Cyber risk and cybersecurity: a systematic review of data availability

F Cremer, B Sheehan, M Fortmann… - The Geneva papers …, 2022 - pmc.ncbi.nlm.nih.gov
Cybercrime is estimated to have cost the global economy just under USD 1 trillion in 2020,
indicating an increase of more than 50% since 2018. With the average cyber insurance …

[HTML][HTML] Evolving techniques in cyber threat hunting: A systematic review

A Mahboubi, K Luong, H Aboutorab, HT Bui… - Journal of Network and …, 2024 - Elsevier
In the rapidly changing cybersecurity landscape, threat hunting has become a critical
proactive defense against sophisticated cyber threats. While traditional security measures …

LMCA: a lightweight anomaly network traffic detection model integrating adjusted mobilenet and coordinate attention mechanism for IoT

D Han, HX Zhou, TH Weng, Z Wu, B Han, KC Li… - Telecommunication …, 2023 - Springer
As widely known, most of the Internet of Things (IoT) devices own small storage and
constrained computing power, and hence, their poor security evaluation capabilities make …

[HTML][HTML] Machine learning schemes for anomaly detection in solar power plants

M Ibrahim, A Alsheikh, FM Awaysheh, MD Alshehri - Energies, 2022 - mdpi.com
The rapid industrial growth in solar energy is gaining increasing interest in renewable power
from smart grids and plants. Anomaly detection in photovoltaic (PV) systems is a demanding …

Security and privacy for low power iot devices on 5g and beyond networks: Challenges and future directions

J Cook, SU Rehman, MA Khan - IEEE Access, 2023 - ieeexplore.ieee.org
The growth in the use of small sensor devices, commonly known as the Internet of Things
(IoT), has resulted in unprecedented amounts of data being generated and captured. With …

[HTML][HTML] A comparative assessment of machine learning algorithms in the IoT-based network intrusion detection systems

M Samantaray, RC Barik, AK Biswal - Decision Analytics Journal, 2024 - Elsevier
The rapid increase in online risks is a reflection of the exponential growth of Internet of
Things (IoT) networks. Researchers have proposed numerous intrusion detection …

Cloud‐based video streaming services: Trends, challenges, and opportunities

T Kumar, P Sharma, J Tanwar… - CAAI Transactions …, 2024 - Wiley Online Library
Cloud computing has drastically changed the delivery and consumption of live streaming
content. The designs, challenges, and possible uses of cloud computing for live streaming …

Explainable AI-based innovative hybrid ensemble model for intrusion detection

U Ahmed, Z Jiangbin, A Almogren, S Khan… - Journal of Cloud …, 2024 - Springer
Cybersecurity threats have become more worldly, demanding advanced detection
mechanisms with the exponential growth in digital data and network services. Intrusion …

[HTML][HTML] Using machine learning for detecting liquidity risk in banks

RI Barongo, JT Mbelwa - Machine Learning with Applications, 2024 - Elsevier
The accurate classification of banks' Liquidity Risk (LR) for regulatory supervision is
hindered by limitations in the measures, such as Minimum Liquid Assets (MLA), Net-Stable …

[PDF][PDF] Network intrusion detection system: Machine learning approach

AS Jaradat, MM Barhoush, RB Easa - Indonesian Journal of …, 2022 - researchgate.net
The main goal of intrusion detection system (IDS) is to monitor the network performance and
to investigate any signs of any abnormalities over the network. Recently, intrusion detection …