UGR '16: A new dataset for the evaluation of cyclostationarity-based network IDSs
The evaluation of algorithms and techniques to implement intrusion detection systems
heavily rely on the existence of well designed datasets. In the last years, a lot of efforts have …
heavily rely on the existence of well designed datasets. In the last years, a lot of efforts have …
A review of rule learning-based intrusion detection systems and their prospects in smart grids
Intrusion detection systems (IDS) are commonly categorized into misuse based, anomaly
based and specification based IDS. Both misuse based IDS and anomaly based IDS are …
based and specification based IDS. Both misuse based IDS and anomaly based IDS are …
Cyber intrusion detection by combined feature selection algorithm
Due to the widespread diffusion of network connectivity, the demand for network security
and protection against cyber-attacks is ever increasing. Intrusion detection systems (IDS) …
and protection against cyber-attacks is ever increasing. Intrusion detection systems (IDS) …
Intrusion detection using big data and deep learning techniques
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 …
performance of intrusion detection systems. Three classifiers are used to classify network …
A survey of intrusion detection from the perspective of intrusion datasets and machine learning techniques
The evolution in the attack scenarios has been such that finding efficient and optimal
Network Intrusion Detection Systems (NIDS) with frequent updates has become a big …
Network Intrusion Detection Systems (NIDS) with frequent updates has become a big …
Towards a reliable comparison and evaluation of network intrusion detection systems based on machine learning approaches
Presently, we are living in a hyper-connected world where millions of heterogeneous
devices are continuously sharing information in different application contexts for wellness …
devices are continuously sharing information in different application contexts for wellness …
Evaluation of machine learning techniques for traffic flow-based intrusion detection
Cybersecurity is one of the great challenges of today's world. Rapid technological
development has allowed society to prosper and improve the quality of life and the world is …
development has allowed society to prosper and improve the quality of life and the world is …
Distributed detection of clone attacks in wireless sensor networks
Wireless Sensor Networks (WSNs) are often deployed in hostile environments where an
adversary can physically capture some of the nodes, first can reprogram, and then, can …
adversary can physically capture some of the nodes, first can reprogram, and then, can …
Alert correlation in collaborative intelligent intrusion detection systems—A survey
As complete prevention of computer attacks is not possible, intrusion detection systems
(IDSs) play a very important role in minimizing the damage caused by different computer …
(IDSs) play a very important role in minimizing the damage caused by different computer …
Botnet detection techniques: review, future trends, and issues
In recent years, the Internet has enabled access to widespread remote services in the
distributed computing environment; however, integrity of data transmission in the distributed …
distributed computing environment; however, integrity of data transmission in the distributed …