JOURNAL ARTICLE

AI-Powered Cyberattacks: Impacts and Defense Strategies

Bashir, NimraZafar, Muhammad Zeeshan

Year: 2025 Journal:   Zenodo (CERN European Organization for Nuclear Research)   Publisher: European Organization for Nuclear Research

Abstract

The rapid advancement of artificial intelligence (AI) has empowered cybercriminals to launch sophisticated attacks that bypass traditional defenses. These AI-powered cyberattacks—ranging from automated phishing and adversarial AI evasion to deepfake fraud—pose unprecedented threats to global cybersecurity. This review examines the evolution and multifaceted impacts of AI-driven threats on both individuals and organizations, evaluates current defense strategies, and proposes a comprehensive, multi-layered defense framework. This framework integrates AI-based detection with human oversight and international collaboration while addressing operational challenges and ethical concerns. The findings underscore the urgent need for proactive and adaptive security measures to counter the emerging threats.

Keywords:
Adversarial system Evasion (ethics) Phishing Key (lock) Government (linguistics) Emerging technologies

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