4 papers · 1 filter
Breaking the Assumptions: Auditing Input-Side Jailbreak Defenses Against Semantic Attacks
Aaditya Pratap, Harsh Kasyap, Somanath Tripathy
Locally deployed Large Language Models (LLMs) via inference engines such as Ollama run without the moderation and abuse detection present in API-served models. Therefore, the safet…
PRoVeFL: Private Robust and Verifiable Aggregation in Federated Learning
Harsh Kasyap, Anil Kumar Pradhan, Ugur Ilker Atmaca +2
Federated Learning (FL) enables multiple clients to collaboratively train machine learning models while retaining data locality, thereby enhancing user privacy. However, traditiona…
Analysis of LLMs Against Prompt Injection and Jailbreak Attacks
Piyush Jaiswal, Aaditya Pratap, Shreyansh Saraswati +2
Large Language Models (LLMs) are widely deployed in real-world systems. Given their broader applicability, prompt engineering has become an efficient tool for resource-scarce organ…
Privacy-preserving Fuzzy Name Matching for Sharing Financial Intelligence
Harsh Kasyap, Ugur Ilker Atmaca, Carsten Maple +2
Financial institutions rely on data for many operations, including a need to drive efficiency, enhance services and prevent financial crime. Data sharing across an organisation or…