This paper surveys the deep learning (DL) approaches for intrusion-detection systems
(IDSs) in Internet of Things (IoT) and the associated datasets toward identifying gaps …

With the development of new technologies such as big data, cloud computing, and the
Internet of Things, network attack technology is constantly evolving and upgrading, and …

Advances in the Internet of Things (IoT) and aviation sector have resulted in the emergence
of smart airports. Services and systems powered by the IoT enable smart airports to have …

With the latest advances in information and communication technologies, greater amounts of
sensitive user and corporate information are shared continuously across the network …

Nowadays, cloud computing provides easy access to a set of variable and configurable
computing resources based on user demand through the network. Cloud computing …

The recent boom in deep learning has revealed that the application of deep neural networks
is a valuable way to address network intrusion detection problems. This paper presents a …

Abstract Network-based Intrusion Detection Systems (NIDSs) are deployed in computer
networks to identify intrusions. NIDSs analyse network traffic to detect malicious content …

The enormous increase in the use of the Internet in daily life has provided an opportunity for
the intruder attempt to compromise the security principles of availability, confidentiality, and …

摘要随着互联网时代的发展, 内部威胁, 零日漏洞和DoS 攻击等攻击行为日益增加,
网络安全变得越来越重要, 入侵检测已成为网络攻击检测的一种重要手段. 随着机器学习算法的 …

Aiming at the poor performance and flexibility of traditional assessment methods of network
security in dealing with a large number of network attack data, this paper proposes a …