Resilient machine learning for networked cyber physical systems: A survey for machine learning security to securing machine learning for CPS

FO Olowononi, DB Rawat, C Liu - … Communications Surveys & …, 2020 - ieeexplore.ieee.org
Cyber Physical Systems (CPS) are characterized by their ability to integrate the physical and
information or cyber worlds. Their deployment in critical infrastructure have demonstrated a …

Security and privacy of internet of medical things: A contemporary review in the age of surveillance, botnets, and adversarial ML

RU Rasool, HF Ahmad, W Rafique, A Qayyum… - Journal of Network and …, 2022 - Elsevier
Abstract Internet of Medical Things (IoMT) supports traditional healthcare systems by
providing enhanced scalability, efficiency, reliability, and accuracy of healthcare services. It …

Intrusion Detection in Industrial Internet of Things Network‐Based on Deep Learning Model with Rule‐Based Feature Selection

JB Awotunde, C Chakraborty… - … and mobile computing, 2021 - Wiley Online Library
The Industrial Internet of Things (IIoT) is a recent research area that links digital equipment
and services to physical systems. The IIoT has been used to generate large quantities of …

Cyber intrusion detection system based on a multiobjective binary bat algorithm for feature selection and enhanced bat algorithm for parameter optimization in neural …

WAHM Ghanem, SAA Ghaleb, A Jantan… - IEEE …, 2022 - ieeexplore.ieee.org
The staggering development of cyber threats has propelled experts, professionals and
specialists in the field of security into the development of more dependable protection …

Enhancing IIoT networks protection: A robust security model for attack detection in Internet Industrial Control Systems

IA Khan, M Keshk, D Pi, N Khan, Y Hussain, H Soliman - Ad Hoc Networks, 2022 - Elsevier
Abstract Industrial Internet of Things (IIoT) networks involves heterogeneous technological
and manufacturing services and devices. The communication and data exchange …

An enhanced multi-stage deep learning framework for detecting malicious activities from autonomous vehicles

IA Khan, N Moustafa, D Pi, W Haider… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Intelligent Transportation Systems (ITS), particularly Autonomous Vehicles (AVs), are
susceptible to safety and security concerns that impend people's lives. Nothing like manually …

Secure deep learning in defense in deep-learning-as-a-service computing systems in digital twins

Z Lv, D Chen, B Cao, H Song… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
While Digital Twins (DTs) bring convenience to city managers, they also generate new
challenges to city network security. Currently, cyberspace security becomes increasingly …

A review of anomaly detection strategies to detect threats to cyber-physical systems

N Jeffrey, Q Tan, JR Villar - Electronics, 2023 - mdpi.com
Cyber-Physical Systems (CPS) are integrated systems that combine software and physical
components. CPS has experienced rapid growth over the past decade in fields as disparate …

[HTML][HTML] Multi-aspect rule-based AI: Methods, taxonomy, challenges and directions toward automation, intelligence and transparent cybersecurity modeling for critical …

IH Sarker, H Janicke, MA Ferrag, A Abuadbba - Internet of Things, 2024 - Elsevier
Critical infrastructure (CI) typically refers to the essential physical and virtual systems, assets,
and services that are vital for the functioning and well-being of a society, economy, or nation …

Unsupervised gan-based intrusion detection system using temporal convolutional networks and self-attention

PF de Araujo-Filho, M Naili, G Kaddoum… - … on Network and …, 2023 - ieeexplore.ieee.org
Fifth-generation (5G) networks provide connectivity to a massive number of devices and
boost a plethora of applications in several different domains. However, the large adoption of …