PPT-Web Spam Discussion paper

Adam Kilgarriff Vit Suchomel Lexical Computing Ltd UK NLP Laboratory Masaryk Univ Brno Cz 1 The particular Moroccan oil could very well moisturize dry skin handing it out an even makeup including easier different textures. Slides adapted from . Information Retrieval and Web Search, Stanford University, Christopher Manning and Prabhakar Raghavan. CS345A, Winter 2009: Data Mining. Stanford University, Anand Rajaraman, Jeffrey D. Ullman. Zhenhai Duan. Department of Computer Science. Florida State University. Outline. Motivation and background. SPOT algorithm on detecting compromised machines. Performance evaluation . Summary. 2. Motivation. 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. Author : Kirill . Levchenko. , Andreas . Pitsillidis. , . Neha. . Chachra. , Brandon Enright, . M’ark. . F’elegyh’azi. , Chris Grier, Tristan Halvorson, Chris . Kanich. , Christian . Kreibich. . 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 . Suranga Seneviratne. . . ✪. , . Aruna. Seneviratne . . ✪. , . Mohamed Ali (Dali) . Kaafar. . . , . Anirban. . Mahanti. . . , . Prasant. . Mohapatra. . ★. UNSW. . NICTA. , Australia. Vacha Dave . +. , Saikat Guha. ★. and Yin Zhang *. . + . University of California, San Diego. . ★ . Microsoft Research . India. . * The University of Texas at Austin. . Internet Advertising Today. rhetorical context?. SPAM . is a set of tools we’ll use to look at . rhetorical context . and make decisions about how to best communicate our ideas. .. S. ituation:. P. urpose:. A. udience:. M. ode:. 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 . threat to Internet users. A collaborative approach. is needed to provide the best spam-mitigation solutions. and security protection. . The Challenge of Spam. Different stakeholders are taking different steps. 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 . Zhang . Yanbin. , SG17/Q5 Rapporteur. Geneva, Switzerland . March, 2016. M. ain Content. C. hapter 1. Introduction of Spam . C. hapter 2. The Objective and Mission for Q5. C. hapter 3. The Position of Specific Projects in Q5. Agenda. Next Generation Antispam Protection . Forefront Overview. Forefront Security for Exchange Server. Forefront Online Security for Exchange. Hybrid Software + Services Solution. Summary. Q&A. Amir . Houmansadr. CS660: Advanced Information Assurance. Spring 2015. Content may be borrowed from other resources. . See the last slide for acknowledgements!. Our Knowledge of Spam. What do we know about spam?.