Efficient Prevention Mechanism Against Spam Attacks for Social Networking Sites

A. Praveena and S. Smys
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A. Praveena: Jansons Institute of Technology, Department of Computer Science and Engineering
S. Smys: R.V.S. Technical Campus, Department of Computer Science and Engineering

A chapter in New Trends in Computational Vision and Bio-inspired Computing, 2020, pp 1095-1102 from Springer

Abstract: Abstract In recent days, the development in the Internet plays a major role in all types of activities that have been driven specialists to consider research frameworks to help the clients and applications in getting the directions by conveying nature of administration in systems. Some sorts of strategies are appropriate for giving security in correspondence to seized conditions, for example, portable registering, internet business, media transmission, and system administration. In such cases, service providers are focusing more on enriching the service access to end users. Since, there is an intermediate data theft or attack that was occurred during the broadcast process. Hence, an overview on different detection schemes are considered for successful determination and arrangement for attack recognition with various neural systems and some swarm computations has been proposed. The proposed strategies have been valuable for adequately identifying the system interruptions with the objective to give security to the Internet and to upgrade the nature of administration.

Keywords: Social network attack; Spam detection; Adaboost logitboost algorithm; Chaos genetic algorithm; Proposed hybrid optimization (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_111

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DOI: 10.1007/978-3-030-41862-5_111

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