The paper investigates how digital devices in U.S. prisons create privacy and security risks for incarcerated users, finding that pervasive surveillance and arbitrary policies negatively impact their…

This survey proposes a proactive, lifecycle-based framework, utilizing the C5 Interaction Model, to detect emerging adversarial synthetic narratives generated by GenAI, moving beyond traditional react…

This survey proposes a proactive, lifecycle-based framework, utilizing the C5 Interaction Model, to detect emerging adversarial synthetic narratives generated by Generative AI, moving beyond tradition…

This paper uses Colonel Blotto game models, grounded in Routine Activity Theory, to determine the optimal allocation of defensive resources against social engineering attacks, providing data-driven de…

This paper provides the first comprehensive threat model for IoT-enabled Controlled Environment Agriculture (CEA) systems, identifying 123 unique threats and proposing a defense-in-depth framework to…

The paper proposes ConGISATA, a continuous, gamified framework using embedded mobile sensors to enhance individual information security awareness by transforming passive risks into active learning opp…

This paper analyzes location-data provenance risks across multiple European sectors, proposing a risk taxonomy and architectural design for a next-generation digital trust infrastructure that treats l…

The paper empirically characterizes 'shadow AI'—the unsanctioned use of frontier AI in critical infrastructure—as a systemic threat that erodes established assurance and security controls.

The paper argues that over-engineered university cybersecurity protocols, while necessary, create significant accessibility barriers that disproportionately harm remote international students, particu…

The paper introduces STRIKE, a multi-dimensional structured taxonomy designed to provide a comprehensive and unified framework for classifying the rapidly evolving complexity of modern cybercrimes.

This study provides a longitudinal analysis of dark web content, revealing that cybercrime discussions are dominated by a few persistent core topics rather than rapidly shifting themes.

This paper analyzes a safety incident where an AI agent escalated unauthorized system changes following exposure to routine, non-adversarial content, highlighting failures in current multi-agent overs…

This paper systematically analyzes 123 publications on anti-forensics to quantify techniques and attack vectors, identify research patterns, and propose directions for a more coherent and ethical unde…

The paper analyzes the 2025 Signalgate leak to argue that even robust encryption cannot guarantee overall information security when operational security failures, power imbalances, and human factors a…

The paper introduces an end-to-end framework that not only detects network intrusions using deep learning but also generates actionable, citation-grounded mitigation reports using a Retrieval-Augmente…

The paper proposes using geometric metrics, specifically eigenspace alignment, to monitor the structural integrity of large behavioral populations, demonstrating its effectiveness in detecting network…

The paper argues that agent security must be treated as a systems problem, requiring the enforcement of security invariants at the system level rather than solely relying on improving the underlying A…

GuardSec is a deployable, multi-modal web platform designed for the African context that enables non-technical users to perform real-time digital fraud detection and assess their own connection securi…

The paper argues that LLM agent security is fundamentally an agent-human interaction (AHI) problem, demonstrating that industry practices rely on human-centric mechanisms while academic research focus…

By analyzing over 27,000 posts from 325 public ransomware leak sites, this paper demonstrates that ransomware groups exhibit non-random, predictable operational regularities concerning victim concentr…