PPT-Detecting and Characterizing Social Spam Campaigns

Author : yoshiko-marsland | Published Date : 2015-10-14

Hongyu Gao Jun Hu Christo Wilson Zhichun Li Yan Chen and Ben Y Zhao Northwestern University US Northwestern Huazhong Univ of Sci amp Tech China

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Detecting and Characterizing Social Spam Campaigns: Transcript


Hongyu Gao Jun Hu Christo Wilson Zhichun Li Yan Chen and Ben Y Zhao Northwestern University US Northwestern Huazhong Univ of Sci amp Tech China. Zhenhai Duan. Department of Computer Science. Florida State University. Outline. Motivation and background. SPOT algorithm on detecting compromised machines. Performance evaluation . Summary. 2. Motivation. A social initiative against mobile spam. Problem. Mobile revolution in India led to sharp decline in cost of SMS/Call. It makes sense to advertise on mobile.. Spam SMS and calls.. Gross infringement of customer’s privacy.. Lydia Song, Lauren Steimle, . Xiaoxiao. . Xu. Outline. Introduction to Project . Pre-processing . Dimensionality Reduction. Brief discussion of different algorithms. K-nearest. D. ecision tree. Logistic regression. Kurt Thomas. , Chris Grier, . Vern Paxson, Dawn Song. University of California, Berkeley. International Computer Science Institute. Motivation. Social networks are regular targets for abuse. 26% of URLs on Twitter lead to spam. Hongyu. . Gao. , . Yan . Chen, Kathy Lee, Diana . Palsetia. . and . Alok. . Choudhary. Lab for Internet and Security Technology (LIST). Department of EECS. Northwestern University. Background. 2. Background. . 1. Sai Koushik Haddunoori. Problem:. E-mail provides a perfect way to send . millions . of advertisements at no cost for the sender, and this unfortunate fact is nowadays extensively exploited by several . Ethan Grefe. December . 13, . 2013. Motivation. Spam email . is constantly cluttering inboxes. Commonly removed using rule based filters. Spam often has . very similar characteristics . This allows . Suranga Seneviratne. . . ✪. , . Aruna. Seneviratne . . ✪. , . Mohamed Ali (Dali) . Kaafar. . . , . Anirban. . Mahanti. . . , . Prasant. . Mohapatra. . ★. UNSW. . NICTA. , Australia. Spam:. Spam is unsolicited or undesired electronic junk mail. Characteristics of spam are:. Mass . mailing to large number of recipients. Usually a commercial advertisement. Annoying but usually harmless unless coupled with a fraud based phishing scam . Spam:. Spam is unsolicited or undesired electronic junk mail. Characteristics of spam are:. Mass . mailing to large number of recipients. Usually a commercial advertisement. Annoying but usually harmless unless coupled with a fraud based phishing scam . Detecting and Characterizing Social Spam Campaigns Hongyu Gao , Jun Hu , Christo Wilson , Zhichun Li , Yan Chen and Ben Y. Zhao Northwestern University, US Northwestern / Huazhong Univ. Spam is unsolicited . e. mail in the form of:. Commercial advertising. Phishing. Virus-generated . Spam. Scams. E.g. Nigerian Prince who has an inheritance he wishes to share. What is Bulk Email?. Bulk . 100 billion spam email per day. Easy to setup spam networks. Low cost of operation. Millions of dollars worth of time and . equipment to combat spam. Techniques used to combat spam. header tests. address whitelist/blacklist. Atliay. Betül . Delalic. Nijaz. PS Kryptographie und IT Sicherheit SS17. 1. INHALT. Definition . . Arten . Funktionsweise . T. echnische Voraussetzungen. . Auswirkungen . . Kosten . Rechtslage .

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