A holistic review of network anomaly detection systems: A comprehensive survey

N Moustafa, J Hu, J Slay - Journal of Network and Computer Applications, 2019 - Elsevier
Abstract Network Anomaly Detection Systems (NADSs) are gaining a more important role in
most network defense systems for detecting and preventing potential threats. The paper …

Distributed denial of service (DDoS) resilience in cloud: Review and conceptual cloud DDoS mitigation framework

O Osanaiye, KKR Choo, M Dlodlo - Journal of Network and Computer …, 2016 - Elsevier
Despite the increasing popularity of cloud services, ensuring the security and availability of
data, resources and services remains an ongoing research challenge. Distributed denial of …

Deep abstraction and weighted feature selection for Wi-Fi impersonation detection

ME Aminanto, R Choi, HC Tanuwidjaja… - IEEE Transactions …, 2017 - ieeexplore.ieee.org
The recent advances in mobile technologies have resulted in Internet of Things (IoT)-
enabled devices becoming more pervasive and integrated into our daily lives. The security …

Big data analytics framework for peer-to-peer botnet detection using random forests

K Singh, SC Guntuku, A Thakur, C Hota - Information Sciences, 2014 - Elsevier
Network traffic monitoring and analysis-related research has struggled to scale for massive
amounts of data in real time. Some of the vertical scaling solutions provide good …

Survey of network intrusion detection methods from the perspective of the knowledge discovery in databases process

B Molina-Coronado, U Mori… - … on Network and …, 2020 - ieeexplore.ieee.org
The identification of network attacks which target information and communication systems
has been a focus of the research community for years. Network intrusion detection is a …

A review on machine learning approaches for network malicious behavior detection in emerging technologies

M Rabbani, Y Wang, R Khoshkangini, H Jelodar… - Entropy, 2021 - mdpi.com
Network anomaly detection systems (NADSs) play a significant role in every network
defense system as they detect and prevent malicious activities. Therefore, this paper offers …

A study on intrusion detection using neural networks trained with evolutionary algorithms

T Dash - Soft Computing, 2017 - Springer
Intrusion detection has been playing a crucial role for making a computer network secure for
any transaction. An intrusion detection system (IDS) detects various types of malicious …

[PDF][PDF] Deep learning in intrusion detection system: An overview

E Aminanto, K Kim - 2016 International Research Conference on …, 2016 - caislab.kaist.ac.kr
Identifying unknown attacks is one of the big challenges in network Intrusion Detection
Systems (IDSs) research. In the past decades, researchers adopted various machine …

Mitigating TCP SYN flooding based EDOS attack in cloud computing environment using binomial distribution in SDN

SQA Shah, FZ Khan, M Ahmad - Computer Communications, 2022 - Elsevier
Cloud Computing provides an auto-scaling feature for dynamic resource utilization to cope
with their customers' requirements and charge as 'pay-per-use'. Attackers get the benefit of …

Detecting impersonation attack in WiFi networks using deep learning approach

ME Aminanto, K Kim - … : 17th International Workshop, WISA 2016, Jeju …, 2017 - Springer
WiFi network traffics will be expected to increase sharply in the coming years, since WiFi
network is commonly used for local area connectivity. Unfortunately, there are difficulties in …