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@article{169171,
        author = {Rahul Guha and Manju Vyas and Geerija Lavania and Pankaj Kumar Sharma},
        title = {Investigating the application of Machine Learning algorithms for threat detection and anomaly detection in Network Traffic},
        journal = {International Journal of Innovative Research in Technology},
        year = {2024},
        volume = {11},
        number = {6},
        pages = {402-406},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=169171},
        abstract = {The risk of network breaches and cyberattacks is ongoing in today's interconnected world. As the Internet grows, cyberattacks are evolving quickly, and the state of cyber security is not promising (Sarker, 2021). In order to help detect and avoid these dangers, researchers recognized the challenge and resorted to machine learning techniques. Machine learning methods are ideal for detecting threats in network traffic because of their capacity to examine massive amounts of data and spot trends and anomalies.},
        keywords = {Machine learning, cyber security, network traffic, anomaly detection, and threat detection.},
        month = {November},
        }