A Pragmatic Optimal Approach for Detection of Cyber Attacks using Genetic Programming
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- @InProceedings{Mane:2020:CINTI,
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author = "Nikhil Mane and Anjali Verma and Arti Arya",
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title = "A Pragmatic Optimal Approach for Detection of Cyber
Attacks using Genetic Programming",
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booktitle = "2020 IEEE 20th International Symposium on
Computational Intelligence and Informatics (CINTI)",
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year = "2020",
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pages = "71--76",
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abstract = "Cyber-attacks are becoming an increasing threat to
people and daily businesses regularly. Attackers have
also been evolving their strategies and methods with
time. Every attack carried out has the potential to
exploit the system on a large scale. Various Artificial
Intelligence (AI) algorithms are used to defend such
vulnerabilities. This paper analyzes a novel attack and
extracts attackers' intrusion scenarios. Evolutionary
Computation Techniques have been remarkably used in the
field of cybersecurity. This paper particularly
discusses the Distributed Denial Of Service (DDoS)
attack. The effect of this attack ranges from a
disturbance of an elementary service to causing major
threats to critical services. In recent times these
attacks have become more intricate and carry a
significant threat. Therefore, there is a necessity for
an intelligent Intrusion Detection System (IDS) to
recognize attacks. In this study, work is carried on
the latest dataset called Modern DDoS. This paper
comprises of comparing the results of six established
classification techniques: Random Forest, Naive Bayes,
Stochastic Gradient Descent, Decision Trees, Logistic
Regression, and K-Nearest Neighbour (KNN) with the
proposed Genetic Programming model. The results show
that the proposed Genetic Programming model has better
accuracy when compared to various existing methods.",
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keywords = "genetic algorithms, genetic programming",
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DOI = "doi:10.1109/CINTI51262.2020.9305844",
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ISSN = "2471-9269",
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month = nov,
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notes = "Also known as \cite{9305844}",
- }
Genetic Programming entries for
Nikhil Mane
Anjali Verma
Arti Arya
Citations