Intrusion detection systems (IDSs) are intrinsically linked to a comprehensive solution of
cyberattacks prevention instruments. To achieve a higher detection rate, the ability to design …

Intrusion detection is one of the most critical network security problems in the technology
world. Machine learning techniques are being implemented to improve the Intrusion …

Digital assets have come under various network security threats in the digital age. As a kind
of security equipment to protect digital assets, intrusion detection system (IDS) is less …

Recently, the huge amounts of data and its incremental increase have changed the
importance of information security and data analysis systems for Big Data. Intrusion …

In this paper, Big Data and Deep Learning Techniques are integrated to improve the
performance of intrusion detection systems. Three classifiers are used to classify network …

Intrusion Detection Systems (IDSs) utilise deep learning techniques to identify intrusions
with maximum accuracy and reduce false alarm rates. The feature extraction is also …

Serious concerns regarding vulnerability and security have been raised as a result of the
constant growth of computer networks. Intrusion detection systems (IDS) have been adopted …

The expeditious growth of the World Wide Web and the rampant flow of network traffic have
resulted in a continuous increase of network security threats. Cyber attackers seek to exploit …

The successful applications and diversified popularity of the Internet of Things (IoT) present
various advantages and opportunities in broad characteristics of our lives. However …

Internet evolution produced a connected world with a massive amount of data. This
connectivity advantage came with the price of more complex and advanced attacks …