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@article{151568,
        author = {Sree Sita Kanaka Naga Sai Sree Kandalam and SURYA V and BHAGYA SHREE and ASHITOSH ARUN GUPTA},
        title = {A Data-Driven and Probabilistic Methodology for Malicious URL Prediction},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {8},
        number = {1},
        pages = {279-284},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=151568},
        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.},
        keywords = {Cyber Attack, Machine Learning, STM Algorithm, Random Forest, Cybersecurity},
        month = {},
        }