Detecting and preventing cyber insider threats: A survey

L Liu, O De Vel, QL Han, J Zhang… - … Surveys & Tutorials, 2018 - ieeexplore.ieee.org
Information communications technology systems are facing an increasing number of cyber
security threats, the majority of which are originated by insiders. As insiders reside behind …

Defense mechanisms against DDoS attacks in a cloud computing environment: State-of-the-art and research challenges

N Agrawal, S Tapaswi - IEEE Communications Surveys & …, 2019 - ieeexplore.ieee.org
The salient features of cloud computing (such as on-demand self-service, resource pooling,
broad network access, rapid elasticity, and measured service) are being exploited by …

A flexible SDN-based architecture for identifying and mitigating low-rate DDoS attacks using machine learning

JA Perez-Diaz, IA Valdovinos, KKR Choo, D Zhu - IEEE Access, 2020 - ieeexplore.ieee.org
While there have been extensive studies of denial of service (DoS) attacks and DDoS attack
mitigation, such attacks remain challenging to mitigate. For example, Low-Rate DDoS (LR …

A survey of distributed denial-of-service attack, prevention, and mitigation techniques

T Mahjabin, Y **ao, G Sun… - International Journal of …, 2017 - journals.sagepub.com
Distributed denial-of-service is one kind of the most highlighted and most important attacks
of today's cyberworld. With simple but extremely powerful attack mechanisms, it introduces …

Low-rate DoS attacks, detection, defense, and challenges: A survey

W Zhijun, L Wen**g, L Liang, Y Meng - IEEE access, 2020 - ieeexplore.ieee.org
Low-rate Denial of service (LDoS) attacks has become one of the biggest threats to the
Internet, cloud computing platforms, and big data centers. As an evolutionary species of …

Explainable AI-based DDOS attack identification method for IoT networks

CS Kalutharage, X Liu, C Chrysoulas, N Pitropakis… - Computers, 2023 - mdpi.com
The modern digitized world is mainly dependent on online services. The availability of
online systems continues to be seriously challenged by distributed denial of service (DDoS) …

[HTML][HTML] An entropy-based network anomaly detection method

P Bereziński, B Jasiul, M Szpyrka - Entropy, 2015 - mdpi.com
Data mining is an interdisciplinary subfield of computer science involving methods at the
intersection of artificial intelligence, machine learning and statistics. One of the data mining …

[HTML][HTML] A survey of low rate ddos detection techniques based on machine learning in software-defined networks

AA Alashhab, MSM Zahid, MA Azim, MY Daha… - Symmetry, 2022 - mdpi.com
Software-defined networking (SDN) is a new networking paradigm that provides centralized
control, programmability, and a global view of topology in the controller. SDN is becoming …

An early detection of low rate DDoS attack to SDN based data center networks using information distance metrics

KS Sahoo, D Puthal, M Tiwary, JJPC Rodrigues… - Future Generation …, 2018 - Elsevier
The primary innovations behind Software Defined Networks (SDN) are the decoupling of the
control plane from the data plane and centralizing the network management through a …

An SDN-based intrusion detection system using SVM with selective logging for IP traceback

P Hadem, DK Saikia, S Moulik - Computer Networks, 2021 - Elsevier
In this paper we introduce a Software Defined Networking (SDN) based Intrusion Detection
System (IDS) using the Support Vector Machines (SVM) along with Selective Logging for IP …