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 …

A comprehensive survey on hardware-assisted malware analysis and primitive techniques

EP Kumar, S Priyanka - Computer Networks, 2023 - Elsevier
Malware poses an extremely dangerous threat to the digital world, significantly impacting
various domains such as smart cities, intelligent transportation, wireless sensor networks …

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 …

AI-HydRa: Advanced hybrid approach using random forest and deep learning for malware classification

S Yoo, S Kim, S Kim, BB Kang - Information Sciences, 2021 - Elsevier
The extremely diffused architecture of the Internet enables the propagation of malware and
presents a significant challenge for the development of defenses against such malware …

Improving malicious email detection through novel designated deep-learning architectures utilizing entire email

T Muralidharan, N Nissim - Neural Networks, 2023 - Elsevier
In today's email dependent world, cyber criminals often target organizations using a variety
of social engineering techniques and specially crafted malicious emails. When successful …

A multi-perspective malware detection approach through behavioral fusion of api call sequence

E Amer, I Zelinka, S El-Sappagh - Computers & Security, 2021 - Elsevier
The widespread development of the malware industry is considered the main threat to our e-
society. Therefore, malware analysis should also be enriched with smart heuristic tools that …

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 …

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) …

Attack-Aware IoT network traffic routing leveraging ensemble learning

Q Abu Al-Haija, A Al-Badawi - Sensors, 2021 - mdpi.com
Network Intrusion Detection Systems (NIDSs) are indispensable defensive tools against
various cyberattacks. Lightweight, multipurpose, and anomaly-based detection NIDSs …

A malware classification method based on memory dump grayscale image

Y Dai, H Li, Y Qian, X Lu - Digital Investigation, 2018 - Elsevier
Effective analysis of malware is of great significance in guaranteeing the reliability of the
system operation. Malware can easily escape from existing dynamic analysis methods …