A survey on intrusion detection system: feature selection, model, performance measures, application perspective, challenges, and future research directions
With the increase in the usage of the Internet, a large amount of information is exchanged
between different communicating devices. The data should be communicated securely …
between different communicating devices. The data should be communicated securely …
Machine learning and deep learning methods for intrusion detection systems: A survey
H Liu, B Lang - applied sciences, 2019 - mdpi.com
Networks play important roles in modern life, and cyber security has become a vital research
area. An intrusion detection system (IDS) which is an important cyber security technique …
area. An intrusion detection system (IDS) which is an important cyber security technique …
A survey and analysis of intrusion detection models based on cse-cic-ids2018 big data
JL Leevy, TM Khoshgoftaar - Journal of Big Data, 2020 - Springer
The exponential growth in computer networks and network applications worldwide has been
matched by a surge in cyberattacks. For this reason, datasets such as CSE-CIC-IDS2018 …
matched by a surge in cyberattacks. For this reason, datasets such as CSE-CIC-IDS2018 …
Machine learning-based IoT-botnet attack detection with sequential architecture
With the rapid development and popularization of Internet of Things (IoT) devices, an
increasing number of cyber-attacks are targeting such devices. It was said that most of the …
increasing number of cyber-attacks are targeting such devices. It was said that most of the …
Botnet Attack Detection by Using CNN‐LSTM Model for Internet of Things Applications
H Alkahtani, THH Aldhyani - Security and Communication …, 2021 - Wiley Online Library
The Internet of Things (IoT) has grown rapidly, and nowadays, it is exploited by cyber attacks
on IoT devices. An accurate system to identify malicious attacks on the IoT environment has …
on IoT devices. An accurate system to identify malicious attacks on the IoT environment has …
A self-adaptive deep learning-based system for anomaly detection in 5G networks
The upcoming fifth-generation (5G) mobile technology, which includes advanced
communication features, is posing new challenges on cybersecurity defense systems …
communication features, is posing new challenges on cybersecurity defense systems …
Towards sFlow and adaptive polling sampling for deep learning based DDoS detection in SDN
Abstract Distributed Denial of Service (DDoS) is one of the most rampant attacks in the
modern Internet of Things (IoT) network infrastructures. Security plays a very vital role for an …
modern Internet of Things (IoT) network infrastructures. Security plays a very vital role for an …
IoT intrusion detection taxonomy, reference architecture, and analyses
This paper surveys the deep learning (DL) approaches for intrusion-detection systems
(IDSs) in Internet of Things (IoT) and the associated datasets toward identifying gaps …
(IDSs) in Internet of Things (IoT) and the associated datasets toward identifying gaps …
[HTML][HTML] Packet analysis for network forensics: A comprehensive survey
LF Sikos - Forensic Science International: Digital Investigation, 2020 - Elsevier
Packet analysis is a primary traceback technique in network forensics, which, providing that
the packet details captured are sufficiently detailed, can play back even the entire network …
the packet details captured are sufficiently detailed, can play back even the entire network …
A firefly algorithm modified support vector machine for the credit risk assessment of supply chain finance
H Zhang, Y Shi, X Yang, R Zhou - Research in International Business and …, 2021 - Elsevier
Abstract Purpose Nowadays, Supply Chain Finance (SCF) has been developing rapidly
since the emergence of credit risk. Therefore, this paper used SVM optimized by the firefly …
since the emergence of credit risk. Therefore, this paper used SVM optimized by the firefly …