Semi-Supervised Machine Learning Approach For DDOS Detection

Registration ID: IJNRD_191512

Published ID: IJNRD2304543

DOI: Click Here to Get

D.Dinesh Goud , Mrs. R. Jagadeeswari , A.Yashwanth Reddy , Ch. Bhargava Siva Kumar Reddy , R. Mani Raghavendra

The fast propagation of computer networks has changed the viewpoint of network security. An easy access condition causes computer networks to be susceptible to several threats from hackers. Threats to networks are numerous and potentially devastating. Up until now, researchers have developed intrusion detection systems (IDS) capable of detecting attacks in several available environments. A boundless number of methods for misuse detection as well as anomaly detection have been applied.Many of the technologies proposed are complementary to each other since, for different kinds of environments, some approaches perform better than others. This project presents new intrusion detection systems that are then used to survey and classify them. The taxonomy consists of the detection principle and certain operational aspects of the intrusion detection system. In our project, we have used algorithms like Nave Bayes (NB) and Random Forest (RF). All are measured in terms of accuracy.

Published Paper   E-Certificate

D.Dinesh Goud, Mrs. R. Jagadeeswari, A.Yashwanth Reddy, Ch. Bhargava Siva Kumar Reddy, & R. Mani Raghavendra (April-2023). Semi-Supervised Machine Learning Approach For DDOS Detection. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 8(4), f391-f395. https://ijnrd.org/papers/IJNRD2304543.pdf

Volume 8 Issue 4, April-2023

Pages : f391-f395

Paper Reg. ID: IJNRD_191512

Published Paper Id: IJNRD2304543

Downloads: 000121980

Research Area: Computer Engineering 

Country: Kurnool, Andhra Pradesh, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2304543.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2304543

Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

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