One of the major challenges in cybersecurity is the provision of an automated and effective
cyber-threats detection technique. In this paper, we present an AI technique for cyberthreats …

One of the major challenges in cybersecurity is the provision of an automated and effective
cyber-threats detection technique. In this paper, we present an AI technique for cyber-threats …

At the present time, Security is a crucial issue for all organizations and companies, because
intruders are constantly developing new techniques to infiltrate their infrastructure to steal or …

Over the last years, several works have proposed highly accurate machine learning (ML)
techniques for network-based intrusion detection systems (NIDS), that are hardly used in …

As various types of network threats have increased recently, manual threat response by
security analysts has become a limitation. To compensate for this, the importance of security …

The use of Machine Learning (ML) techniques in Intrusion Detection Systems (IDS) has
taken a prominent role in the network security management field, due to the substantial …

In this paper, we present a survey of deep learning approaches for cyber security intrusion
detection, the datasets used, and a comparative study. Specifically, we provide a review of …

Intrusion detection systems (IDSs) are employed to maintain computer networks from cyber
attacks. Here, the aim is to detect intrusions once the data is transmitted across the internet …

With successful machine learning applications in many fields, researchers tried to introduce
machine learning into intrusion detection systems for building classification models …

The widespread use of the Internet of Things and distributed heterogeneous devices has
shed light on the implementation of efficient and reliable intrusion detection systems. These …