Real-time big data processing for anomaly detection: A survey

RAA Habeeb, F Nasaruddin, A Gani… - International Journal of …, 2019 - Elsevier
The advent of connected devices and omnipresence of Internet have paved way for
intruders to attack networks, which leads to cyber-attack, financial loss, information theft in …

A comprehensive survey of anomaly detection techniques for high dimensional big data

S Thudumu, P Branch, J Jin, J Singh - Journal of Big Data, 2020 - Springer
Anomaly detection in high dimensional data is becoming a fundamental research problem
that has various applications in the real world. However, many existing anomaly detection …

Enhanced network anomaly detection based on deep neural networks

S Naseer, Y Saleem, S Khalid, MK Bashir, J Han… - IEEE …, 2018 - ieeexplore.ieee.org
Due to the monumental growth of Internet applications in the last decade, the need for
security of information network has increased manifolds. As a primary defense of network …

A comprehensive survey on network anomaly detection

G Fernandes, JJPC Rodrigues, LF Carvalho… - Telecommunication …, 2019 - Springer
Nowadays, there is a huge and growing concern about security in information and
communication technology among the scientific community because any attack or anomaly …

Machine learning in network anomaly detection: A survey

S Wang, JF Balarezo, S Kandeepan… - IEEE …, 2021 - ieeexplore.ieee.org
Anomalies could be the threats to the network that have ever/never happened. To protect
networks against malicious access is always challenging even though it has been studied …

Data-driven edge intelligence for robust network anomaly detection

S Xu, Y Qian, RQ Hu - IEEE Transactions on Network Science …, 2019 - ieeexplore.ieee.org
The advancement of networking platforms for assured online services requires robust and
effective network intelligence systems against anomalous events and malicious threats. With …

Clustering‐based real‐time anomaly detection—A breakthrough in big data technologies

RA Ariyaluran Habeeb, F Nasaruddin… - Transactions on …, 2022 - Wiley Online Library
Off late, the ever increasing usage of a connected Internet‐of‐Things devices has
consequently augmented the volume of real‐time network data with high velocity. At the …

[图书][B] Network anomaly detection: A machine learning perspective

DK Bhattacharyya, JK Kalita - 2013 - books.google.com
With the rapid rise in the ubiquity and sophistication of Internet technology and the
accompanying growth in the number of network attacks, network intrusion detection has …

Big data analytics for network anomaly detection from netflow data

DS Terzi, R Terzi, S Sagiroglu - 2017 International Conference …, 2017 - ieeexplore.ieee.org
Cyber-attacks was organized in a simple and random way in the past. However attacks are
carried out systematically and long term nowadays. In addition, the high calculation volume …

A deep learning ensemble for network anomaly and cyber-attack detection

V Dutta, M Choraś, M Pawlicki, R Kozik - Sensors, 2020 - mdpi.com
Currently, expert systems and applied machine learning algorithms are widely used to
automate network intrusion detection. In critical infrastructure applications of communication …