Benchmarking of machine learning for anomaly based intrusion detection systems in the CICIDS2017 dataset

ZK Maseer, R Yusof, N Bahaman, SA Mostafa… - IEEE …, 2021 - ieeexplore.ieee.org
An intrusion detection system (IDS) is an important protection instrument for detecting
complex network attacks. Various machine learning (ML) or deep learning (DL) algorithms …

A survey on machine learning-based malware detection in executable files

J Singh, J Singh - Journal of Systems Architecture, 2021 - Elsevier
In last decade, a proliferation growth in the development of computer malware has been
done. Nowadays, cybercriminals (attacker) use malware as a weapon to carry out the …

Fuzzy logic-based DDoS attacks and network traffic anomaly detection methods: Classification, overview, and future perspectives

D Javaheri, S Gorgin, JA Lee, M Masdari - Information Sciences, 2023 - Elsevier
Nowadays, cybersecurity challenges and their ever-growing complexity are the main
concerns for various information technology-driven organizations and companies. Although …

Deep learning-based intrusion detection systems: a systematic review

J Lansky, S Ali, M Mohammadi, MK Majeed… - IEEE …, 2021 - ieeexplore.ieee.org
Nowadays, the ever-increasing complication and severity of security attacks on computer
networks have inspired security researchers to incorporate different machine learning …

TP2SF: A Trustworthy Privacy-Preserving Secured Framework for sustainable smart cities by leveraging blockchain and machine learning

P Kumar, GP Gupta, R Tripathi - Journal of Systems Architecture, 2021 - Elsevier
With the advancement in sensor technology and the proliferation of low-cost electronic
circuits, Internet of Things (IoT) is emerging as a promising technology for realization of …

Machine and deep learning solutions for intrusion detection and prevention in IoTs: A survey

PLS Jayalaxmi, R Saha, G Kumar, M Conti… - IEEE Access, 2022 - ieeexplore.ieee.org
The increasing number of connected devices in the era of Internet of Thing (IoT) has also
increased the number intrusions. Intrusion Detection System (IDS) is a secondary intelligent …

Towards secure intrusion detection systems using deep learning techniques: Comprehensive analysis and review

SW Lee, M Mohammadi, S Rashidi… - Journal of Network and …, 2021 - Elsevier
Providing a high-performance Intrusion Detection System (IDS) can be very effective in
controlling malicious behaviors and cyber-attacks. Regarding the ever-growing negative …

A hybrid machine learning model for intrusion detection in VANET

H Bangui, M Ge, B Buhnova - Computing, 2022 - Springer
Abstract While Vehicular Ad-hoc Network (VANET) is developed to enable effective vehicle
communication and traffic information exchange, VANET is also vulnerable to different …

A survey on security and authentication in wireless body area networks

B Narwal, AK Mohapatra - Journal of Systems Architecture, 2021 - Elsevier
Abstract Wireless Body Area Networks (WBAN) is often envisioned as a paradigm shift from
the traditional healthcare system to the modern E-Healthcare system. The patient's vitals …

[HTML][HTML] LITNET-2020: An annotated real-world network flow dataset for network intrusion detection

R Damasevicius, A Venckauskas, S Grigaliunas… - Electronics, 2020 - mdpi.com
Network intrusion detection is one of the main problems in ensuring the security of modern
computer networks, Wireless Sensor Networks (WSN), and the Internet-of-Things (IoT). In …