Cyber Shadows: Neutralizing Security Threats with AI and Targeted Policy Measures
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Abstract (arXiv)
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.
Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 16 of its 29 references that are in the map. First posted on arXiv 3 Jan 2025.
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16 of 29 references.
References · 16
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- 2023Raising the Cost of Malicious AI-Powered Image Editingcited by 160
- 2023Large Language Models for Code: Security Hardening and Adversarial Testingcited by 149
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- 2022Is GitHub's Copilot as Bad as Humans at Introducing Vulnerabilities in Code?cited by 63
- 2022Data Poisoning Attacks Against Multimodal Encoderscited by 41
- 2023Accelerating science with human-aware artificial intelligencecited by 27
- 2023Digital Deception: Generative Artificial Intelligence in Social Engineering and Phishingcited by 26
- 2023Towards Trustworthy Explanation: On Causal Rationalizationcited by 19
4 more
- 2023Diagnosis, Feedback, Adaptation: A Human-in-the-Loop Framework for Test-Time Policy Adaptationcited by 16
- 2024SOPHON: Non-Fine-Tunable Learning to Restrain Task Transferability For Pre-trained Modelscited by 16
- 2022A Game-Theoretic Framework for Managing Risk in Multi-Agent Systemscited by 13
- 2023Securing the Digital World: Protecting smart infrastructures and digital industries with Artificial Intelligence (AI)-enabled malware and intrusion detectioncited by 6
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