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 …

[PDF][PDF] On the classification of Microsoft-Windows ransomware using hardware profile

S Aurangzeb, RNB Rais, M Aleem, MA Islam… - PeerJ Computer …, 2021 - peerj.com
Due to the expeditious inclination of online services usage, the incidents of ransomware
proliferation being reported are on the rise. Ransomware is a more hazardous threat than …

A survey of using machine learning in IoT security and the challenges faced by researchers

KM Harahsheh, CH Chen - Informatica, 2023 - digitalcommons.odu.edu
Abstract The Internet of Things (IoT) has become more popular in the last 15 years as it has
significantly improved and gained control in multiple fields. We are nowadays surrounded by …

Early detection of ransomware activity based on hardware performance counters

MA Putrevu, VSC Putrevu, SK Shukla - Proceedings of the 2023 …, 2023 - dl.acm.org
Modern-day ransomware variants are quick in their operations and start to encrypt the files
within a few seconds after the initial payload execution. This poses an exigency towards …

HiPeR-early detection of a ransomware attack using hardware performance counters

PM Anand, PVS Charan, SK Shukla - Digital Threats: Research and …, 2023 - dl.acm.org
Ransomware has been one of the most prevalent forms of malware over the previous
decade, and it continues to be one of the most significant threats today. Recently …

Explainable machine learning for intrusion detection via hardware performance counters

AP Kuruvila, X Meng, S Kundu… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
The exponential proliferation of Malware over the past decade has threatened system
security across a plethora of Internet of Things (IoT) devices. Furthermore, the improvements …

Resource-and workload-aware model parallelism-inspired novel malware detection for IoT devices

S Kasarapu, S Shukla… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
The wide adoption of Internet of Things (IoT) devices has led to better connectivity along with
seamless communication and smart computation capabilities across the network. Despite …

Guarding against the unknown: Deep transfer learning for hardware image-based malware detection

Z He, H Homayoun, H Sayadi - Journal of Hardware and Systems Security, 2024 - Springer
Malware is increasingly becoming a significant threat to computing systems, and detecting
zero-day (unknown) malware is crucial to ensure the security of modern systems. These …

Enhancing IoT malware detection through adaptive model parallelism and resource optimization

S Kasarapu, S Shukla, SMP Dinakarrao - arxiv preprint arxiv:2404.08808, 2024 - arxiv.org
The widespread integration of IoT devices has greatly improved connectivity and
computational capabilities, facilitating seamless communication across networks. Despite …

Towards Secure IoT‐Based Payments by Extension of Payment Card Industry Data Security Standard (PCI DSS)

MNM Bhutta, S Bhattia, MA Alojail… - Wireless …, 2022 - Wiley Online Library
IoT emergence has given rise to a new digital experience of payment transactions where
physical objects like refrigerators, cars, and wearables will make payments. These physical …