Related papers: A novel reliability attack of Physical Unclonable …

As a well-known physical unclonable function that can provide huge number of challenge response pairs (CRP) with a compact design and fully compatibility with current electronic fabrication process, the arbiter PUF (APUF) has attracted…

Recent advances in Machine Learning(ML) have led to its broad adoption in a series of power system applications, ranging from meter data analytics, renewable/load/price forecasting to grid security assessment. Although these data-driven…

Machine learning (ML) has recently created many new success stories. Hence, there is a strong motivation to use ML technology in software-intensive systems, including safety-critical systems. This raises the issue of safety verification of…

Large language model (LLM) unlearning aims to remove specific data influences from pre-trained model without costly retraining, addressing privacy, copyright, and safety concerns. However, recent studies reveal a critical vulnerability:…

Programming errors, defective hardware components (such as hard disk spindle defects), and environmental hazards can lead to invalid memory operations. In addition, less predictable forms of environmental stress, such as radiation, thermal…

Programmable Logic Controllers (PLCs) play a critical role in the industrial control systems. Vulnerabilities in PLC programs might lead to attacks causing devastating consequences to the critical infrastructure, as shown in Stuxnet and…

Generative Artificial Intelligence models, such as Large Language Models (LLMs) and Large Vision Models (VLMs), exhibit state-of-the-art performance but remain vulnerable to hardware-based threats, specifically bit-flip attacks (BFAs).…

Even though recent years have seen many attacks exposing severe vulnerabilities in Federated Learning (FL), a holistic understanding of what enables these attacks and how they can be mitigated effectively is still lacking. In this work, we…

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…

With the boom of Large Language Models (LLMs), the research of solving Math Word Problem (MWP) has recently made great progress. However, there are few studies to examine the security of LLMs in math solving ability. Instead of attacking…

This paper presents a framework for securing blockchain-based IoT systems by integrating Physical Unclonable Functions (PUFs) and Zero-Knowledge Proofs (ZKPs) within a Hyperledger Fabric environment. The proposed framework leverages PUFs…

Recently, major progress has been made towards the realisation of quantum internet to enable a broad range of classically intractable applications. These applications such as delegated quantum computation require running a secure…

Machine learning (ML) sees an increasing prevalence of being used in the internet-of-things (IoT)-based smart grid. However, the trustworthiness of ML is a severe issue that must be addressed to accommodate the trend of ML-based smart grid…

Upcoming certification actions related to the security of machine learning (ML) based systems raise major evaluation challenges that are amplified by the large-scale deployment of models in many hardware platforms. Until recently, most of…

Despite its technological benefits, Internet of Things (IoT) has cyber weaknesses due to the vulnerabilities in the wireless medium. Machine learning (ML)-based methods are widely used against cyber threats in IoT networks with promising…

The Internet of Things (IoT) is considered as the key enabling technology for smart services. Security and privacy are particularly open challenges for IoT applications due to the widespread use of commodity devices. This work introduces…

As large language models are increasingly deployed in sensitive environments, fingerprinting attacks pose significant privacy and security risks. We present a study of LLM fingerprinting from both offensive and defensive perspectives. Our…

Physical unclonable functions (PUFs) are widely considered in secret key generation for resource constrained devices. However, PUFs require additional hardware overhead. In this paper, we focus on developing a PUF-efficient, robust, and…

Large language models (LLMs) have demonstrated impressive performance and have come to dominate the field of natural language processing (NLP) across various tasks. However, due to their strong instruction-following capabilities and…

Interconnected embedded devices are increasingly used invarious scenarios, including industrial control, building automation, or emergency communication. As these systems commonly process sensitive information or perform safety critical…