DETECT AND ASSESS THE CYBERSECURITY THREATS WITH THEIR MITIGATION APPROACHES USING ML ALGORITHM

Registration ID: IJNRD_196440

Published ID: IJNRD2305615

DOI: Click Here to Get

Abhishek Kumar Singh

Cybersecurity is a critical concern for organizations worldwide, as the number and severity of cyber-attacks continue to increase. Malware attacks, phishing attacks, SQL injections, and DDoS attacks are just a few of the methods that hackers use to gain unauthorized access to sensitive data, steal information, and cause damage. According to Cybersecurity Ventures, there were 38,09,448 records stolen from breaches every day since 2013, with 158,727 per hour, 2645 per minute, and 44 per second. Despite the growing threat of cyber-attacks, many organizations are ill-equipped to handle sophisticated attacks. Only 38% of global organizations claim to be prepared to handle such attacks, and an estimated 54% of companies report experiencing one or more attacks in the last 12 months. Additionally, cloud security has become an increasingly important area of concern, with distributed denial-of-service (DDoS) and data privacy being the most common cloud security areas, with a 16% level of use and 14%, respectively. To address these issues, machine learning (ML) techniques have been employed in cybersecurity to detect and prevent cyber-attacks. There are 30 ML techniques used, with some being used in hybrid models and others as standalone models. The most popular ML technique used is the Support Vector Machine (SVM) in both hybrid and standalone models. Additionally, 60% of research papers that use ML techniques compared their models with other models to prove their efficiency, and 13 different evaluation metrics were used. Propose to the development of an ML model to detect various types of cyber threats in data, such as DoS, Probe, R2L, and U2R. This model can significantly improve cybersecurity measures and help prevent data loss, data misuse, and stealing data.

Published Paper   E-Certificate

Abhishek Kumar Singh (May-2023). DETECT AND ASSESS THE CYBERSECURITY THREATS WITH THEIR MITIGATION APPROACHES USING ML ALGORITHM. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 8(5), g134-g138. https://ijnrd.org/papers/IJNRD2305615.pdf

Volume 8 Issue 5, May-2023

Pages : g134-g138

Paper Reg. ID: IJNRD_196440

Published Paper Id: IJNRD2305615

Downloads: 000121991

Research Area: Computer Science & Technology 

Country: Bangalore, Karnataka, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2305615.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2305615

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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