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ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
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Impact Factor : 8.14
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| Paper Title: | A Fuzzy approach for DDoS attack detection in Digital Forensics |
| Authors Name: | RESHMA A S |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJRTI_200531
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| Published Paper Id: | IJRTI2501113 |
| Published In: | Volume 10 Issue 1, January-2025 |
| DOI: | http://doi.one/10.1729/Journal.43425 |
| Abstract: | Denial of Service (DoS) attacks are presumed to be severe threats on the web, which aim to hinder the network’s bandwidth, thus disrupting the network operations (Cheema et al., 2022). The DoS attacks involve the operation interruption of a system/network/service. It happens through a single-source attack (Syed et al., 2020). Distributed denial of service attack (DDoS), a sub-category of DoS, is confronted by multiple sources to compromise the network (Agrawal & Vieira, 2013; Mittal et al., 2023). In DDoS attacks, cybercriminals often target firewalls, routers, and links, causing damage to the victim’s defense system either for ransom or personal target (Bawany et al., 2017). This attack often results in enormous losses for the sector involved in online services. In this context, digital forensics, a category of online service, is a practical approach for cyber specialists in gathering digital evidence to uncover fraudulent activities in online media; it is also prone to cyber-attacks. Malicious intruders in this situation often target digital forensic experts’ tools; however, a DoS attack is widespread and tampers with the forensic investigation process. This issue highlights the need for an immediate approach to confront the DoS/DDoS issue posed by cybercriminals (Pandey et al., 2020). DDoS attacks have been in research studies for many decades; nevertheless, intense aftereffects were understood after witnessing the disruption of popular websites Amazon, Spotify, and Twitter in 2016 by DDoS attacks (Twitter, Amazon, Spotify Went down Following Massive DDoS Attack, 2016). This paper proposes to employ fuzzy logic, which can act as a countermeasure with its power to identify malicious packets and, therefore, take proper actions in preventing DDoS attacks (Iyengar et al., 2014). A DoS/DDoS attack is considered the most dangerous among other cyber threats, for which disruption technology like machine learning has been employed in identifying DDoS attacks to guarantee multilayer privacy concerns (Kumari & Mrunalini, 2022). |
| Keywords: | Fuzzy Approach,DDo Attack,Digital Forensics,Network Congestion,Inter-node communication |
| Cite Article: | "A Fuzzy approach for DDoS attack detection in Digital Forensics", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.10, Issue 1, page no.a931-a935, January-2025, Available :http://www.ijrti.org/papers/IJRTI2501113.pdf |
| Downloads: | 000569 |
| ISSN: |
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
| Publication Details: |
Published Paper ID: IJRTI2501113
Registration ID:200531
Published In: Volume 10 Issue 1, January-2025
DOI (Digital Object Identifier): http://doi.one/10.1729/Journal.43425
Page No: a931-a935 Country: Trivandrum, KERALA, India Research Area: Science & Technology Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2501113 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2501113 |
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ISSN: 2456-3315
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