Search Results for author: Ashish Kundu

Found 11 papers, 0 papers with code

RAW: A Robust and Agile Plug-and-Play Watermark Framework for AI-Generated Images with Provable Guarantees

no code implementations23 Jan 2024 Xun Xian, Ganghua Wang, Xuan Bi, Jayanth Srinivasa, Ashish Kundu, Mingyi Hong, Jie Ding

Subsequently, we employ a classifier that is jointly trained with the watermark to detect the presence of the watermark.

Prometheus: Infrastructure Security Posture Analysis with AI-generated Attack Graphs

no code implementations20 Dec 2023 Xin Jin, Charalampos Katsis, Fan Sang, Jiahao Sun, Elisa Bertino, Ramana Rao Kompella, Ashish Kundu

In this paper, we propose Prometheus, an advanced system designed to provide a detailed analysis of the security posture of computing infrastructures.

Demystifying Poisoning Backdoor Attacks from a Statistical Perspective

no code implementations16 Oct 2023 Ganghua Wang, Xun Xian, Jayanth Srinivasa, Ashish Kundu, Xuan Bi, Mingyi Hong, Jie Ding

The growing dependence on machine learning in real-world applications emphasizes the importance of understanding and ensuring its safety.

Backdoor Attack

Evaluating Chatbots to Promote Users' Trust -- Practices and Open Problems

no code implementations9 Sep 2023 Biplav Srivastava, Kausik Lakkaraju, Tarmo Koppel, Vignesh Narayanan, Ashish Kundu, Sachindra Joshi

Chatbots, the common moniker for collaborative assistants, are Artificial Intelligence (AI) software that enables people to naturally interact with them to get tasks done.

Chatbot Language Modelling +1

Edge Security: Challenges and Issues

no code implementations14 Jun 2022 Xin Jin, Charalampos Katsis, Fan Sang, Jiahao Sun, Ashish Kundu, Ramana Kompella

Edge computing is a paradigm that shifts data processing services to the network edge, where data are generated.

Edge-computing

BeautifAI -- A Personalised Occasion-oriented Makeup Recommendation System

no code implementations13 Sep 2021 Kshitij Gulati, Gaurav Verma, Mukesh Mohania, Ashish Kundu

The proposed work's novel contributions, including the incorporation of occasion context, region-wise makeup recommendation, real-time makeup previews and continuous makeup feedback, set our system apart from the current work in makeup recommendation.

Towards Deep Federated Defenses Against Malware in Cloud Ecosystems

no code implementations27 Dec 2019 Josh Payne, Ashish Kundu

In cloud computing environments with many virtual machines, containers, and other systems, an epidemic of malware can be highly threatening to business processes.

BIG-bench Machine Learning Cloud Computing +3

Uncheatable Machine Learning Inference

no code implementations8 Aug 2019 Mustafa Canim, Ashish Kundu, Josh Payne

Given a classification service supplier $S$, intermediary CaaS provider $P$ claiming to use $S$ as a classification backend, and customer $C$, our work addresses the following questions: (i) how can $P$'s claim to be using $S$ be verified by $C$?

BIG-bench Machine Learning Fraud Detection +1

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