Efficient density and cluster based incremental outlier detection in data streams

A Degirmenci, O Karal - Information Sciences, 2022 - Elsevier
In this paper, a novel, parameter-free, incremental local density and cluster-based outlier
factor (iLDCBOF) method is presented that unifies incremental versions of local outlier factor …

When SDN Meets Low-rate Threats: A Survey of Attacks and Countermeasures in Programmable Networks

D Tang, R Dai, Y Yan, K Li, W Liang, Z Qin - ACM Computing Surveys, 2024 - dl.acm.org
Low-rate threats are a class of attack vectors that are disruptive and stealthy, typically crafted
for security vulnerabilities. They have been the significant concern for cyber security …

Performance and features: Mitigating the low-rate TCP-targeted DoS attack via SDN

D Tang, Y Yan, S Zhang, J Chen… - IEEE Journal on Selected …, 2021 - ieeexplore.ieee.org
Software-Defined Networking (SDN) is an emerging network architecture. The decoupled
data and control plane provides programmability for efficient network management …

Detection and mitigation of low-rate denial-of-service attacks: A survey

VDM Rios, PRM Inácio, D Magoni, MM Freire - IEEE Access, 2022 - ieeexplore.ieee.org
The potential for being the target of Denial of Service (DoS) attacks is one of the most severe
security threats on the Internet. Attackers have been modifying their attack format over the …

AKN-FGD: adaptive kohonen network based fine-grained detection of ldos attacks

D Tang, X Wang, X Li, P Vijayakumar… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Low-rate denial of service (LDoS) attacks exploit the security vulnerabilities of network
protocols adaptive mechanisms to launch periodic bursts. These attacks result in the severe …

[Retracted] Research on DoS Traffic Detection Model Based on Random Forest and Multilayer Perceptron

H He, G Huang, B Zhang… - Security and …, 2022 - Wiley Online Library
Denial of service (DoS) attack is a typical and extremely destructive attack, which poses a
serious threat to the Internet security and is highly concealed, making it difficult to detect. In …

A new detection method for LDoS attacks based on data mining

D Tang, J Chen, X Wang, S Zhang, Y Yan - Future Generation Computer …, 2022 - Elsevier
The serving capabilities of networks are reduced by low-rate denial of service (LDoS)
attacks that periodically send high-intensity pulse data flows. This type of attack shows a …

A deep 1-d CNN and bidirectional LSTM ensemble model with arbitration mechanism for lddos attack detection

Z Liu, J Yu, B Yan, G Wang - IEEE Transactions on Emerging …, 2022 - ieeexplore.ieee.org
Low-rate Distributed Denial of Service (LDDoS) attacks are complex and common security
issues, which disrupt the essential services of the varied and emerging networks. However …

Multi-homed abnormal behavior detection algorithm based on fuzzy particle swarm cluster in user and entity behavior analytics

J Cui, G Zhang, Z Chen, N Yu - Scientific Reports, 2022 - nature.com
User and entity behavior analytics (UEBA) is an anomaly detection technique that identifies
potential threat events in the enterprise's internal threat analysis and external intrusion …

Observer-Based Dynamic Event-Triggered Robust H Control of Networked Control Systems Under DoS Attacks

L Huang, J Guo, B Li - IEEE Access, 2021 - ieeexplore.ieee.org
This paper designs an observer-based controller with a dynamic event-triggered strategy for
networked control systems with external disturbance, system uncertainty, and unknown …