[HTML][HTML] Cyber risk and cybersecurity: a systematic review of data availability

F Cremer, B Sheehan, M Fortmann, AN Kia… - The Geneva papers …, 2022 - ncbi.nlm.nih.gov
Cybercrime is estimated to have cost the global economy just under USD 1 trillion in 2020,
indicating an increase of more than 50% since 2018. With the average cyber insurance …

Deep learning approaches for detecting DDoS attacks: A systematic review

M Mittal, K Kumar, S Behal - Soft computing, 2023 - Springer
In today's world, technology has become an inevitable part of human life. In fact, during the
Covid-19 pandemic, everything from the corporate world to educational institutes has shifted …

Machine learning techniques to detect a DDoS attack in SDN: A systematic review

TE Ali, YW Chong, S Manickam - Applied Sciences, 2023 - mdpi.com
The recent advancements in security approaches have significantly increased the ability to
identify and mitigate any type of threat or attack in any network infrastructure, such as a …

A one-dimensional convolutional neural network (1D-CNN) based deep learning system for network intrusion detection

EUH Qazi, A Almorjan, T Zia - Applied Sciences, 2022 - mdpi.com
The connectivity of devices through the internet plays a remarkable role in our daily lives.
Many network-based applications are utilized in different domains, eg, health care, smart …

Machine-learning-enabled ddos attacks detection in p4 programmable networks

F Musumeci, AC Fidanci, F Paolucci, F Cugini… - Journal of Network and …, 2022 - Springer
Abstract Distributed Denial of Service (DDoS) attacks represent a major concern in modern
Software Defined Networking (SDN), as SDN controllers are sensitive points of failures in …

Intrusion detection system on IoT with 5G network using deep learning

N Yadav, S Pande, A Khamparia… - … and Mobile Computing, 2022 - Wiley Online Library
The Internet of Things (IoT) cyberattacks of fully integrated servers, applications, and
communications networks are increasing at exponential speed. As problems caused by the …

Performance evaluation of deep learning techniques for DoS attacks detection in wireless sensor network

S Salmi, L Oughdir - Journal of Big Data, 2023 - Springer
Wireless sensor networks (WSNs) are increasingly being used for data monitoring and
collection purposes. Typically, they consist of a large number of sensor nodes that are used …

A comprehensive review of vulnerabilities and AI-enabled defense against DDoS attacks for securing cloud services

S Kumar, M Dwivedi, M Kumar, SS Gill - Computer Science Review, 2024 - Elsevier
The advent of cloud computing has made a global impact by providing on-demand services,
elasticity, scalability, and flexibility, hence delivering cost-effective resources to end users in …

An efficient hyperparameter control method for a network intrusion detection system based on proximal policy optimization

H Han, H Kim, Y Kim - Symmetry, 2022 - mdpi.com
The complexity of network intrusion detection systems (IDSs) is increasing due to the
continuous increases in network traffic, various attacks and the ever-changing network …

[PDF][PDF] DDoS attack intrusion detection system based on hybridization of CNN and LSTM

ASA Issa, Z Albayrak - Acta Polytechnica Hungarica, 2023 - researchgate.net
A distributed denial-of-service (DDoS) attack is one of the most pernicious threats to network
security. DDoS attacks are considered one of the most common attacks among all network …