NDLI: Detecting and filtering instant messaging spam - a global and personalized approach

Please wait, while we are loading the content...

Detecting and filtering instant messaging spam - a global and personalized approach

Content Provider	IEEE Xplore Digital Library
Author	Zhijun Liu Weili Lin Na Li Lee, D.
Copyright Year	2005
Description	Author affiliation: Dept. of Comput. Sci. & Eng., Ohio State Univ., Columbus, OH, USA (Zhijun Liu; Weili Lin; Na Li; Lee, D.)
Abstract	While instant message (IM) is gaining its popularity it is exposed to increasingly severe security threats. A serious problem is IM spam (spim) that is unsolicited commercial messages sent via IM messengers. Unlike e-mail spam (unsolicited bulk e-mails), which has been a serious security issue for a long time and a number of techniques have been proposed to cope with, spim has not received adequate attention from the research community yet, and traditional spam filtering techniques are not directly applicable to spim due to its presence information and real time nature. In this paper, we present a new architecture for detecting and filtering spim. With the unique infrastructure of IM systems spim detection and filtering can be achieved not only at the client (receiver) side - for a personalized filtering - but also at the server side and various IM gateways - for a global filtering. Our technique integrates a number of mature spam defending techniques with modifications for IM applications, such as Black/White List, collaborative feedback based filtering, content-based technique, and challenge-response based filtering. We also design and implement new techniques for efficient spim detection and filtering, including filtering methods based on IM sending rate, content based spim defending techniques, fingerprint vector based filtering, text comparison filtering, and Bayesian filtering. We provide an analysis of their performances based on experimental results.
Starting Page	19
Ending Page	24
File Size	256291
Page Count	6
File Format	PDF
ISBN	0780394275
DOI	10.1109/NPSEC.2005.1532048
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2005-11-06
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Computer science Protocols Feedback Unsolicited electronic mail Information security Collaboration Information filters Electronic mail Information filtering Computer security
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
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
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

A Personalized Spam Filtering Approach Utilizing Two Separately Trained Filters

Personalized Filtering of Polymorphic E-mail Spam

Automatic Personalized Spam Filtering through Significant Word Modeling

An e-mail client implementation with spam filtering and security mechanisms

Fast Effective Botnet Spam Detection

A Self-learning Spam Detecting System Model Based on Memory Rules

Multi-objective spam filtering using an evolutionary algorithm

Defense against Direct Spam over Internet Telephony by Caller Pre-validation

Collaborative Reputation-based Voice Spam Filtering

Detecting and filtering instant messaging spam - a global and personalized approach

Similar Documents

A Personalized Spam Filtering Approach Utilizing Two Separately Trained Filters

Personalized Filtering of Polymorphic E-mail Spam

Automatic Personalized Spam Filtering through Significant Word Modeling

An e-mail client implementation with spam filtering and security mechanisms

Fast Effective Botnet Spam Detection

A Self-learning Spam Detecting System Model Based on Memory Rules

Multi-objective spam filtering using an evolutionary algorithm

Defense against Direct Spam over Internet Telephony by Caller Pre-validation

Collaborative Reputation-based Voice Spam Filtering

Detecting and filtering instant messaging spam - a global and personalized approach