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Cyber risk and cybersecurity: a systematic review of data availability
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 …
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
In the rapidly changing cybersecurity landscape, threat hunting has become a critical
proactive defense against sophisticated cyber threats. While traditional security measures …
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
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 …
constrained computing power, and hence, their poor security evaluation capabilities make …
[HTML][HTML] Machine learning schemes for anomaly detection in solar power plants
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 …
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
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 …
(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 …
Things (IoT) networks. Researchers have proposed numerous intrusion detection …
Cloud‐based video streaming services: Trends, challenges, and opportunities
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 …
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 …
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 …
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 …
to investigate any signs of any abnormalities over the network. Recently, intrusion detection …