A Perspective View on Sybil Attack Defense Mechanisms in Online Social Networks

Blessy Antony and S. Revathy
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Blessy Antony: Sathyabama Institute of Science and Technology (Deemed to Be University)
S. Revathy: Sathyabama Institute of Science and Technology (Deemed to Be University)

A chapter in New Trends in Computational Vision and Bio-inspired Computing, 2020, pp 675-679 from Springer

Abstract: Abstract Online Social Networks (OSN) offers a dais for the individuals to create a social affiliation or network with people of common interest. These sites plays a vital role in people’s lives ranging from entertainment to various business. Application Program Interface developed for OSN can be used to avail services offered by other third party applications. OSNs obliges as a consistent identity for web services. Due to the open nature of Social Networking Sites, they are more susceptible to malicious attacks. One major attack is creation of bogus identities called Sybil attack. This attack leads to outflow of private information, forged reviews and various fraudulent activities. Different methods such as graph based techniques, machine learning based techniques are there to detect and prevent Sybil attack in OSN. This paper provides a perspective view on various research works implemented on this area.

Keywords: Online Social Network (OSN); Sybil attack; RenRen; Twitter; Facebook (search for similar items in EconPapers)
Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-030-41862-5_66

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DOI: 10.1007/978-3-030-41862-5_66

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