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  • Title

    :

    Sybil Sentinel System based on Voting for Social Networks

    Authors

    :

    Abinaya V.1, ShebaKeziaMalarchelvi P. D.2

    Keywords

    :

    Online Social Network (OSN), Spam, Malware, Sybil’s, Sybil Attack,PageRank-style algorithm, Global Acceptance Rates.

    Issue Date

    :

    April– 2016

    Abstract

    :

    Unscrupulous users increasingly find Online Social Networking (OSN) platforms as lucrative targets for malicious activities, such as sending spam and spreading malware. In particular, attackers leverage the open nature of OSNs and send unwanted friend requests known as friend spam to legitimate users and it has been proven to be the most evasive malicious activity. This is evident by the fact that most OSN users experience friend spam on a substantially more frequent basis than they experience spam on their newsfeeds or other types of unwanted traffic. This might happen due to Sybil’s that generate friend spams. A Sybil attack happens when an insecure computer is hijacked to claim multiple identities which are used to send friend spams. Friend spams can be used to undermine social-graph-based defense schemes. Hence, allowing malicious accounts to effortlessly solicit friend requests to unsuspected users who may accept them, can lead to the collapse of a major defense line. The existing systems focus on using the social graph structure to isolate fakes and rely on the assumption that fakes can befriend only few real accounts. This assumption is not valid. Hence in this paper, a scalable defense system against Sybil’s that leverages userlevel activities is proposed. The proposed system uses a PageRank-style algorithm to appropriately assign the number of votes that one can cast on another node. Due to more negative votes from real users, Sybil’s would get low global acceptance rates and thus can be identified out.

    Page(s)

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    1-9

    ISSN

    :

    2347- 4734

    Source

    :

    Vol. 3, No.1, April 2016

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