This paper aggregates robocall reports from 65 countries and provides the first publicly available multimodal and international robocall dataset, analyzing calling patterns, identifying common campaig…

The paper introduces RoboKA, a KAN-based multimodal fusion framework, and a synthetic dataset (Robo-SAr) to significantly improve robocall surveillance by modeling complex adversarial interactions bet…

The paper analyzes the real threat of GenAI in cybercrime, arguing that while high-end automation (Stand-Alone Complex) is possible, current adoption is low and primarily affects skilled actors, sugge…

The paper introduces MyPhoneBench, a new framework that demonstrates that current phone-use agents often fail to respect user privacy, even when successfully completing simple tasks, primarily due to…

The paper introduces MATRA, a systematic threat modeling framework, to assess how known LLM threats translate into concrete, deployment-specific risks within autonomous agentic AI systems.

The paper investigates the effectiveness of hardware-backed security mechanisms when mobile devices are repurposed outside their original ecosystem, concluding that vendor-locked mechanisms significan…

This paper addresses the security vulnerabilities in drone swarm control algorithms by proposing two fuzzing tools, SwarmFuzzGraph and SwarmFuzzBinary, to discover Swarm Propagation Vulnerabilities (S…

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 paper provides a comparative framework analyzing the distinct security and privacy risks inherent in virtual and robotic assistive systems, culminating in design recommendations for trustworthy t…

This paper proposes the first web-focused threat model for agentic browsers, demonstrating that traditional web social engineering attacks can be amplified into dangerous, reproducible threats when ex…

This paper provides a systematic, layered review of security risks and defense strategies for autonomous agent frameworks, using OpenClaw as a case study to address the current lack of integrated rese…

This study analyzes a large dataset of mobile messaging scams from Reddit, finding that rapidly growing reply-based scams are poorly detected by current off-the-shelf tools, necessitating the developm…

The paper addresses the lack of user understanding regarding the actions and residual effects of advanced computer-use agents by proposing AgentTrace, a traceability framework for visualizing agent be…

The paper introduces RoboJailBench, the first standardized evaluation framework for assessing adversarial jailbreak attacks and defenses in embodied AI systems like robots.

This paper provides a systematic survey of ROS 2 middleware and identifies architectural limits through three dimensions: Space, Time, and State.

This paper demonstrates that using a communication algorithm (CommFormer) with heterogeneous agents significantly improves the speed and performance of multi-agent reinforcement learning for autonomou…

This paper provides a large-scale characterization of Telegram bots, revealing that while they serve useful functions like crowdsourcing, they are also extensively used for malicious activities such a…

The paper proposes a novel attack paradigm demonstrating how compromising a single robot in an LLM-controlled multi-robot system can rapidly propagate malicious intent to cause coordinated unsafe acti…

The paper proposes a novel, empirical methodology called 'backchaining' to derive and prioritize Loss of Control (LoC) mitigations by analyzing the errors an AI system makes on mission-specific nation…

The paper empirically compares the security and privacy implementation characteristics of major Android messaging apps (Meta Messenger, Signal, and Telegram) using static and dynamic analysis, finding…