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Machine Learning Susses Out Social-Network Fraud
CowboyRobot writes "Machine learning techniques can be used to detect fraud and spies on social networks based on certain features, such as the number of followers and the number of devices used to access the network. Certain characteristics of social-network accounts have a high correlation with fraud and can be used to differentiate between real and fake accounts, a researcher presenting at the SOURCE Boston Conference said this week. Using machine learning techniques, Vicente Diaz, a senior security analyst with security software firm Kaspersky Lab, found that seven characteristics of Twitter profiles could identify fraudulent accounts 91% of the time. The number of devices from which a user accesses the service, the ratio of followers to people following an account, the average number of tweets to each person, and the number of tweets to an unknown receiver are all features that correlate strongly to fraudulent accounts, he says."
it is called "reconnaissance" mission.
Ergo, I am the Spy.
Or am I the Scout who is the Spy?
the ratio of followers to people following an account
doesn't equal one, then fraud.
I feel sorry for everyone named JAMES BOND.
Their method recognizes 97% of all profiles on FB as fraud, because they are.
In related news, social network machine learning fraud bots get algorithm update based on current fraud detection algorithms.
What's good about this, is that the few false positives would be from annoying assholes, so we can ban them too and nothing much will be lost.
AC raises a good point: people are pretty good at ignoring spam. I just ignored it. Is this a really big problem on social network sites? The article says somewhere between 9 and 20% of user accounts on facebook are for spam. Who the hell is adding random people as friends they've never heard of before, then can't tell spam from actual communication?
My guess is this is annoying for facebook and advertising firms who are paying money for sanctioned spamming, and they want to make sure they're not advertising to spam accounts. I mean, companies are, I guess, dropping serious money on their social media pages and accounts. To find out the only people who are following those accounts are other advertisers must really make them stop and wonder what the hell they're doing. Hilarious.
Hmm. Your ideas are intriguing to me and I wish to subscribe to your newsletter.
This is pretty much useless. If people start using software filters to detect social-network frauds and spammers, the frauds and spammers will simply reverse-engineer the filter algorithm and adjust their "number of devices from which a user accesses the service, the ratio of followers to people following an account, the average number of tweets to each person, and the number of tweets to an unknown receiver" to whatever values don't trigger the fraud filter.
The spammers evolve just as fast as the filters.
http://www.geoffreylandis.com
Because every anime roleplay account I've seen have over 2000 friends.
... If I had a facebook account. Using my Orkut account as an example, the software would find that I only use a single device to access (desktop pc), have few friends (but genuine) and post few reviews and comments (only what I consider important).
:-)
In conclusion, as I do not access facebook even from my watch, do not comment on every single thing I do in my day and not have "thousands of followers", so I can only be a fraud
Religion: The greatest weapon of mass destruction of all time
Another reason to never use any social network ever.
(Hint: The social network is actually the spy in the equation, and I didn't need machine learning to figure that out.)
found that seven characteristics of Twitter profiles could identify fraudulent accounts 91% of the time.
Taking the 91% number as accurate for argument's sake, what are the false positive and false negative rates? Even a 1% false positive or false negative rate would be quite a lot of accounts when you consider how many millions of twitter accounts there are out there.
Most of the information I put on my facebook account is noise. I didn't really attend 10 different universities, speak 15 different languages, or was born in that other country.
The only people that care about this are marketers. But even then, does it matter if the account is real or not? I haven't seen any good evidence that social marketing can directly relate to in-store or online purchases. Its all a scam.
Come on slashdot - fix this little faggot. Regular people have to scroll down forever to get to the first real post!
Fix this crap, slashdot!
"Windows is like the faint smell of piss in a subway: it's there, and there's nothing you can do about it." - Charlie Br
The sole indicator needed for detecting social network fraud is the existing of an account on a social network.
Everyone lies...
The number of devices from which a user accesses the service.
So does Twitter just publicly disclose a simple device count or the detailed information on all devices? If the latter, isn't that a whopping security hole to be exploited by people looking for targets with known vulnerable devices.
I am becoming gerund, destroyer of verbs.
Fake accounts are easy to spot - just look if their profile picture looks real.
You're embarassing yourself Jeremiah Cornelius http://slashdot.org/comments.pl?sid=3581857&cid=43276741 since you posted that using your registered username by mistake (instead of your usual anonymous coward submissions by the 100's the past 2-3 months now on slashdot) giving away it's you spamming this forums almost constantly, just as you have in the post I just replied to.