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 …

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 IP flows with principal component analysis and ant colony optimization

G Fernandes Jr, LF Carvalho, JJPC Rodrigues… - Journal of Network and …, 2016 - Elsevier
It is remarkable how proactive network management is in such demand nowadays, since
networks are growing in size and complexity and Information Technology services cannot be …

Machine learning techniques applied to detect cyber attacks on web applications

M Choraś, R Kozik - Logic Journal of IGPL, 2015 - academic.oup.com
The increased usage of cloud services, growing number of web applications users, changes
in network infrastructure that connects devices running mobile operating systems and …

Mapreduce intrusion detection system based on a particle swarm optimization clustering algorithm

I Aljarah, SA Ludwig - 2013 IEEE congress on evolutionary …, 2013 - ieeexplore.ieee.org
The increasing volume of data in large networks to be analyzed imposes new challenges to
an intrusion detection system. Since data in computer networks is growing rapidly, the …

DyClee: Dynamic clustering for tracking evolving environments

NB Roa, L Travé-Massuyès, VH Grisales-Palacio - Pattern Recognition, 2019 - Elsevier
Evolving environments challenge researchers with non stationary data flows where the
concepts–or states–being tracked can change over time. This requires tracking algorithms …

Real-time support vector machine based network intrusion detection system using Apache Storm

MA Manzoor, Y Morgan - 2016 IEEE 7th Annual Information …, 2016 - ieeexplore.ieee.org
Network intrusion detection is critical component of network management for security, quality
of service and other purposes. These systems allow early detection of network intrusion and …

Hunting attacks in the dark: clustering and correlation analysis for unsupervised anomaly detection

J Mazel, P Casas, R Fontugne… - … Journal of Network …, 2015 - Wiley Online Library
Network anomalies and attacks represent a serious challenge to ISPs, who need to cope
with an increasing number of unknown events that put their networks' integrity at risk. Most of …

Unsupervised classification and characterization of honeypot attacks

P Owezarski - 10th International Conference on Network and …, 2014 - ieeexplore.ieee.org
Monitoring communication networks and their traffic is of essential importance for estimating
the risk in the Internet, and therefore designing suited protection systems for computer …

MSCA: An unsupervised anomaly detection system for network security in backbone network

Y Liu, Y Gu, X Shen, Q Liao, Q Yu - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Anomaly detection is a crucial topic in network security which refers to automatically mining
known and unknown attacks or threats. Many detectors have been proposed in the last …