Cybers Security Analysis and Measurement Tools Using Machine Learning Approach - Archive ouverte HAL
Communication Dans Un Congrès Année : 2022

Cybers Security Analysis and Measurement Tools Using Machine Learning Approach

Taher Ghazal
  • Fonction : Auteur
Mohammad Kamrul Hasan
  • Fonction : Auteur
Nidal Al-Dmour
  • Fonction : Auteur
Waleed Al-Sit
  • Fonction : Auteur
Shayla Islam
  • Fonction : Auteur

Résumé

Artificial intelligence (AI) and machine learning (ML) have been used in transforming our environment and the way people think, behave, and make decisions during the last few decades [1]. In the last two decades everyone connected to the Internet either an enterprise or individuals has become concerned about the security of his/their computational resources. Cybersecurity is responsible for protecting hardware and software resources from cyber attacks e.g. viruses, malware, intrusion, eavesdropping. Cyber attacks either come from black hackers or cyber warfare units. Artificial intelligence (AI) and machine learning (ML) have played an important role in developing efficient cyber security tools. This paper presents Latest Cyber Security Tools Based on Machine Learning which are: Windows defender ATP, DarckTrace, Cisco Network Analytic, IBM QRader, StringSifter, Sophos intercept X, SIME, NPL, and Symantec Targeted Attack Analytic.
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Dates et versions

hal-03955353 , version 1 (25-01-2023)

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Citer

Taher Ghazal, Mohammad Kamrul Hasan, Raed Abu Zitar, Nidal Al-Dmour, Waleed Al-Sit, et al.. Cybers Security Analysis and Measurement Tools Using Machine Learning Approach. 2022 1st International Conference on AI in Cybersecurity (ICAIC), 2022, Victoria, TX, United States. pp.1-4, ⟨10.1109/ICAIC53980.2022.9897045⟩. ⟨hal-03955353⟩

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