NDLI: SOAP: A Social network Aided Personalized and effective spam filter to clean your e-mail box

Content Provider	IEEE Xplore Digital Library
Author	Ze Li Haiying Shen
Copyright Year	2011
Description	Author affiliation: Department of Electrical and Computer Engineering, Clemson University, SC 29631, USA (Ze Li; Haiying Shen)
Abstract	The explosive growth of unsolicited emails has prompted the development of numerous spam filtering techniques. A Bayesian spam filter is superior to a static keywordbased spam filter because it can continuously evolve to tackle new spam by learning keywords in new spam emails. However, Bayesian spam filters can be easily poisoned by avoiding spam keywords and adding many innocuous keywords in the emails. In addition, they need a significant amount of time to adapt to a new spam based on user feedback. Moreover, few current spam filters exploit social networks to assist spam detection. In order to develop an accurate and user-friendly spam filter, in this paper, we propose a SOcial network Aided Personalized and effective spam filter (SOAP). Unlike previous filters that focus on parsing keywords (e.g, Bayesian filter) or building blacklists, SOAP exploits the social relationship among email correspondents to detect the spam adaptively and automatically. SOAP integrates three components into the basic Bayesian filter: social closeness-based spam filtering, social interest-based spam filtering, and adaptive trust management. We evaluate performance of SOAP based on the trace data from Facebook. Experimental results show that SOAP can greatly improve the performance of Bayesian spam filters in terms of the accuracy, attack-resilience and efficiency of spam detection. We also find that the performance of Bayesian spam filters is the lower bound of SOAP.
Starting Page	1835
Ending Page	1843
File Size	505338
Page Count	9
File Format	PDF
ISBN	9781424499199
ISSN	0743166X
e-ISBN	9781424499212
DOI	10.1109/INFCOM.2011.5934984
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-04-10
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Simple object access protocol Bayesian methods Social network services Unsolicited electronic mail Accuracy Training
Content Type	Text
Resource Type	Article
Subject	Computer Science Electrical and Electronic Engineering

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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