Integration of AI in Cybersecurity: Current Trends with a Focused Look at Intrusion Detection Applications

• URL: http://arxiv.org/abs/2605.17219v1
• Date: Sun, 17 May 2026 01:44:23 GMT
• Title: Integration of AI in Cybersecurity: Current Trends with a Focused Look at Intrusion Detection Applications
• Abstract summary: integration into Cybersecurity has garnered significant attention.<n>Current trends include the use of Generative AI, Natural Language Processing, Federated Learning for privacy-preserving collaborative training.<n>Aims to uncover meaningful insights through comparative analysis based on the employed AI techniques and reported performance.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Artificial Intelligence (AI) is widely adopted today for its ability to detect patterns, automate tasks, and reduce time and cost across various applications. Its integration into Cybersecurity has garnered significant attention, particularly in areas such as intrusion detection, malware analysis, and phishing or spam detection. As AI and cybersecurity evolve, new methods and approaches emerge regularly. Current trends include the use of Generative AI, Natural Language Processing, Federated Learning for privacy-preserving collaborative training, and eXplainable AI to ensure interpretability and trust, which are vital in cybersecurity. This paper presents an interesting review of current AI-based cybersecurity trends, focusing on intrusion detection approaches and aiming to uncover meaningful insights through comparative analysis based on the employed AI techniques and reported performance.

Related papers

• AI in Cyberpsychology: A systematic literature review of Cybersecurity enhancement by using AI for analyzing psychology of Victims, Attackers, and Defenders [0.6524460254566904]
  Cyberpsychology (CPSY) is defined as the use of psychology to enhance cybersecurity applications.<n>The review presents a comprehensive taxonomy of the cyber-security applications, the AI methodologies used, and the psychological concepts employed across the studies.
  arXiv  Detail & Related papers  (2026-07-14T17:18:30Z)
• Cyber Threat Intelligence for Artificial Intelligence Systems [0.0]
  We investigate how cyber threat intelligence may evolve to address attacks that target AI systems.<n>We outline what an AI-oriented threat intelligence knowledge base should contain.<n>We discuss techniques for measuring similarity between collected indicators and newly observed AI artifacts.
  arXiv  Detail & Related papers  (2026-03-05T11:37:47Z)
• Trojans in Artificial Intelligence (TrojAI) Final Report [52.6138928911574]
  TrojAI was launched to confront an emerging vulnerability in modern artificial intelligence: the threat of AI Trojans.<n>TrojAI helped to map out the complex nature of the threat and pioneered foundational detection methods.<n>Report concludes with lessons learned and recommendations for advancing AI security research.
  arXiv  Detail & Related papers  (2026-02-06T19:52:14Z)
• ORCA -- An Automated Threat Analysis Pipeline for O-RAN Continuous Development [57.61878484176942]
  Open-Radio Access Network (O-RAN) integrates numerous software components in a cloud-like deployment, opening the radio access network to previously unconsidered security threats.<n>Current vulnerability assessment practices often rely on manual, labor-intensive, and subjective investigations, leading to inconsistencies in the threat analysis.<n>We propose an automated pipeline that leverages Natural Language Processing (NLP) to minimize human intervention and associated biases.
  arXiv  Detail & Related papers  (2026-01-20T07:31:59Z)
• Autonomous Threat Detection and Response in Cloud Security: A Comprehensive Survey of AI-Driven Strategies [0.0]
  Cloud computing has changed online communities in three dimensions, which are scalability, adaptability and reduced overhead.<n>There are serious security concerns which are brought about by its distributed and multi-tenant characteristics.<n>The old methods of detecting and reacting to threats are becoming less and less effective even in the advanced stages of cyberattacks of cloud infrastructures.<n>The recent trend in the field of addressing these limitations is the creation of technologies of artificial intelligence (AI)
  arXiv  Detail & Related papers  (2026-01-06T04:19:27Z)
• Position: Mind the Gap-the Growing Disconnect Between Established Vulnerability Disclosure and AI Security [56.219994752894294]
  We argue that adapting existing processes for AI security reporting is doomed to fail due to fundamental shortcomings for the distinctive characteristics of AI systems.<n>Based on our proposal to address these shortcomings, we discuss an approach to AI security reporting and how the new AI paradigm, AI agents, will further reinforce the need for specialized AI security incident reporting advancements.
  arXiv  Detail & Related papers  (2024-12-19T13:50:26Z)
• Artificial Intelligence as the New Hacker: Developing Agents for Offensive Security [0.0]
  This paper explores the integration of Artificial Intelligence (AI) into offensive cybersecurity. It develops an autonomous AI agent, ReaperAI, designed to simulate and execute cyberattacks. ReaperAI demonstrates the potential to identify, exploit, and analyze security vulnerabilities autonomously.
  arXiv  Detail & Related papers  (2024-05-09T18:15:12Z)
• Review of Generative AI Methods in Cybersecurity [0.6990493129893112]
  This paper provides a comprehensive overview of the current state-of-the-art deployments of Generative AI (GenAI) It covers assaults, jailbreaking, and applications of prompt injection and reverse psychology. It also provides the various applications of GenAI in cybercrimes, such as automated hacking, phishing emails, social engineering, reverse cryptography, creating attack payloads, and creating malware.
  arXiv  Detail & Related papers  (2024-03-13T17:05:05Z)
• Testing autonomous vehicles and AI: perspectives and challenges from cybersecurity, transparency, robustness and fairness [53.91018508439669]
  The study explores the complexities of integrating Artificial Intelligence into Autonomous Vehicles (AVs) It examines the challenges introduced by AI components and the impact on testing procedures. The paper identifies significant challenges and suggests future directions for research and development of AI in AV technology.
  arXiv  Detail & Related papers  (2024-02-21T08:29:42Z)
• A Survey on Explainable Artificial Intelligence for Cybersecurity [14.648580959079787]
  Explainable Artificial Intelligence (XAI) aims to create machine learning models that can provide clear and interpretable explanations for their decisions and actions. In the field of network cybersecurity, XAI has the potential to revolutionize the way we approach network security by enabling us to better understand the behavior of cyber threats.
  arXiv  Detail & Related papers  (2023-03-07T22:54:18Z)
• Proceedings of the Artificial Intelligence for Cyber Security (AICS) Workshop at AAAI 2022 [55.573187938617636]
  The workshop will focus on the application of AI to problems in cyber security. Cyber systems generate large volumes of data, utilizing this effectively is beyond human capabilities.
  arXiv  Detail & Related papers  (2022-02-28T18:27:41Z)
• Adversarial vs behavioural-based defensive AI with joint, continual and active learning: automated evaluation of robustness to deception, poisoning and concept drift [62.997667081978825]
  Recent advancements in Artificial Intelligence (AI) have brought new capabilities to behavioural analysis (UEBA) for cyber-security. In this paper, we present a solution to effectively mitigate this attack by improving the detection process and efficiently leveraging human expertise.
  arXiv  Detail & Related papers  (2020-01-13T13:54:36Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.