A Social approach to security: Using social networks to help detect malicious web content

In the past six years, tremendous growth in the size and popularity of social networking has fundamentally changed the way we use the Internet. As social aspects to the Internet continue to expand in both quantity and scope, security of the users of social networking sites and the data generated by them will ultimately become an unavoidable concern. This is a realization that malicious users have already had, as viruses, spyware, and phishing scams continue to propagate through social networks at an alarming rate. It is now becoming increasingly critical that the average user also understands this potential for the exploitation of trust among the social networking community. Yet, the security industry has been slow to respond in the act of providing adequate tools for protecting the user. This thesis describes the development of a proof-of-concept application that uses social networking data to aid in the detection of malicious web content as it propagates through the user\u27s network. While this methodology certainly has its limitations, including user impersonation and false positive rates, the results of testing this application against known phishing and malware sites with real-world user profiles have shown surprisingly positive results