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@article{148336,
        author = {Manasee Kurkure},
        title = {Survey on Detecting Port Scan Attempts with Combined Analysis of Support Vector Machine and Deep Learning Algorithms},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {6},
        number = {1},
        pages = {0-0},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=148336},
        abstract = {Compared to the past security of networked systems has become a critical universal issue that influences individuals, enterprises and governments. The rate of attacks against networked systems has increased melodramatically, and the strategies used by the attackers are continuing to evolve. For example, the privacy of  important information, security of stored data platforms, availability of knowledge etc. Depending on these problems, cyber terrorism is one of the most important issues in today’s world. Cyber terror, which caused a lot of problems to individuals and institutions, has reached a level that could threaten public and country security by various groups such as criminal organizations, professional persons and cyber activists. Intrusion detection is one of the solutions against these attacks. A free and effective approach for designing Intrusion Detection Systems (IDS) is Machine Learning. In this study, deep learning and support vector machine (SVM) algorithms were used to detect port scan attempts based on the new CICIDS2017 dataset.},
        keywords = {IDS, SVM, CICIDS2017, Cyber Terror, Deep Learning},
        month = {},
        }