Hardware-assisted machine learning in resource-constrained IoT environments for security: review and future prospective

G Kornaros - IEEE Access, 2022 - ieeexplore.ieee.org
As the Internet of Things (IoT) technology advances, billions of multidisciplinary smart
devices act in concert, rarely requiring human intervention, posing significant challenges in …

Towards accurate run-time hardware-assisted stealthy malware detection: a lightweight, yet effective time series CNN-based approach

H Sayadi, Y Gao, H Mohammadi Makrani, J Lin… - Cryptography, 2021 - mdpi.com
According to recent security analysis reports, malicious software (aka malware) is rising at
an alarming rate in numbers, complexity, and harmful purposes to compromise the security …

Ensemble learning for effective run-time hardware-based malware detection: A comprehensive analysis and classification

H Sayadi, N Patel, A Sasan, S Rafatirad… - Proceedings of the 55th …, 2018 - dl.acm.org
Malware detection at the hardware level has emerged recently as a promising solution to
improve the security of computing systems. Hardware-based malware detectors take …

It's all in your head (set): Side-channel attacks on {AR/VR} systems

Y Zhang, C Slocum, J Chen… - 32nd USENIX Security …, 2023 - usenix.org
With the increasing adoption of Augmented Reality/Virtual Reality (AR/VR) systems, security
and privacy concerns attract attention from both academia and industry. This paper …

Semantics-based online malware detection: Towards efficient real-time protection against malware

S Das, Y Liu, W Zhang… - IEEE transactions on …, 2015 - ieeexplore.ieee.org
Recently, malware has increasingly become a critical threat to embedded systems, while the
conventional software solutions, such as antivirus and patches, have not been so successful …

A survey on adversarial attacks for malware analysis

K Aryal, M Gupta, M Abdelsalam, P Kunwar… - IEEE …, 2024 - ieeexplore.ieee.org
Machine learning-based malware analysis approaches are widely researched and
deployed in critical infrastructures for detecting and classifying evasive and growing …

An experimental analysis of security vulnerabilities in industrial IoT devices

X Jiang, M Lora, S Chattopadhyay - ACM Transactions on Internet …, 2020 - dl.acm.org
The revolutionary development of the Internet of Things has triggered a huge demand for
Internet of Things devices. They are extensively applied to various fields of social activities …

On the detection of kernel-level rootkits using hardware performance counters

B Singh, D Evtyushkin, J Elwell, R Riley… - … of the 2017 ACM on Asia …, 2017 - dl.acm.org
Recent work has investigated the use of hardware performance counters (HPCs) for the
detection of malware running on a system. These works gather traces of HPCs for a variety …

Hardware performance counters can detect malware: Myth or fact?

B Zhou, A Gupta, R Jahanshahi, M Egele… - Proceedings of the 2018 …, 2018 - dl.acm.org
The ever-increasing prevalence of malware has led to the explorations of various detection
mechanisms. Several recent works propose to use Hardware Performance Counters (HPCs) …

Malware detection using machine learning based analysis of virtual memory access patterns

Z Xu, S Ray, P Subramanyan… - Design, Automation & Test …, 2017 - ieeexplore.ieee.org
Malicious software, referred to as malware, continues to grow in sophistication. Past
proposals for malware detection have primarily focused on software-based detectors which …