A decentralized and personalized spam filter based on social computing

Liu, Xin; Zhaojun, Xin; Shi, Leyi; Wang, Yao

doi:10.1109/iwcmc.2014.6906473

Cited by 4 publications

(2 citation statements)

References 8 publications

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“…Et al [17] proposed a spam filtering approach in which a collaborative and personalized spam filter based on social networks. This approach reflects the collaboration and personalization the of users with similar interest.…”

Section: Related Workmentioning

confidence: 99%

Spam Reduction by using E-mail History and Authentication (SREHA)

Yasin

2016

IJCNIS

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Abstract-Spam messages are today one of the most serious threats to users of E-mail messages. There are several ways to prevent and detect spam message, the most important way is filtering spam. Sometimes Filtering fails to discover some spam messages or even fails in the classification of non-spam messages as a spam messages. In this paper, we suggest a new effective method that reduces the spam messages by integrating prevention and detection techniques in one scheme. The reduction achieved by considering history and user authentication. This method based on issuing a certificate to each reliable user during the process of Email account Creation. The certificate used by Email servers to discard or forward ingoing or outgoing Emails. Each Server has to maintain white, gray and blacklist according to Email classification spam or ham, which determined by the user or by the contents examination of the message in terms of empty or contained only links without any text or by searching for a specific keywords in the subject and in the content. We believe that there are no bad or good E-mails forever, so the proposed model dynamically allows the transition of E-mail from one state to another state based on the number of received spam and ham messages.

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Section: Related Workmentioning

confidence: 99%

Spam Reduction by using E-mail History and Authentication (SREHA)

Yasin

2016

IJCNIS

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“…Xin Liu et al [5] proposed a spam filtering approach with push technology to share user's individual spam knowledge in social network. Spam filtering approaches like source based method and content based method are used.…”

Section: Literature Surveymentioning

confidence: 99%

Efficient Classifier for Detecting Spam in Social Networks through Sentiment Analysis

Nalarubiga¹,

Sindhuja²

2016

Asia. Jour. Rese. Soci. Scie. and Human.

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Social networking services are used for communication between people to share information through internet. The unbounded growth of content and users pushes the internet technologies to certain limitations. Data mining plays a major role in the field of social network to extract relevant content from the voluminous data which is being a phenomenal task, because of its dynamic nature the participation is more complex. The major problem, users face spammer's interaction which leads to misunderstanding and inconvenience for social activities. This work concentrates on detecting the spammer actions using feature relevance analysis and applying efficient classifier. The main objective of the proposed work is to find relationship between features and classifying patterns for detecting spam message from the unwanted sites. The system applies efficient classification algorithms after feature relevance analysis for detecting spam in better way. The outcome of this project will serve for the users participating in social networks for effective purpose like business, marketing and establishing contacts.

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Mobile Social Networks: Architecture, Privacy, Security Issues and Solutions

Lakshmi¹,

T²

2017

jcm

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A decentralized and personalized spam filter based on social computing

Cited by 4 publications

References 8 publications

Spam Reduction by using E-mail History and Authentication (SREHA)

Spam Reduction by using E-mail History and Authentication (SREHA)

Efficient Classifier for Detecting Spam in Social Networks through Sentiment Analysis

Mobile Social Networks: Architecture, Privacy, Security Issues and Solutions

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