Graph-based algorithms and models for security, healthcare, and finance

Graph mining;Information propagation;Behavior characterization;Malware detection;Comment spammer detection;Smoking abstinence and relapse;Alcohol abstinence and relapse;Insider trading

Tamersoy, Acar ; Chau, Duen Horng (Polo) Computational Science and Engineering Navathe, Shamkant B. De Choudhury, Munmun Basole, Rahul C. Roundy, Kevin A. ; Chau, Duen Horng (Polo)

University:Georgia Institute of Technology

Department:Computational Science and Engineering

关键词: Graph mining;    Information propagation;    Behavior characterization;    Malware detection;    Comment spammer detection;    Smoking abstinence and relapse;    Alcohol abstinence and relapse;    Insider trading;   

Others  :  https://smartech.gatech.edu/bitstream/1853/54986/1/TAMERSOY-DISSERTATION-2016.pdf

美国|英语

来源: SMARTech Repository

【 摘 要 】

Graphs (or networks) are now omnipresent, infusing into many aspects of society. This dissertation contributes unified graph-based algorithms and models to help solve large-scale societal problems affecting millions of individuals' daily lives, from cyber-attacks involving malware to tobacco and alcohol addiction. The main thrusts of our research are: (1) Propagation-based Graph Mining Algorithms: We develop graph mining algorithms to propagate information between the nodes to infer important details about the unknown nodes. We present three examples: AESOP (patented) unearths malware lurking in people's computers with 99.61% true positive rate at 0.01% false positive rate; our application of ADAGE on malware detection (patent-pending) enables to detect malware in a streaming setting; and EDOCS (patent-pending) flags comment spammers among 197 thousand users on a social media platform accurately and preemptively. (2) Graph-induced Behavior Characterization: We derive new insights and knowledge that characterize certain behavior from graphs using statistical and algorithmic techniques. We present two examples: a study on identifying attributes of smoking and drinking abstinence and relapse from an addiction cessation social media community; and an exploratory analysis of how company insiders trade. Our work has already made impact to society: deployed by Symantec, AESOP is protecting over 120 million people worldwide from malware; EDOCS has been deployed by Yahoo and it guards multiple online communities from comment spammers.