A comprehensive index of artificial intelligence and machine-learning research with AI-generated summaries, citation metrics, and direct links to papers and code.
Juan S. Santillana
VectraYX-Vision-1B is a sub-2B Spanish/LATAM cybersecurity VLM with structured reasoning and tool use, but current vision SFT yields near-zero visual grounding.
Unknown
This paper introduces FLASH, a fast and robust framework for privacy-preserving machine learning, focusing on the 4PC setting to enhance security and efficiency in MLaaS.
Unknown
A-MemGuard is the first proactive defense framework for LLM agent memory, addressing security challenges in agent-based systems.
Unknown
Agentrim introduces a tool risk mitigation framework for agentic AI systems, combining LLM-based reasoning with reinforcement learning to dynamically restrict tool permissions and reduce security risks.
Ana Reyna, Cristian Martín, Jaime Chen, et al.
This paper surveys the integration of blockchain with IoT, analyzing challenges and opportunities for enhancing security and data reliability in distributed IoT environments.
Unknown
This paper demonstrates that LLM agents can autonomously hack websites, revealing their offensive cybersecurity capabilities.
Unknown
This paper explores the transformative role of autonomous AI agents in optimizing AI infrastructure, emphasizing data security and operational efficiency.
Unknown
This paper analyzes the security of large language model-based AI agents by studying their workflows and identifying vulnerabilities.
William Stallings
A comprehensive textbook survey of cryptography and network security principles and practice, covering both foundational concepts and modern applications.
Alex Kuo
This paper evaluates the opportunities and challenges of cloud computing in healthcare across management, technology, security, and legal aspects.
Tianyu Gu, Kang Liu, Brendan Dolan-Gavitt, et al.
This paper demonstrates that outsourced training of deep neural networks introduces security risks where adversaries can create backdoored networks that perform well on normal inputs but fail on attacker-chosen inputs.
Maanak Gupta, Charankumar Akiri, Kshitiz Aryal, et al.
This paper explores the dual-use of generative AI in cybersecurity, demonstrating attack techniques like jailbreaks and prompt injection, while also proposing defensive applications.