Identifying Malicious Web Links and Their Attack Types in Social Networks

Authors

  • R. Hamsa Veni  Assistant Professor, Department of MCA, Sri Venkateswara College of Engineering and Technology, Chittoor, AP, India,
  • A.Hariprasad Reddy  PG Scholar, Department of MCA, Sri Venkateswara College of Engineering and Technology, Chittoor, AP, India
  • C.Kesavulu  PG Scholar, Department of MCA, Sri Venkateswara College of Engineering and Technology, Chittoor, AP, India

Keywords:

Cyber Attacks, DNS Information, URL, Malicious Address.

Abstract

Malicious URLs are wide wont to mount numerous cyber attacks together with spamming, phishing and malware. Detection of malicious URLs and identification of threat varieties area unit important to thwart these attacks. Knowing the type of a threat permits estimation of severity of the attack and helps adopt a good step. Existing strategies usually notice malicious URLs of one attack kind. During this paper, we have a tendency to propose methodology using machine learning to notice malicious URLs of all the popular attack varieties and establish the character of attack a malicious address tries to launch. Our method uses a range of discriminative options together with matter properties, link structures, webpage contents, DNS information, and network traffic. Several of those options are novel and extremely effective.

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IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology

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Published

2018-04-30

Issue

Volume 3, Issue 4, March-April-2018

Section

Research Articles

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How to Cite

[1]
R. Hamsa Veni, A.Hariprasad Reddy, C.Kesavulu, " Identifying Malicious Web Links and Their Attack Types in Social Networks, IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 3, Issue 4, pp.1060-1066, March-April-2018.