A new study by Ben-Gurion University of the Negev (BGU) researchers predicts that a new generation of malware (software written for malicious purposes like identity theft) could steal data on human behavior patterns, which is more dangerous than traditional, detectable attacks.
In the newly published paper, “Stealing Reality,” Dr. Yaniv Altshuler and Dr. Yuval Elovici from BGU discuss malware threats that extract personal information about relationships in a real-world social network, as well as characteristic information about individuals in the network. Using mathematical models, based on actual mobile network data, the researchers demonstrated that malware attacks could be adapted to follow human behavior on social networks.
According to the researchers, “Many social networks collect important user data such as age, occupation and role, personality and more to create a ‘rich identity.’ With access to such sensitive information, the possibility for significantly more targeted and dangerous attacks is now open. There is a level of trust generated among users connected via social networks and these new threats, unbeknownst to the user, seek to violate it.”
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