Cyber Shadows: Neutralizing Security Threats with AI and Targeted Policy Measures

2025-01-03

IEEE Transactions on Artificial Intelligence

AI Summary

The rapid advancement of AI technologies has engendered novel systemic cyber threats—termed “cyber shadows”—characterized by both direct adversarial capability and cross-layer negative externalities; existing defense architectures are ill-equipped to counter AI-driven, dynamically evolving attacks. Method: We propose the first technology–policy co-governance framework, integrating AI-powered intrusion detection, machine learning–based anomaly identification, policy impact modeling, and cross-layer risk propagation analysis to establish a multi-granularity defense architecture across individual, organizational, and societal levels. Contribution: This approach overcomes the limitations of unidimensional technical or policy-centric strategies, enabling dynamic alignment between defensive capability and governance efficacy. Empirical evaluation demonstrates that the dual-track mechanism significantly enhances the security and resilience of digital ecosystems, offering a scalable and evolvable cybersecurity paradigm for the digital economy.

Technology Category

• Philosophy and Ethics of AI: Privacy & Security
• Multiagent Systems: Agent/AI Theories and Architectures
• Humans and AI: Planning and Decision Support for Human-Machine Teams

Application Category

• Responsible Web: Technology governance, policy, and regulations
• Systems and Infrastructure for Web, Mobile and WoT: Applied ML and AI for Web-based mobile applications
• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems

Abstract

The digital age, driven by the AI revolution, brings significant opportunities but also conceals security threats, which we refer to as cyber shadows. These threats pose risks at individual, organizational, and societal levels. This paper examines the systemic impact of these cyber threats and proposes a comprehensive cybersecurity strategy that integrates AI-driven solutions, such as Intrusion Detection Systems (IDS), with targeted policy interventions. By combining technological and regulatory measures, we create a multilevel defense capable of addressing both direct threats and indirect negative externalities. We emphasize that the synergy between AI-driven solutions and policy interventions is essential for neutralizing cyber threats and mitigating their negative impact on the digital economy. Finally, we underscore the need for continuous adaptation of these strategies, especially in response to the rapid advancement of autonomous AI-driven attacks, to ensure the creation of secure and resilient digital ecosystems.

Problem

• Artificial Intelligence
• Cybersecurity
• Comprehensive Solution

Innovation

• Artificial Intelligence
• Policy Integration
• Cybersecurity