26 papers
Integrity of peer-to-peer distributed LLM inference under malicious nodes
Mert Cihangiroglu, Antonino Nocera
Peer-to-peer distributed inference executes a Large Language Model (LLM) on pooled consumer hardware by spreading its layers across many nodes. Every request passes through nodes t…
CVE-TTP KG: Knowledge Graph Linking Software Vulnerabilities to Attack Behaviors
Swati Yadav, Dincy R. Arikkat, Basant Agarwal +3
In the evolving threat landscape, adversaries exploit software vulnerabilities to launch sophisticated attacks, challenging traditional defenses. Although databases like CVE and NV…
An AI-Based Solution for Secure Service Provisioning in IoT
Marco Arazzi, Mert Cihangiroglu, Serena Nicolazzo +2
As the Internet of Things (IoT) continues its rapid expansion, the attack surface grows accordingly, with emerging threats targeting smart objects and their interactions. In this e…
A Multi-task Mixture of Experts Framework for Malware Classification, Packing Detection, and Family Attribution
Jithin S., Roshin Sleeba C., Anvin Mariya P. B. +4
Malware classification remains a challenging problem due to its inherent heterogeneity, the presence of packed binaries, and the diverse distribution of malware families. Tradition…
GAS-Leak-LLM: Genetic Algorithm-Based Suffix Optimization for Black-Box LLM Jailbreaking
Aman Anifer, Vignesh Kumar Kembu, Vishnu M +4
Large Language Models (LLMs) constitute pivotal components within the AI-dominated information technology ecosystem. To mitigate risks associated with harmful or policy-violating o…
LightSplit: Practical Privacy-Preserving Split Learning via Orthogonal Projections
Mert Cihangiroglu, Alessandro Pegoraro, Phillip Rieger +2
Split learning (SL) enables collaborative training by partitioning a neural network across clients and a central server, but the cut-layer interface introduces a key challenge: hig…