CRAIJun 22, 2023

Impacts and Risk of Generative AI Technology on Cyber Defense

arXiv:2306.13033v127 citationsh-index: 27
Originality Synthesis-oriented
AI Analysis

It addresses cybersecurity challenges for defense professionals, but is incremental as it applies existing frameworks to a new technology.

The paper tackles the cybersecurity risks posed by generative AI, such as phishing and deepfakes, by analyzing threats through the Cyber Kill Chain framework and proposing adaptive defense strategies like detection and adversarial training.

Generative Artificial Intelligence (GenAI) has emerged as a powerful technology capable of autonomously producing highly realistic content in various domains, such as text, images, audio, and videos. With its potential for positive applications in creative arts, content generation, virtual assistants, and data synthesis, GenAI has garnered significant attention and adoption. However, the increasing adoption of GenAI raises concerns about its potential misuse for crafting convincing phishing emails, generating disinformation through deepfake videos, and spreading misinformation via authentic-looking social media posts, posing a new set of challenges and risks in the realm of cybersecurity. To combat the threats posed by GenAI, we propose leveraging the Cyber Kill Chain (CKC) to understand the lifecycle of cyberattacks, as a foundational model for cyber defense. This paper aims to provide a comprehensive analysis of the risk areas introduced by the offensive use of GenAI techniques in each phase of the CKC framework. We also analyze the strategies employed by threat actors and examine their utilization throughout different phases of the CKC, highlighting the implications for cyber defense. Additionally, we propose GenAI-enabled defense strategies that are both attack-aware and adaptive. These strategies encompass various techniques such as detection, deception, and adversarial training, among others, aiming to effectively mitigate the risks posed by GenAI-induced cyber threats.

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