Deep Learning Model for Cybersecurity Attack Detection in Cyber-Physical Systems

M Abdullahi, H Alhussian, N Aziz… - 2022 6th …, 2022 - ieeexplore.ieee.org
In recent years, there has been an increasing demand for computing devices in cyber-
physical systems (CPS), which include smart manufacturing, air intelligent transportation …

Self-aware effective identification and response to viral cyber threats

P Baroni, F Cerutti, D Fogli, M Giacomin… - … on Cyber Conflict …, 2021 - ieeexplore.ieee.org
Artificial intelligence (AI) techniques can significantly improve cyber security operations if
tasks and responsibilities are effectively shared between human and machine. AI …

NexGuard: Industrial Cyber-Physical System Défense Using Ensemble Feature Selection and Explainable Deep Learning Techniques

S Krishnaveni, S Sivamohan, TM Chen… - 2023 2nd …, 2023 - ieeexplore.ieee.org
In recent years, industrial cyber-physical systems (ICPS) have advanced rapidly, resulting in
sophisticated and intelligent networks of industrial devices and systems. These networks …

[PDF][PDF] Advances in Machine Learning For Safeguarding a PUREX Reprocessing Facility.

N Shoman, BB Cipiti - 2020 - osti.gov
The average IAEA inspector spends approximately 100 days in the field per year verifying
activities at various nuclear facilities. Detecting diversion of nuclear material from bulk …

[HTML][HTML] Bridging the Cybersecurity Gap: A Comprehensive Analysis of Threats to Power Systems, Water Storage, and Gas Network Industrial Control and Automation …

T Gueye, A Iqbal, Y Wang, RT Mushtaq, MI Petra - Electronics, 2024 - mdpi.com
This research addresses the dearth of real-world data required for effective neural network
model building, delving into the crucial field of industrial control and automation system …

Improving situational awareness in aviation: Robust vision-based detection of hazardous objects

A Levin, N Vidimlic - 2020 - diva-portal.org
Enhanced vision and object detection could be useful in the aviation domain in situations of
bad weather or cluttered environments. In particular, enhanced vision and object detection …

Procedurally generated simulated datasets for aerial explosive hazard detection

J Kerley, A Fuller, M Kovaleski… - Chemical …, 2022 - spiedigitallibrary.org
Recent advancements in signal processing and computer vision are largely due to machine
learning (ML). While exciting, the reality is that most modern ML approaches are based on …

Projected needs for robot-assisted chemical, biological, radiological, or nuclear (CBRN) incidents

RR Murphy, J Peschel, C Arnett… - 2012 IEEE International …, 2012 - ieeexplore.ieee.org
This report projects the need for unmanned aerial and ground vehicles to assist with a
response to a hazardous material incident, also called chemical biological radiological or …

[图书][B] Deep learning applications for cyber security

M Alazab, MJ Tang - 2019 - Springer
ICT is arguably the greatest general purpose tool currently invented by mankind. It has
turned the carts into autonomous vehicles, the printing press into the Internet, the telephone …

[HTML][HTML] Fast complex-valued CNN for radar jamming signal recognition

H Zhang, L Yu, Y Chen, Y Wei - Remote Sensing, 2021 - mdpi.com
Jamming is a big threat to the survival of a radar system. Therefore, the recognition of radar
jamming signal type is a part of radar countermeasure. Recently, convolutional neural …