COMPARATIVE ANALYSIS OF GLOBAL CYBERSECURITY LAWS FOR AI THREAT MITIGATION

Global cybersecurity laws are evolving to address AI- induced threats, but significant gaps remain in accountability, transparency, and international coordination. Comparative analysis highlights that while the EU provides a proactive regulatory model, the U.S., China, and Australia exhibit varying degrees of preparedness. Harmonized legal approaches, informed by best practices across jurisdictions, are crucial for mitigating the complex and adaptive risks posed by AI systems. The comparative analysis of global cybersecurity laws for AI threat mitigation demonstrates that while significant progress has been made across major jurisdictions, substantial gaps remain in regulatory readiness, harmonization, and enforcement. As AI systems increasingly influence critical infrastructures, financial ecosystems, defense mechanisms, and personal data environments, the need for robust and adaptive cybersecurity laws has become more urgent than ever (Brundage et al., 2018). The review highlights that the United States, European Union, China, and Australia have adopted distinct regulatory approaches shaped by their political, economic, and ethical priorities. However, these differences also create fragmentation, complicating cross- border investigations, data- sharing compliance, and transnational enforcement mechanisms (Floridi et al., 2018). W hile the European Union’ s proposed Artificial Intelligence Act offers the most comprehensive attempt at regulating high- risk AI systems through structured risk classification, transparency requirements, and accountability provisions, its implementation challenges and jurisdictional constraints limit its global impact (European Commission, 2021). Conversely, the United States follows a more decentralized, sector-specific model that promotes innovation but lacks explicit liability mechanisms for harms caused by autonomous or adaptive AI systems, creating uncertainties regarding accountability, especially in high- impact domains like healthcare and autonomous vehicles (Calo, 2017). China’ s cybersecurity law reflects strong state control, with robust oversight and strict security assessments for AI technologies, yet it falls short in fostering transparency, cross- border cooperation, and independent auditing elements critical for global AI threat mitigation (Li, 2020). A key finding is the pervasive challenge posed by the opacity of AI systems, commonly referred to as the “ black- box problem,” which obstructs explain ability and limits the ability of legal authorities to attribute wrongdoing or identify the root cause of AI- induced incidents (Burrell, 2016). Without transparent and auditable AI models, both regulators and practitioners face difficulties in establishing causation and enforcing accountability. Additionally, the problem of unclear liability persists across jurisdictions, particularly when AI systems operate autonomously or evolve beyond their original design parameters. Existing legal structures remain highly dependent on human- centric notions of responsibility, which are insufficient in addressing the adaptive behavior of advanced AI systems (Gasser & Almeida, 2017). Furthermore, the rapid evolution of AI- driven cyber threats, including adversarial attacks, deepfake manipulation, and data poisoning, demands continuous updates to legal frameworks, threat modeling practices, and international cooperation mechanisms. Overall, the findings suggest a strong need for interoperability and harmonization of cybersecurity laws to effectively mitigate AI- driven threats in a globally interconnected environment. Collaborative frameworks, international standards, cross- border information sharing, and unified accountability models must be prioritized. Policymakers should adopt multi- layered regulatory approaches integrating ethics, technical standards, legal oversight, and human- centered governance (Binns, 2018). Developing globally recognized AI security standards, mandating explain ability features in high- risk AI systems, and establishing joint cybersecurity task forces could significantly strengthen the global enforcement landscape. In conclusion, addressing AI- based cybersecurity threats requires not only jurisdiction- specific reforms but also a shared global commitment to creating resilient, transparent, and accountable governance structures that safeguard societies against the rapidly evolving risks of artificial intelligence.

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