From intrusion detection to attacker attribution: A comprehensive survey of unsupervised methods
Over the last five years there has been an increase in the frequency and diversity of network
attacks. This holds true, as more and more organizations admit compromises on a daily …
attacks. This holds true, as more and more organizations admit compromises on a daily …
Flow-based intrusion detection: Techniques and challenges
MF Umer, M Sher, Y Bi - Computers & Security, 2017 - Elsevier
Flow-based intrusion detection is an innovative way of detecting intrusions in high-speed
networks. Flow-based intrusion detection only inspects the packet header and does not …
networks. Flow-based intrusion detection only inspects the packet header and does not …
Boosting-based DDoS detection in internet of things systems
I Cvitić, D Perakovic, BB Gupta… - IEEE Internet of Things …, 2021 - ieeexplore.ieee.org
Distributed Denial-of-Service (DDoS) attacks remain challenging to mitigate in the existing
systems, including in-home networks that comprise different Internet of Things (IoT) devices …
systems, including in-home networks that comprise different Internet of Things (IoT) devices …
Multi-level hybrid support vector machine and extreme learning machine based on modified K-means for intrusion detection system
Intrusion detection has become essential to network security because of the increasing
connectivity between computers. Several intrusion detection systems have been developed …
connectivity between computers. Several intrusion detection systems have been developed …
A double-layered hybrid approach for network intrusion detection system using combined naive bayes and SVM
T Wisanwanichthan, M Thammawichai - Ieee Access, 2021 - ieeexplore.ieee.org
A pattern matching method (signature-based) is widely used in basic network intrusion
detection systems (IDS). A more robust method is to use a machine learning classifier to …
detection systems (IDS). A more robust method is to use a machine learning classifier to …
Efficient feature selection and classification through ensemble method for network intrusion detection on cloud computing
Cloud computing is a preferred option for organizations around the globe, it offers scalable
and internet-based computing resources as a flexible service. Security is a key concern …
and internet-based computing resources as a flexible service. Security is a key concern …
Evaluation of machine learning classifiers for mobile malware detection
Mobile devices have become a significant part of people's lives, leading to an increasing
number of users involved with such technology. The rising number of users invites hackers …
number of users involved with such technology. The rising number of users invites hackers …
Intrusion detection techniques for mobile cloud computing in heterogeneous 5G
Mobile cloud computing is applied in multiple industries to obtain cloud‐based services by
leveraging mobile technologies. With the development of the wireless networks, defending …
leveraging mobile technologies. With the development of the wireless networks, defending …
[PDF][PDF] Towards Generating Real-life Datasets for Network Intrusion Detection.
With exponential growth in the number of computer applications and the sizes of networks,
the potential damage that can be caused by attacks launched over the Internet keeps …
the potential damage that can be caused by attacks launched over the Internet keeps …
A novel architecture combined with optimal parameters for back propagation neural networks applied to anomaly network intrusion detection
Today, as attacks against computer networks are evolving rapidly, Network Intrusion
Detection System (NIDS) has become a valuable tool for the defense-in-depth of computer …
Detection System (NIDS) has become a valuable tool for the defense-in-depth of computer …