Comparative Evaluation on Various Machine Learning Strategies Based on Identification of DDoS Attacks in IoT Environment

M Abinaya, S Prabakeran… - 2023 9th International …, 2023 - ieeexplore.ieee.org
IoT is a combination of networks that have the ability to collect and share the information
through web. Though IoT is used in areas such as healthcare, smart cities, agriculture …

PE-v-SVR based Architecture to Predict and Prevent Low and Slow-Rate DDoS Attacks using Machine Learning

D Chhettri, FJ George, AM Nair… - 2024 11th International …, 2024 - ieeexplore.ieee.org
Distributed Denial of Service (DDoS) attacks continue to emerge; low and slow attacks pose
a serious threat. These small-scale attacks often evade traditional security protections and …

Man-machine Cooperative Monitoring System to Support Detection of DoS/DDoS Attacks Through Continuous SOM Diagram Generation

H Suzuki, A Iwasa, T Uchiyama… - … on Networking and …, 2023 - ieeexplore.ieee.org
DoS/DDoS attacks on the Internet target various organizations and government agencies.
Because DoS/DDoS attacks disguise themselves as legitimate communication, they are …

[PDF][PDF] Research on the Characteristics and Detection Methods of DDoS Attacks on Wireless Sensor Networks for Vehicle Networking

X Fang, K Fang, G Li, X Jin, L Zheng - Eng. Adv, 2022 - hillpublisher.com
Smart vehicles constitute the intelligent transportation system, the complex traffic network of
multiple types of sensors in the energy consumption data and the amount of data transmitted …

HDS: A Hierarchical Scheme for Accurate and Efficient DDoS Flooding Attack Detection

Y Zhuang, H Wu, S Liu, G Cheng… - 2022 23rd Asia-Pacific …, 2022 - ieeexplore.ieee.org
As the scale of Distributed Denial of Service (DDoS) flooding attacks has increased
significantly, many detection methods have applied sketch data structures to compress the …

A novel CNN‐based approach for detection and classification of DDoS attacks

AA Najar, MN Sugali, FR Lone, A Nazir - … and Computation: Practice … - Wiley Online Library
Among the recent network security issues, Distributed Denial of Service (DDoS) attack is
one of the most dangerous threats in today's cyberspace that can disrupt essential services …

Development and evaluation of ensemble learning models for detection of distributed denial-of-service attacks in ınternet of things

Y Yılmaz, S Buyrukoğlu - 2022 - 79.123.160.167
Internet of Things that process tremendous confidential data have difficulty performing
traditional security algorithms, thus their security is at risk. The security tasks to be added to …

Development and Evaluation of Ensemble Learning Models for Detection of DDOS Attacks in IoT

Y Yılmaz, S Buyrukoğlu - Hittite Journal of Science and Engineering - dergipark.org.tr
Internet of Things that process tremendous confidential data have difficulty performing
traditional security algorithms, thus their security is at risk. The security tasks to be added to …

TOTAL VIEWS

M Abdel-Kader - hillpublisher.com
Introducing a numerical modelling and formulae to predict ballistic limit (perforation velocity
or perforation limit) of concrete barriers strengthened with steel plates and subjected to rigid …

[PDF][PDF] Explainable deep learning for detecting cyber threats

S Mahdavifar - 2021 - unbscholar.lib.unb.ca
Cyber threats have imperiled the security and viability of many entities that exist in this
rapidly evolving data-driven world. In this regard, security specialists are designing new …