no code implementations • 19 Feb 2024 • Shubhi Shukla, Manaar Alam, Pabitra Mitra, Debdeep Mukhopadhyay
Machine learning, with its myriad applications, has become an integral component of numerous technological systems.
no code implementations • 26 May 2023 • Christoforos Vasilatos, Manaar Alam, Talal Rahwan, Yasir Zaki, Michail Maniatakos
As the use of Large Language Models (LLMs) in text generation tasks proliferates, concerns arise over their potential to compromise academic integrity.
no code implementations • 20 Apr 2023 • Manaar Alam, Hithem Lamri, Michail Maniatakos
Federated Learning (FL) enables collaborative deep learning training across multiple participants without exposing sensitive personal data.
no code implementations • 18 Aug 2022 • Manaar Alam, Shubhajit Datta, Debdeep Mukhopadhyay, Arijit Mondal, Partha Pratim Chakrabarti
The security of deep learning (DL) systems is an extremely important field of study as they are being deployed in several applications due to their ever-improving performance to solve challenging tasks.
no code implementations • 1 Aug 2022 • Shubhi Shukla, Manaar Alam, Sarani Bhattacharya, Debdeep Mukhopadhyay, Pabitra Mitra
In this paper, as a separate case study, we demonstrate that a DL model secured with differential privacy (a popular countermeasure against MIA) is still vulnerable to MIA against an adversary exploiting Class Leakage.
no code implementations • 9 Dec 2021 • Manaar Alam, Shubhajit Datta, Debdeep Mukhopadhyay, Arijit Mondal, Partha Pratim Chakrabarti
Ensemble methods against adversarial attacks demonstrate that an adversarial example is less likely to mislead multiple classifiers in an ensemble having diverse decision boundaries.
no code implementations • 13 Aug 2020 • Manaar Alam, Sayandeep Saha, Debdeep Mukhopadhyay, Sandip Kundu
Trained Deep Neural Network (DNN) models are considered valuable Intellectual Properties (IP) in several business models.
no code implementations • 13 Nov 2018 • Manaar Alam, Debdeep Mukhopadhyay
Deep Learning algorithms have recently become the de-facto paradigm for various prediction problems, which include many privacy-preserving applications like online medical image analysis.
no code implementations • 28 Sep 2018 • Anirban Chakraborty, Manaar Alam, Vishal Dey, Anupam Chattopadhyay, Debdeep Mukhopadhyay
Deep learning has emerged as a strong and efficient framework that can be applied to a broad spectrum of complex learning problems which were difficult to solve using the traditional machine learning techniques in the past.