151 citations · 373 across the 31 of their papers we have counts for
17 papers · 1 filter
Security Analysis for SCONE Logic Locking
Akashdeep Saha, Mohammed Nabeel, Johann Knechtel +2
SCONE [DAC'25] expands a logic locking interface with additional encoded inputs derived from the original primary inputs, and admits two realizations: a \textit{with-ES} variant, w…
CHEHAB RL: Learning to Optimize Fully Homomorphic Encryption Computations
Bilel Sefsaf, Abderraouf Dandani, Abdessamed Seddiki +4
Fully Homomorphic Encryption (FHE) enables computations directly on encrypted data, but its high computational cost remains a significant barrier. Writing efficient FHE code is a c…
@NTT: Algorithm-Targeted NTT hardware acceleration via Design-Time Constant Optimization
Mohammed Nabeel, Mahmoud Hafez, Michail Maniatakos
The Number Theoretic Transform (NTT) is a critical computational bottleneck in many lattice-based postquantum cryptographic (PQC) algorithms. By leveraging the Fast Fourier Transfo…
PAPER: Privacy-Preserving Convolutional Neural Networks using Low-Degree Polynomial Approximations and Structural Optimizations on Leveled FHE
Eduardo Chielle, Manaar Alam, Jinting Liu +2
Recent work using Fully Homomorphic Encryption (FHE) has made non-interactive privacy-preserving inference of deep Convolutional Neural Networks (CNNs) possible. However, the perfo…
ReVeil: Unconstrained Concealed Backdoor Attack on Deep Neural Networks using Machine Unlearning
Manaar Alam, Hithem Lamri, Michail Maniatakos
Backdoor attacks embed hidden functionalities in deep neural networks (DNN), triggering malicious behavior with specific inputs. Advanced defenses monitor anomalous DNN inferences…
RTL-Breaker: Assessing the Security of LLMs against Backdoor Attacks on HDL Code Generation
Lakshmi Likhitha Mankali, Jitendra Bhandari, Manaar Alam +4
Large language models (LLMs) have demonstrated remarkable potential with code generation/completion tasks for hardware design. In fact, LLM-based hardware description language (HDL…
LLMPot: Dynamically Configured LLM-based Honeypot for Industrial Protocol and Physical Process Emulation
Christoforos Vasilatos, Dunia J. Mahboobeh, Hithem Lamri +2
Industrial Control Systems (ICS) are extensively used in critical infrastructures ensuring efficient, reliable, and continuous operations. However, their increasing connectivity an…
TREBUCHET: Fully Homomorphic Encryption Accelerator for Deep Computation
David Bruce Cousins, Yuriy Polyakov, Ahmad Al Badawi +21
Secure computation is of critical importance to not only the DoD, but across financial institutions, healthcare, and anywhere personally identifiable information (PII) is accessed.…
ICSPatch: Automated Vulnerability Localization and Non-Intrusive Hotpatching in Industrial Control Systems using Data Dependence Graphs
Prashant Hari Narayan Rajput, Constantine Doumanidis, Michail Maniatakos
The paradigm shift of enabling extensive intercommunication between the Operational Technology (OT) and Information Technology (IT) devices allows vulnerabilities typical to the IT…
PerDoor: Persistent Non-Uniform Backdoors in Federated Learning using Adversarial Perturbations
Manaar Alam, Esha Sarkar, Michail Maniatakos
Federated Learning (FL) enables numerous participants to train deep learning models collaboratively without exposing their personal, potentially sensitive data, making it a promisi…
Scalable privacy-preserving cancer type prediction with homomorphic encryption
Esha Sarkar, Eduardo Chielle, Gamze Gursoy +3
Machine Learning (ML) alleviates the challenges of high-dimensional data analysis and improves decision making in critical applications like healthcare. Effective cancer type from…
FieldFuzz: In Situ Blackbox Fuzzing of Proprietary Industrial Automation Runtimes via the Network
Andrei Bytes, Prashant Hari Narayan Rajput, Constantine Doumanidis +3
Networked Programmable Logic Controllers (PLCs) are proprietary industrial devices utilized in critical infrastructure that execute control logic applications in complex proprietar…
Accelerating Fully Homomorphic Encryption by Bridging Modular and Bit-Level Arithmetic
Eduardo Chielle, Oleg Mazonka, Homer Gamil +1
The dramatic increase of data breaches in modern computing platforms has emphasized that access control is not sufficient to protect sensitive user data. Recent advances in cryptog…
CoFHEE: A Co-processor for Fully Homomorphic Encryption Execution (Extended Version)
Mohammed Nabeel, Homer Gamil, Deepraj Soni +6
The migration of computation to the cloud has raised concerns regarding the security and privacy of sensitive data, as their need to be decrypted before processing, renders them su…
Explainability Matters: Backdoor Attacks on Medical Imaging
Munachiso Nwadike, Takumi Miyawaki, Esha Sarkar +2
Deep neural networks have been shown to be vulnerable to backdoor attacks, which could be easily introduced to the training set prior to model training. Recent work has focused on…
Stop-and-Go: Exploring Backdoor Attacks on Deep Reinforcement Learning-based Traffic Congestion Control Systems
Yue Wang, Esha Sarkar, Wenqing Li +2
Recent work has shown that the introduction of autonomous vehicles (AVs) in traffic could help reduce traffic jams. Deep reinforcement learning methods demonstrate good performance…
ICSREF: A Framework for Automated Reverse Engineering of Industrial Control Systems Binaries
Anastasis Keliris, Michail Maniatakos
The security of Industrial Control Systems (ICS) has been attracting increased attention over the past years, following the discovery of real threats targeting industrial environme…