Affirmative Safety: An Approach to Risk Management for Advanced Ai

The paper suggests that companies developing high-risk AI systems should demonstrate their safety before deployment, arguing for proactive risk management. It proposes a risk management approach where developers must provide evidence that risks are below acceptable thresholds. The paper discusses technical and operational evidence for safety, comparing its approach to the NIST AI Risk Management Framework.

Evolving EU Security Policies for Critical Infrastructure and Services

The article explores the importance of critical infrastructure (CI) and essential services (ES) for population security and business continuity. It examines the challenges posed by the interdependence of CI and ES, which complicates threat identification and risk management. The study identifies new research directions on operational risk management, public security, and resilience in critical supply networks.

Interpretation of Effects in Verifying the Banking Customers

The research examines the impact of traditional verification methods on customer satisfaction and operational efficiency in commercial banks. It suggests adopting digital solutions such as biometric authentication and machine learning algorithms to streamline verification, prevent fraud, enhance security, and improve customer engagement. The study aims to provide recommendations for innovative methods aligning with digital transformation and customer expectations.

Will A Cybersecurity Safe Harbor Raise All Boats?

“Using cybersecurity certification as the basis for providing a complete defense to liability may not prevent every harm from occurring. However, if organizations invest in certification to avoid legal liability, this should collectively improve the resilience and quality of technology products in the United States and beyond.”

Human Factors in Security Risk Analysis of Software Systems: A Systematic Literature Review

Security risk analysis techniques involve identifying security threats in software systems and planning countermeasures. Automation and knowledge reuse aid analysts, but they must interpret and assess tool outcomes, which can be biased. A review of 22 studies highlights conflicting conclusions on human factors in security risk analysis and identifies gaps in literature.

From Insight to Compliance: Appropriate Technical and Organisational Security Measures Through the Lens of Cybersecurity Maturity Models

“... this article provides anchorage to scholarly audiences when scrutinizing the extent to which privacy and security measures qualify as ‘appropriate’ in the context of liability claims and actions for damages, thereby creating an opportunity to move from technical insight to legal compliance.”