On the use of artificial intelligence to deal with privacy in IoT systems: A systematic literature review

G Giordano, F Palomba, F Ferrucci - Journal of Systems and Software, 2022 - Elsevier
Abstract The Internet of Things (IoT) refers to a network of Internet-enabled devices that can
make different operations, like sensing, communicating, and reacting to changes arising in …

Cyber security and beyond: Detecting malware and concept drift in AI-based sensor data streams using statistical techniques

M Amin, F Al-Obeidat, A Tubaishat, B Shah… - Computers and …, 2023 - Elsevier
Abstract In the Industrial Internet of Things (IIoT), mobile devices can be used to remotely
monitor and control industrial processes, equipment, and machinery. They can also be used …

A novel hybrid convolutional neural network-and gated recurrent unit-based paradigm for IoT network traffic attack detection in smart cities

BB Gupta, KT Chui, A Gaurav, V Arya, P Chaurasia - Sensors, 2023 - mdpi.com
Internet of Things (IoT) devices within smart cities, require innovative detection methods.
This paper addresses this critical challenge by introducing a deep learning-based approach …

SiPGuard: run-time System-in-Package security monitoring via power noise variation

T Zhang, ML Rahman, HM Kamali… - … Transactions on Very …, 2023 - ieeexplore.ieee.org
As Moore's law comes to a crawl, advanced package and integration techniques become
increasingly crucial by allowing for the combination of fabricated silicon dies, so-called …

Obfuscation revealed: Leveraging electromagnetic signals for obfuscated malware classification

DP Pham, D Marion, M Mastio, A Heuser - Proceedings of the 37th …, 2021 - dl.acm.org
The Internet of Things (IoT) is constituted of devices that are exponentially growing in
number and in complexity. They use numerous customized firmware and hardware, without …

HADES-IoT: A practical and effective host-based anomaly detection system for IoT devices (extended version)

D Breitenbacher, I Homoliak, YL Aung… - IEEE Internet of …, 2021 - ieeexplore.ieee.org
Internet of Things (IoT) devices have become ubiquitous, with applications in many domains,
including industry, transportation, and healthcare; these devices also have many household …

Machine learning in wavelet domain for electromagnetic emission based malware analysis

N Chawla, H Kumar… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
This paper presents a signal processing and machine learning (ML) based methodology to
leverage Electromagnetic (EM) emissions from an embedded device to remotely detect a …

Attacks on IoT: side-channel power acquisition framework for intrusion detection

D Lightbody, DM Ngo, A Temko, CC Murphy… - Future Internet, 2023 - mdpi.com
This study proposes the wider use of non-intrusive side-channel power data in cybersecurity
for intrusion detection. An in-depth analysis of side-channel IoT power behaviour is …

[HTML][HTML] Energy-based approach for attack detection in IoT devices: A survey

V Merlino, D Allegra - Internet of Things, 2024 - Elsevier
The proliferation of Internet of Things (IoT) devices has revolutionized multiple sectors,
promising significant societal benefits. With an estimated 29 billion IoT devices expected to …

Disassembling software instruction types through impedance side-channel analysis

MS Awal, MT Rahman - 2023 IEEE International Symposium on …, 2023 - ieeexplore.ieee.org
Recent attacks on embedded devices emphasize the pressing need for a solution to protect
against malware and maintain software privacy. Although there are several anomaly …