Recent trends in AI-based intelligent sensing

A Sharma, V Sharma, M Jaiswal, HC Wang… - Electronics, 2022 - mdpi.com
In recent years, intelligent sensing has gained significant attention because of its
autonomous decision-making ability to solve complex problems. Today, smart sensors …

Vibration-based anomaly detection using LSTM/SVM approaches

K Vos, Z Peng, C Jenkins, MR Shahriar… - … Systems and Signal …, 2022 - Elsevier
Fault detection is a critical step for machine condition monitoring and maintenance. With
advances in machine learning technologies, automated faulty condition identification can be …

Fuzzy-based energy management system with decision tree algorithm for power security system

K Ramya, Y Teekaraman, KAR Kumar - International Journal of …, 2019 - Springer
Energy security (ES) has great impact on power grids. Therefore it is important to have
power security service (PSS). The PSS should be designed to handle interference and …

[图书][B] The state of the art in intrusion prevention and detection

ASK Pathan - 2014 - api.taylorfrancis.com
Most of the security threats in various communications networks are posed by the illegitimate
entities that enter or intrude within the network perimeter, which could commonly be termed …

A review on deep neural network for computer network traffic classification

MA Haque, DR Palit - arXiv preprint arXiv:2205.10830, 2022 - arxiv.org
Focus on Deep Neural Network based malicious and normal computer Network Traffic
classification.(such as attacks, phishing, any other illegal activity and normal traffic …

Intensive pre-processing of kdd cup 99 for network intrusion classification using machine learning techniques

I Obeidat, N Hamadneh, M Alkasassbeh, M Almseidin… - 2019 - learntechlib.org
Network security engineers work to keep services available all the time by handling intruder
attacks. Intrusion Detection System (IDS) is one of the obtainable mechanism that used to …

Analysis of intrusion detection in cyber attacks using DEEP learning neural networks

P Kumar, AA Kumar, C Sahayakingsly… - Peer-to-Peer Networking …, 2021 - Springer
In this digital period, internet has turned into an indispensable wellspring of correspondence
in just about every calling. With the expanded use of system engineering, its security has …

Machine learning methods for network intrusion detection

M Alkasassbeh, M Almseidin - arXiv preprint arXiv:1809.02610, 2018 - arxiv.org
Network security engineers work to keep services available all the time by handling intruder
attacks. Intrusion Detection System (IDS) is one of the obtainable mechanisms that is used to …

Identifying false data injection attacks in industrial control systems using artificial neural networks

S Potluri, C Diedrich… - 2017 22nd IEEE …, 2017 - ieeexplore.ieee.org
Cyber-attacks on Industrial Control Systems (ICS) are growing in recent years. Existing IT-
security technologies are not sufficient enough to protect the ICS from the novel attacks …

Optimize the coverage probability of prediction interval for anomaly detection of sensor-based monitoring series

J Pang, D Liu, Y Peng, X Peng - Sensors, 2018 - mdpi.com
Effective anomaly detection of sensing data is essential for identifying potential system
failures. Because they require no prior knowledge or accumulated labels, and provide …