Towards an optimal feature selection method for AI-based DDoS detection system

S Saha, AT Priyoti, A Sharma… - 2022 IEEE 19th Annual …, 2022 - ieeexplore.ieee.org
Cyber-attacks are increasing rapidly, so developing effective intrusion detection and
prevention tools for a secure and safer cyberspace is crucial. DDoS (Distributed Denial of …

Detecting DDoS attacks using machine learning techniques and contemporary intrusion detection dataset

N Bindra, M Sood - Automatic Control and Computer Sciences, 2019 - Springer
Recent trends have revealed that DDoS attacks contribute to the majority of overall network
attacks. Networks face challenges in distinguishing between legitimate and malicious flows …

A systematic literature review on machine learning and deep learning approaches for detecting DDoS attacks in software-defined networking

AA Bahashwan, M Anbar, S Manickam, TA Al-Amiedy… - Sensors, 2023 - mdpi.com
Software-defined networking (SDN) is a revolutionary innovation in network technology with
many desirable features, including flexibility and manageability. Despite those advantages …

Domain generated algorithms detection applying a combination of a deep feature selection and traditional machine learning models

M Hassaoui, M Hanini… - Journal of Computer …, 2023 - content.iospress.com
The use of command and control (C2) servers in cyberattacks has risen considerably,
attackers frequently employ the domain generated algorithm (DGA) technique to conceal …

Crypto-preserving investigation framework for deep learning based malware attack detection for network forensics

S Bhardwaj, M Dave - Wireless Personal Communications, 2022 - Springer
The exponential growth in technology observed over the past decade has introduced newer
ways to exploit network and cyber-physical system-related vulnerabilities. Cybercriminals …

Detection of DDoS attack and classification using a hybrid approach

S Nandi, S Phadikar, K Majumder - 2020 Third ISEA …, 2020 - ieeexplore.ieee.org
In the area of cloud security, detection of DDoS attack is a challenging task such that
legitimate users use the cloud resources properly. So in this paper, detection and …

[PDF][PDF] A framework for robust attack detection and classification using rap-densenet

TS Adekunle, TA Adeleke, O Sunday, GN Ebong… - …, 2023 - researchgate.net
Network attacks must be effectively identified and categorized to guarantee strong security.
However, current techniques frequently have trouble correctly identifying and categorizing …

An effective deep learning based multi-class classification of dos and ddos attack detection

AK Silivery, KRM Rao, LK Kumar - International journal of electrical …, 2023 - hrcak.srce.hr
Sažetak In the past few years, cybersecurity is becoming very important due to the rise in
internet users. The internet attacks such as Denial of service (DoS) and Distributed Denial of …

[PDF][PDF] Forging a deep learning neural network intrusion detection framework to curb the distributed denial of service attack

AA Ojugo, RE Yoro - International Journal of Electrical and Computer …, 2021 - academia.edu
Today's popularity of the internet has since proven an effective and efficient means of
information sharing. However, this has consequently advanced the proliferation of …

Ddos attack detection in wsn using modified bgru with mfo model

S Venkatasubramanian… - Advanced Applications of …, 2024 - igi-global.com
Significant challenges in the areas of energy and security persist for wireless sensor
networks (WSNs). Avoiding denial-of-service assaults is a priority for safeguarding WSN …