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@article{153855,
        author = {Gurpreet Kour Khalsa  and Amit Sharma },
        title = {Intrusion  Detection System Using Anomaly Detection Based on  Outlier   Approach},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {8},
        number = {9},
        pages = {169-176},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=153855},
        abstract = {An Intrusion Detection System (IDS) is a software application that monitors the system or activities of network for malicious activities and generates reports to the management system. The main focus of Intrusion detection systems (IDS) is to identify the possible incidents, logging information about them and to report such attempts. IDS have become an essential addition to the security infrastructure of every organization. The main goal of an intrusion detection system is to detect the attacks efficiently. Furthermore, it is equally important to detect attacks at a beginning stage in order to reduce their impacts. Computer intrusion is unauthorized access to data, computer or internet service. With greater dependency on computers there is a need of prevention and detection of such frauds in order to prevent malicious activities which can hamper the computing resources.   Increase in fraud has resulted in loss of billions of dollars worldwide. In order to detect and prevent frauds several techniques are continually evolved and applied to many systems. This paper proposes intrusion detection system that uses anomaly detection technique based on outlier approach to predict attacks in web applications. The experimental results proved that the proposed approach identifies the anomalies very effectively than any other approaches.},
        keywords = {Fraud detection. Intrusion. Fraud prevention. Anomaly detection.},
        month = {},
        }