rahman and Ting-Kai Huang, both Ph.D. students. Rahman presented the paper outlining the findings at the recent USENIX Security Symposium 2012.

During the four-month experiment, which was conducted from June to October 2011, the researchers analyzed more than 40 million posts from 12,000 people who installed MyPageKeeper. They found that 49 percent of users were exposed to at least one socware post during the four months.

"This is really an arms race with hackers," said Faloutsos, who has studied web security for more than 15 years. "In many ways, Facebook has replaced e-mail and web sites. Hackers are following that same path and we need new applications like MyPageKeeper to stop them."

The application, which is already attracting commercial interest, works by continuously scanning the walls and news feeds of subscribed users, identifying socware posts and alerting the users. In the future, the researchers are considering allowing MyPageKeeper to remove malicious posts automatically.

The key novelty of the application is that it factors in the "social context" of the post. Social context includes the words in the post and the number of "likes" and comments it received.

For example, the researchers determined that the presence of words -- such as 'FREE,' 'Hurry,' 'Deal' and 'Shocked' -- provide a strong indication of the post being spam. They found that the use of six of the top 100 keywords is sufficient to detect socware.

The researchers point out that users are unlikely to 'like' or comment on socware posts because they add little value. Hence, fewer likes or comments are also an indicator of socware.

Furthermore, MyPageKeeper checks URLs against domain lists that have been identified as being responsible for spam, phishing or malware. Any URL that matches is classified as socware.

During the four-month experiment, the researchers also found:

A consistently large number of socware notifications are sent every day, with noticeable spikes on a few days. For example, 4,056 notifications were sent on July 11, 2011, which corresponded to a scam that went viral conning users into completing surveys with the pretext of fake free products.Only 54 percent of socware links have been shortened by URL shorteners such as bit.ly and tinyurl.com. The researchers thought this number would be higher because URL shorteners allow the web site address to be hidden. They also found that many scams use somewhat obviously "fake" domain names, such as http://iphonefree5. com and http://nfljerseyfree. com, but users seem to fall for it and click the link.Certain words are much more likely to be found in Facebook socware than in e-mail spam. For example, "omg" is 332 times more likely to appear in Facebook socware. Meanwhile, "bank" is 56 times more likely to appear in e-mail spam.Twenty percent of socware links are hosted inside of Facebook.

This activity is so high that the researchers expect that Facebook will have to do more to protect its users against socware.

"Malware on Facebook seems to be hosted and enabled by Facebook itself," Faloutsos said. "It's a classic parasitic kind of behavior. It is fascinating and sad at the same time."

App: https://apps.facebook.com/mypagekeeper/

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The above story is reprinted from materials provided by University of California - Riverside. The original article was written by Sean Nealon.

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Looking good on Facebook

ScienceDaily (Apr. 23, 2012) — A European study of students using online social networking shows that users tend to make new connections via their own more attractive friends regardless of whether they are male or female.

Writing in the International Journal of Web Based Communities, Christina Jaschinski and Piet Kommers of the University of Twente, The Netherlands, explain how they have carried out a preliminary study to try and understand better how relationships develop online. "Social network sites have become essential for managing relationships in today's life," they explain. "Therefore, it is increasingly important for scientists to understand how impressions are formed and connections develop in the virtual world."

The advent of the so-called "Web 2.0," the interactive and sharing version of the world wide web, which includes blogs, video and photo sharing sites, social bookmarking, social media, microblogging sites, such as twitter, and online social networks including Google+ and Facebook, has enabled the sharing, connecting and collaboration of people all over the world with very little technological friction. This has grown considerably especially since the marketing of relatively inexpensive smart phones and the growth of broadband internet connectivity.

People meet, connect and interact in these online communities by using a profile as a representation of their identity, the team explains. Unfortunately, the formation of impressions about a person online almost entirely lacks non-verbal cues other than those based on their profile photo and the status and content of their friends' profiles. Users can control their photo, but not how it is perceived but more importantly they cannot control the profiles of other users. This latter point is not so different from the social networks we form offline, where a newcomer may judge a person based on the company they keep. At least offline the person has the opportunity to project themselves in a more comprehensive manner and deflect such judgements by their own actions and behaviour rather than just that of their friends and associates.

The team recruited 78 students who use perhaps the most popular online social network, Facebook, apparently fast approaching 1 billion users, to investigate how the attractiveness of Facebook friends affects the impressions formed of friends of friends by users. The study simply involved mocking up Facebook profiles and asking the students to carry out a "hot or not" type assessment based purely on the visual appearance of the user's profile photo within the page. The team found that someone is considered more likeable and seen as a potential friend when they are associated with good-looking friends.

The findings could have implications not only for social scientists hoping to understand these new modes of interpersonal behaviour but might also be used by companies and other organisations hoping to benefit from social networking applications. Additionally, the extension of traditional networking for marketing and job hunting offered by the online world is increasingly important and users are more aware of how they are creating an impression, good or bad, in the online world.

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The above story is reprinted from materials provided by Inderscience, via AlphaGalileo.

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Christina Jaschinski and Piet Kommers. Does beauty matter? The role of friends' attractiveness and gender on social attractiveness ratings of individuals on Facebook. International Journal of Web Based Communities, 2012 (in press)

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Facebook is a community

ScienceDaily (Jan. 25, 2012) — Researchers in Italy have used two high-speed computer algorithms to analyse the connections between a large sub-set of the more than half a billion users of the social networking site Facebook to reveal that the system has a very strong structure. The study, published in the International Journal of Social Network Mining, shows that Facebook has a well-defined community structure that follows a statistical power law in which there are a huge number of people with few connections and a much smaller number with a large number of connections.

Emilio Ferrara of the Department of Mathematics, at the University of Messina, has anonymised Facebook data and used two sophisticated algorithms to uncover the hidden network structure across Facebook's millions of users. His research demonstrates that as with many social networks in the everyday world and networks found in nature, Facebook has the three common properties of such systems. First, it demonstrates the "small world" effect, known colloquially as "six degrees of separation" in which it is frequently possible to connect the majority of members, the nodes, of a network with all the other members through a small number of mutual friends or connections.

Secondly, Facebook follows the power law degree distribution where there are many users with a small number of connections. There are thus fewer and fewer users with more and more connections and only a very small number of people with a huge number of connections. Thirdly, Facebook rather obviously manifests as a community of interacting users rather than a collection of individuals.

One might imagine that so much is obvious given the popularity and activity of Facebook, which is the number one web destination and "application" for many millions of people. However, in order to prove that it is indeed a community-type network a statistical analysis of the type carried out by Ferrara was required. With the proof in hand, one might now investigate the structure of the Facebook network in more detail, apply the findings to other social networks, such as Twitter and LinkedIn in order to spot the differences and similarities with a view to informing those who operate and create such networks. The same research might also point the way to a better understanding of natural networks, such as offline human communities, insect colonies or even the spread of emergent diseases.

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Journal Reference:

Emilio Ferrara. Community structure discovery in Facebook. International Journal of Social Network Mining, 2012; 1 (1): 67 DOI: 10.1504/IJSNM.2012.045106

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