Related papers: A 0.16pJ/bit Recurrent Neural Network Based PUF fo…
We introduce a mathematical framework for simulating Hybrid Boolean Network (HBN) Physically Unclonable Functions (PUFs, HBN-PUFs). We verify that the model is able to reproduce the experimentally observed PUF statistics for uniqueness…
We propose a secure and lightweight key based challenge obfuscation for strong PUFs. Our architecture is designed to be resilient against learning attacks. Our obfuscation mechanism uses non-linear feedback shift registers (NLFSRs).…
Physical unclonable functions (PUFs) are small circuits that are widely used as hardware security primitives for authentication. These circuits can generate unique signatures because of the inherent randomness in manufacturing and process…
This paper proposes a 3-input arbiter-based novel physically unclonable function (PUF) design. Firstly, a 3-input priority arbiter is designed using a simple arbiter, two multiplexers (2:1), and an XOR logic gate. The priority arbiter has…
This article presents a reconfigurable physically unclonable function (PUF) design fabricated using 65-nm CMOS technology. A subthreshold-inverter-based static PUF cell achieves 0.3% native bit error rate (BER) at 0.062-fJ per bit core…
Security is essential for the Internet of Things (IoT). Cryptographic operations for authentication and encryption commonly rely on random input of high entropy and secure, tamper-resistant identities, which are difficult to obtain on…
The physical unclonable functions (PUF) are used to provide software as well as hardware security for the cyber-physical systems. They have been used for performing significant cryptography tasks such as generating keys, device…
We introduce a Physically Unclonable Function (PUF) based on an ultra-fast chaotic network known as a Hybrid Boolean Network (HBN) implemented on a field programmable gate array. The network, consisting of $N$ coupled asynchronous logic…
Simple authentication protocols based on conventional physical unclonable function (PUF) are vulnerable to modeling attacks and other security threats. This paper proposes an arbiter PUF based on a linear feedback shift register…
Physically Unclonable Functions (PUFs) are used for securing electronic devices across the implementation spectrum ranging from Field Programmable Gate Array (FPGA) to system on chips (SoCs). However, existing PUF implementations often…
Machine-learning architectures, such as Convolutional Neural Networks (CNNs) are vulnerable to adversarial attacks: inputs crafted carefully to force the system output to a wrong label. Since machine-learning is being deployed in…
Physical Unclonable Functions (PUFs) have been shown to be a highly promising solution for enabling high security systems tailored for low-power devices. Commonly, PUFs are utilised to generate cryptographic keys on-the-fly, replacing the…
We present a new algorithm to train a robust neural network against adversarial attacks. Our algorithm is motivated by the following two ideas. First, although recent work has demonstrated that fusing randomness can improve the robustness…
It is shown that a class of optical physical unclonable functions (PUFs) can be learned to arbitrary precision with arbitrarily high probability, even in the presence of noise, given access to polynomially many challenge-response pairs and…
Physical Unclonable Functions (PUFs) have emerged as a promising solution to identify and authenticate Integrated Circuits (ICs). In this paper, we propose a novel NAND-based Set-Reset (SR) Flip-flop (FF) PUF design for security enclosures…
Evolutionary algorithms have been successfully applied to attacking Physically Unclonable Functions (PUFs). CMA-ES is recognized as the most powerful option for a type of attack called the reliability attack. While there is no reason to…
Machine learning applications are computationally demanding and power intensive. Hardware acceleration of these software tools is a natural step being explored using various technologies. A recurrent processing unit (RPU) is fast and…
The vast areas of applications for IoTs in future smart cities, smart transportation systems, and so on represent a thriving surface for several security attacks with economic, environmental and societal impacts. This survey paper presents…
More and more companies' Intellectual Property (IP) is being integrated into Neural Network (NN) models. This IP has considerable value for companies and, therefore, requires adequate protection. For example, an attacker might replicate a…
The proliferation of the Internet of Things (IoTs) and pervasive use of many different types of mobile computing devices make wireless communication spectrum a precious resource. In order to accommodate the still fast increasing number of…