104 citations · 174 across the 14 of their papers we have counts for
14 papers
Quantization-aware Neural Architectural Search for Intrusion Detection
Rabin Yu Acharya, Laurens Le Jeune, Nele Mentens +2
Deploying machine learning-based intrusion detection systems (IDSs) on hardware devices is challenging due to their limited computational resources, power consumption, and network…
Garbled EDA: Privacy Preserving Electronic Design Automation
Mohammad Hashemi, Steffi Roy, Fatemeh Ganji +1
The complexity of modern integrated circuits (ICs) necessitates collaboration between multiple distrusting parties, including thirdparty intellectual property (3PIP) vendors, desig…
HWGN2: Side-channel Protected Neural Networks through Secure and Private Function Evaluation
Mohammad Hashemi, Steffi Roy, Domenic Forte +1
Recent work has highlighted the risks of intellectual property (IP) piracy of deep learning (DL) models from the side-channel leakage of DL hardware accelerators. In response, to p…
A Survey and Perspective on Artificial Intelligence for Security-Aware Electronic Design Automation
David Selasi Koblah, Rabin Yu Acharya, Daniel Capecci +5
Artificial intelligence (AI) and machine learning (ML) techniques have been increasingly used in several fields to improve performance and the level of automation. In recent years,…
Circuit Masking: From Theory to Standardization, A Comprehensive Survey for Hardware Security Researchers and Practitioners
Ana Covic, Fatemeh Ganji, Domenic Forte
Side-channel attacks extracting sensitive data from implementations have been considered a major threat to the security of cryptographic schemes. This has elevated the need for imp…
InfoNEAT: Information Theory-based NeuroEvolution of Augmenting Topologies for Side-channel Analysis
Rabin Yu Acharya, Fatemeh Ganji, Domenic Forte
Profiled side-channel analysis (SCA) leverages leakage from cryptographic implementations to extract the secret key. When combined with advanced methods in neural networks (NNs), p…
Real-World Snapshots vs. Theory: Questioning the t-Probing Security Model
Thilo Krachenfels, Fatemeh Ganji, Amir Moradi +2
Due to its sound theoretical basis and practical efficiency, masking has become the most prominent countermeasure to protect cryptographic implementations against physical side-cha…
Physically Unclonable Functions and AI: Two Decades of Marriage
Fatemeh Ganji, Shahin Tajik
The current chapter aims at establishing a relationship between artificial intelligence (AI) and hardware security. Such a connection between AI and software security has been conf…
Artificial Neural Networks and Fault Injection Attacks
Shahin Tajik, Fatemeh Ganji
This chapter is on the security assessment of artificial intelligence (AI) and neural network (NN) accelerators in the face of fault injection attacks. More specifically, it discus…
Physical Security in the Post-quantum Era: A Survey on Side-channel Analysis, Random Number Generators, and Physically Unclonable Functions
Sreeja Chowdhury, Ana Covic, Rabin Yu Acharya +3
Over the past decades, quantum technology has seen consistent progress, with notable recent developments in the field of quantum computers. Traditionally, this trend has been prima…
Attack of the Genes: Finding Keys and Parameters of Locked Analog ICs Using Genetic Algorithm
Rabin Yu Acharya, Sreeja Chowdhury, Fatemeh Ganji +1
Hardware intellectual property (IP) theft is a major issue in today's globalized supply chain. To address it, numerous logic locking and obfuscation techniques have been proposed.…
Towards an Insightful Computer Security Seminar
Kashyap Thimmaraju, Julian Fietkau, Fatemeh Ganji
In this paper we describe our experience in designing and evaluating our graduate level computer security seminar course. In particular, our seminar is designed with two goals in m…
Hardware Trust and Assurance through Reverse Engineering: A Survey and Outlook from Image Analysis and Machine Learning Perspectives
Ulbert J. Botero, Ronald Wilson, Hangwei Lu +7
In the context of hardware trust and assurance, reverse engineering has been often considered as an illegal action. Generally speaking, reverse engineering aims to retrieve informa…
RNNIDS: Enhancing Network Intrusion Detection Systems through Deep Learning
Soroush M. Sohi, Jean-Pierre Seifert, Fatemeh Ganji
Security of information passing through the Internet is threatened by today's most advanced malware ranging from orchestrated botnets to simpler polymorphic worms. These threats, a…