A Survey of Intrusion Detection Techniques

With the growing rate of cyber attacks, there is a significant need for intrusion detection systems (IDS) in networked environments. As intrusion tactics become more sophisticated and more challenging to detect, this necessitates improved intrusion detection technology to retain user trust and preserve network security. Over the last decade, several detection methodologies have been designed to provide users with reliability, privacy, and information security. This paper reviews three intrusion detection techniques: blockchain technologies, machine learning, and deep learning. This survey overviews various machine learning and deep learning algorithms, summarizes blockchain technology, and discusses different blockchain methods used for intrusion detection and cybersecurity. We provide insight into their applications, drawbacks, and challenges.