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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM25220

Detecting DDoS Attack using Multi-Agent System

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM25220

Volume:

7 |

8 |

Aug 2023

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
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Not assigned

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

DMP

Dr. M. Purushotham

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Abstract

Distributed denial of service attacks are the acts aiming at the prostration of the limited service coffers within a target host and leading to the rejection of the valid stoner service request. During a DDoS attack, the target host is attacked by multiple, coordinated attack programs, frequently with disastrous results. thus, the effective discovery, identification, treatment, and forestallment of DDoS attacks are of great significance. Grounded on the exploration of DDoS attack principles, features and styles, combined with the possible scripts of DDoS attacks, aMulti-Agent System- grounded DDoS attack discovery system is proposed in this paper to apply DDoS attack discovery for high- cargo communication scripts. In this paper, we take themulti-layer communication protocols into consideration to carry out categorizing and assaying DDoS attacks. Especially given the high- cargo communication scripts, we make an trouble to exploring a possible DDoS attack discovery system with employing a target- drivenmulti-agent modeling methodology to descry DDoS attacks counting on considering the essential characteristics of DDoS attacks. According to the trials verification, the proposed DDoS attack discovery system plays a better discovery performance and is less applicable with the data unit granularity. Meanwhile, the system can effectively descry the target attacks after the sample training. The discovery scheme grounded on the agent technology can nicely perform thepre-set actions and with good scalability to meet the follow- farther conditions of designing and enforcing the prototype software.

KEYWORDS

Bayesian classifier DDoS attack detec tion Agent technology.

Cite This Article

Dr. M. Purushotham, "Detecting DDoS Attack using Multi-Agent System," International Journal of Scientific Research in Engineering and Management, vol. 7, no. 8, Aug 2023.

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Publication Date

8/17/2023

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Double-Blind Peer Review

Review Rounds: 2

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Conflict of Interest

The authors declare no conflict of interest related to this research work.

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