Network intrusion detection system: A systematic study of machine learning and deep learning approaches
The rapid advances in the internet and communication fields have resulted in a huge
increase in the network size and the corresponding data. As a result, many novel attacks are …
increase in the network size and the corresponding data. As a result, many novel attacks are …
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 …
A detailed investigation and analysis of using machine learning techniques for intrusion detection
P Mishra, V Varadharajan… - … surveys & tutorials, 2018 - ieeexplore.ieee.org
Intrusion detection is one of the important security problems in todays cyber world. A
significant number of techniques have been developed which are based on machine …
significant number of techniques have been developed which are based on machine …
Intrusion detection systems using long short-term memory (LSTM)
An intrusion detection system (IDS) is a device or software application that monitors a
network for malicious activity or policy violations. It scans a network or a system for a harmful …
network for malicious activity or policy violations. It scans a network or a system for a harmful …
Deep learning-based intrusion detection systems: a systematic review
Nowadays, the ever-increasing complication and severity of security attacks on computer
networks have inspired security researchers to incorporate different machine learning …
networks have inspired security researchers to incorporate different machine learning …
Machine learning-enabled iot security: Open issues and challenges under advanced persistent threats
Despite its technological benefits, the Internet of Things (IoT) has cyber weaknesses due to
vulnerabilities in the wireless medium. Machine Larning (ML)-based methods are widely …
vulnerabilities in the wireless medium. Machine Larning (ML)-based methods are widely …
Provenance-based intrusion detection systems: A survey
Traditional Intrusion Detection Systems (IDS) cannot cope with the increasing number and
sophistication of cyberattacks such as Advanced Persistent Threats (APT). Due to their high …
sophistication of cyberattacks such as Advanced Persistent Threats (APT). Due to their high …
A survey of network anomaly detection techniques
M Ahmed, AN Mahmood, J Hu - Journal of Network and Computer …, 2016 - Elsevier
Abstract Information and Communication Technology (ICT) has a great impact on social
wellbeing, economic growth and national security in todays world. Generally, ICT includes …
wellbeing, economic growth and national security in todays world. Generally, ICT includes …
Survey of attack projection, prediction, and forecasting in cyber security
This paper provides a survey of prediction, and forecasting methods used in cyber security.
Four main tasks are discussed first, attack projection and intention recognition, in which …
Four main tasks are discussed first, attack projection and intention recognition, in which …
Chained anomaly detection models for federated learning: An intrusion detection case study
The adoption of machine learning and deep learning is on the rise in the cybersecurity
domain where these AI methods help strengthen traditional system monitoring and threat …
domain where these AI methods help strengthen traditional system monitoring and threat …