Timely Detection of DDoS Attacks with Dimenstionality Reduction

Due to the interconnectedness and exponential proliferation of IoT devices, the technology is more susceptible to network attacks like Distributed Denial of Service (DDoS), which disrupt network resources. A growing threat to cloud computing systems is the Distributed Denial of Service (DDoS) attack, in which the attacker starts the attack by taking advantage of computers both inside and outside the cloud system. Real-time analysis of cloud network data is essential for preventing DDoS attacks. DDoS attacks interfere with the operation of Io- connected apps and services by taking advantage of the constrained resources on IoT devices. The impacts of DDoS attacks, which seriously damage current systems, are thoroughly examined in this article in the context of the Internet of Things. One of the most common network attacks is the distributed denial-of-service attack (DDoS). DDoS assaults intensified due to the quick development of computer and communication technologies. Therefore, investigating the detection of a DDoS attack is crucial. A single technique cannot offer adequate security due to the variety of DDoS attack techniques.

Authors

Publication Details

Journal
International Journal of Advanced Research in Science Communication and Technology
Published
2024-11-11
DOI
https://doi.org/10.48175/ijarsct-22158
Citations
1
Primary Topic
Network Security and Intrusion Detection
Type
article
Field-Weighted Citation Impact
0.35
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Timely Detection of DDoS Attacks with Dimenstionality Reduction

M. Sonawane, Miss. Aishwarya Anil Shelke, Miss. Kajal Bhausaheb Pathare, Miss. Ishika Vikas Bagore
1 citations
International Journal of Advanced Research in Science Communication and Technology
Network Security and Intrusion Detection
0.35
article

Timely Detection of DDoS Attacks with Dimenstionality Reduction

M. Sonawane, Miss. Aishwarya Anil Shelke, Miss. Kajal Bhausaheb Pathare, Miss. Ishika Vikas Bagore
article en
1 citations

Abstract

Due to the interconnectedness and exponential proliferation of IoT devices, the technology is more susceptible to network attacks like Distributed Denial of Service (DDoS), which disrupt network resources. A growing threat to cloud computing systems is the Distributed Denial of Service (DDoS) attack, in which the attacker starts the attack by taking advantage of computers both inside and outside the cloud system. Real-time analysis of cloud network data is essential for preventing DDoS attacks. DDoS attacks interfere with the operation of Io- connected apps and services by taking advantage of the constrained resources on IoT devices. The impacts of DDoS attacks, which seriously damage current systems, are thoroughly examined in this article in the context of the Internet of Things. One of the most common network attacks is the distributed denial-of-service attack (DDoS). DDoS assaults intensified due to the quick development of computer and communication technologies. Therefore, investigating the detection of a DDoS attack is crucial. A single technique cannot offer adequate security due to the variety of DDoS attack techniques.

International Journal of Advanced Research in Science Communication and Technology
Openalex Percentile: Top 37%
Network Security and Intrusion Detection
0.35
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Timely Detection of DDoS Attacks with Dimenstionality Reduction — M. Sonawane, Miss. Aishwarya Anil Shelke, et al. · International Journal of Advanced Research in Science Communication and Technology (2024) | TGRS Research Map | TGRS