The Evolving Thread Landscape PF Ai-Powered Cyberattacks:a Multi-Faceted Approach to Defense and Mitigate

EasyChair Preprint no. 14163

Abstract

The advent of artificial intelligence (AI) has revolutionized numerous industries, enhancing efficiency and innovation. However, this technological advancement also presents a double-edged sword, as cybercriminals increasingly leverage AI to orchestrate sophisticated cyberattacks (Goodfellow et al., 2018; Mühlbauer et al., 2022). This article explores the evolving threat landscape of AI-powered cyberattacks and proposes a multi-faceted approach to defense and mitigation. AI's capacity to analyze vast amounts of data, predict patterns, and learn autonomously makes it an invaluable tool for attackers (Cheng et al., 2021; Wang et al., 2022). These AI-driven threats range from automated phishing schemes and advanced malware to large-scale Distributed Denial of Service (DDoS) attacks, all characterized by their precision, adaptability, and ability to evade traditional cybersecurity measures (Cheng et al., 2020; Zhang et al., 2023). AI-powered cyberattacks pose significant risks across various sectors, including finance, healthcare, and government (Crosman, 2021; Zeng et al., 2022). The financial sector, for instance, faces AI-enhanced fraud detection evasion, while the healthcare industry is vulnerable to attacks on medical devices and patient data theft (Friedman, 2022; Borenstein et al., 2023).

Keyphrases: Artificial Intelligence (AI), Cyberattacks, sophisticated

@Booklet{EasyChair:14163,
  author = {Ralph Shad and Peter Broklyn and Axel Egon},
  title = {The Evolving Thread Landscape PF Ai-Powered Cyberattacks:a Multi-Faceted Approach to Defense and Mitigate},
  howpublished = {EasyChair Preprint no. 14163},

  year = {EasyChair, 2024}}