aceA Comprehensive Survey: Evaluating the Efficiency of Artificial Intelligence and Machine Learning Techniques on Cyber Security Solutions
Given the continually rising frequency of cyberattacks, the adoption of artificial intelligence methods, particularly Machine Learning (ML), Deep Learning (DL), and Reinforcement Learning (RL), has become essential in the realm of cybersecurity. These techniques have proven to be effective in detecting and mitigating cyberattacks, which can cause significant harm to individuals, organizations, and even countries. Machine learning algorithms use statistical methods to identify patterns and anomalies in large data…
Machine learning, deep learning and reinforcement learning techniques improve cybersecurity systems' ability to detect and mitigate cyberattacks including malware and intrusions.
ML, DL and RL-based cybersecurity solutions are susceptible to adversarial attacks, and ChatGPT-like tools can be manipulated to threaten data integrity, confidentiality and availability.
Effectiveness claims are constrained by data quality, interpretability limits, and susceptibility to adversarial attacks that can undermine ML-based defenses.
Evidence
- Peer-reviewedIEEE Access2024-01-01
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Truvace Impact Record TRV-2026-0792, v1: “A Comprehensive Survey: Evaluating the Efficiency of Artificial Intelligence and Machine Learning Techniques on Cyber Security Solutions.” Truvace, 2026-08-16. /record/TRV-2026-0792 (accessed at citation time). sha256 e34481d0ee310218…
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