A Data-Driven and Probabilistic Methodology for Malicious URL Prediction

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ISSN: 2349-6002 ESTD Year: 2014

UGC approved journal no 47859

A Data-Driven and Probabilistic Methodology for Malicious URL Prediction
Author(s):
Sree Sita Kanaka Naga Sai Sree Kandalam, SURYA V, BHAGYA SHREE, ASHITOSH ARUN GUPTA
Keywords:
Cyber Attack, Machine Learning, STM Algorithm, Random Forest, Cybersecurity
Abstract
This paper presents a novel implementation of applying the latest machine learning algorithms to detect a cyber intrusion or cyber-attack in web applications. Cyber Security is an ever-growing field, which with the emerging era of data science, has increased its manifold tenfold. Thus are the implications of data security and applications to detect the attacks on cyber medium. Whomsoever it may be, whether companies, businesses, or authorities from the government, it is essential to formulate an application to detect and prevent user data and information from cyber-attacks. This paper implements the latest growing pace of machine learning to implement the same.
Article Details
Unique Paper ID: 151568 Publication Volume & Issue: Volume 8, Issue 1 Page(s): 279 - 284
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