Evasion Techniques in Cybersecurity: An In-Depth Analysis

Because of the rising sophistication of cybersecurity threats, it is imperative to have a thorough grasp of the evasion strategies used by malevolent actors. This study offers a detailed analysis of evasion strategies in several cybersecurity sectors, such as intrusion detection systems, network security, and endpoint protection. This paper employs a methodical approach to examine the development of these methods, showcases actual case studies, and suggests approaches for detection and mitigation. The findings emphasize how crucial it is to conduct ongoing research and development to combat new cyber threats. Key discoveries are reviewed, and directions for further research are indicated.

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Publication Details

Published
2024-12-20
DOI
https://doi.org/10.1109/icaiqsa64000.2024.10882284
Citations
3
Primary Topic
Adversarial Robustness in Machine Learning
Type
article
Field-Weighted Citation Impact
1.04
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article

Evasion Techniques in Cybersecurity: An In-Depth Analysis

Gopal Sakarkar, Anil V. Turukmane, Nilesh Shelke, Ganesh Khekare et al.
3 citations
Adversarial Robustness in Machine Learning
1.04
article

Evasion Techniques in Cybersecurity: An In-Depth Analysis

Gopal Sakarkar, Anil V. Turukmane, Nilesh Shelke, Ganesh Khekare, Siddhant Buchade
article en
3 citations

Abstract

Because of the rising sophistication of cybersecurity threats, it is imperative to have a thorough grasp of the evasion strategies used by malevolent actors. This study offers a detailed analysis of evasion strategies in several cybersecurity sectors, such as intrusion detection systems, network security, and endpoint protection. This paper employs a methodical approach to examine the development of these methods, showcases actual case studies, and suggests approaches for detection and mitigation. The findings emphasize how crucial it is to conduct ongoing research and development to combat new cyber threats. Key discoveries are reviewed, and directions for further research are indicated.

Symbiosis International University (IN), MIT World Peace University (IN), Vellore Institute of Technology University (IN)
Openalex Percentile: Top 18%
Adversarial Robustness in Machine Learning
1.04
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