The Impact of AI on the Cyber Offense-Defense Balance and the Character of Cyber Conflict
Unlike other domains of conflict, and unlike other fields with high anticipated risk from AI, the cyber domain is intrinsically digital with a tight feedback loop between AI training and cyber application. Cyber may have some of the largest and earliest impacts from AI, so it is important to understand how the cyber domain may change as AI continues to advance. Our approach reviewed the literature, collecting nine arguments that have been proposed for offensive advantage in cyber conflict and nine proposed arguments for defensive advantage. We include an additional forty-eight arguments that have been proposed to give cyber conflict and competition its character as collected separately by Healey, Jervis, and Nandrajog. We then consider how each of those arguments and propositions might change with varying degrees of AI advancement. We find that the cyber domain is too multifaceted for a single answer to whether AI will enhance offense or defense broadly. AI will improve some aspects, hinder others, and leave some aspects unchanged. We collect and present forty-four ways that we expect AI to impact the cyber offense-defense balance and the character of cyber conflict and competition.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
PACEbench: A Framework for Evaluating Practical AI Cyber-Exploitation Capabilities
The increasing autonomy of Large Language Models (LLMs) necessitates a rigorous evaluation of their potential to aid in cyber offense. Existing benchmarks often lack real-world complexity and are thus unable to accuratel…
Uplifted Attackers, Human Defenders: The Cyber Offense-Defense Balance for Trailing-Edge Organizations
Advances in AI are widely understood to have implications for cybersecurity. Articles have emphasized the effect of AI on the cyber offense-defense balance, and commentators can be found arguing either that cyber will pr…
LLM agents security duality: a comprehensive survey of self-security and empowered cybersecurity
Large language model (LLM) agents are rapidly being integrated into real-world systems. Their autonomy and tool-use capabilities generate substantial value while simultaneously expanding the security attack surface. This…
The Best Defense is a Good Offense: Countering LLM-Powered Cyberattacks
As large language models (LLMs) continue to evolve, their potential use in automating cyberattacks becomes increasingly likely. With capabilities such as reconnaissance, exploitation, and command execution, LLMs could so…
BountyBench: Dollar Impact of AI Agent Attackers and Defenders on Real-World Cybersecurity Systems
AI agents have the potential to significantly alter the cybersecurity landscape. To help us understand this change, we introduce the first framework to capture offensive and defensive cyber-capabilities in evolving real-…
AI Agent