Computational intelligence intrusion detection techniques in mobile cloud computing environments: Review, taxonomy, and open research issues

S Shamshirband, M Fathi, AT Chronopoulos… - Journal of Information …, 2020 - Elsevier
With the increasing utilization of the Internet and its provided services, an increase in cyber-
attacks to exploit the information occurs. A technology to store and maintain user's …

A survey of intrusion detection systems based on ensemble and hybrid classifiers

AA Aburomman, MBI Reaz - Computers & security, 2017 - Elsevier
Due to the frequency of malicious network activities and network policy violations, intrusion
detection systems (IDSs) have emerged as a group of methods that combats the …

A GA-LR wrapper approach for feature selection in network intrusion detection

C Khammassi, S Krichen - computers & security, 2017 - Elsevier
Intrusions constitute one of the main issues in computer network security. Through malicious
actions, hackers can have unauthorised access that compromises the integrity, the …

Ensemble-based multi-filter feature selection method for DDoS detection in cloud computing

O Osanaiye, H Cai, KKR Choo… - EURASIP Journal on …, 2016 - Springer
Widespread adoption of cloud computing has increased the attractiveness of such services
to cybercriminals. Distributed denial of service (DDoS) attacks targeting the cloud's …

FCM–SVM based intrusion detection system for cloud computing environment

AN Jaber, SU Rehman - Cluster Computing, 2020 - Springer
Cloud computing offer various services over the Internet based on pay-per-use concept.
Therefore, many organizations have already adopted this system to attract the users with its …

Data exfiltration: A review of external attack vectors and countermeasures

F Ullah, M Edwards, R Ramdhany, R Chitchyan… - Journal of Network and …, 2018 - Elsevier
Context One of the main targets of cyber-attacks is data exfiltration, which is the leakage of
sensitive or private data to an unauthorized entity. Data exfiltration can be perpetrated by an …

Network anomaly detection using channel boosted and residual learning based deep convolutional neural network

N Chouhan, A Khan - Applied Soft Computing, 2019 - Elsevier
Anomaly detection in a network is one of the prime concerns for network security. In this
work, a novel Channel Boosted and Residual learning based deep Convolutional Neural …

Towards effective network intrusion detection: from concept to creation on Azure cloud

S Rajagopal, PP Kundapur, KS Hareesha - IEEE Access, 2021 - ieeexplore.ieee.org
Network Intrusion Detection is one of the most researched topics in the field of computer
security. Hacktivists use sophisticated tools to launch numerous attacks that hamper the …

Hybrid Bayesian optimization hypertuned catboost approach for malicious access and anomaly detection in IoT nomalyframework

J Nayak, B Naik, PB Dash, S Vimal, S Kadry - … Computing: Informatics and …, 2022 - Elsevier
The successful applications and diversified popularity of the Internet of Things (IoT) present
various advantages and opportunities in broad characteristics of our lives. However …

A review of intrusion detection systems in RPL routing protocol based on machine learning for internet of things applications

A Seyfollahi, A Ghaffari - Wireless Communications and Mobile …, 2021 - Wiley Online Library
IPv6 routing protocol for low‐power and lossy networks (RPL) has been developed as a
routing agent in low‐power and lossy networks (LLN), where nodes' resource constraint …