Search your topic in Java2share
Home > Projects
eXTReMe Tracker


Intrusion Detection System over Abnormal Internet Sequence

Abstract:

This paper reports the design principles and evaluation results of a new experimental Intrusion Detection System Over Abnormal Internet Sequence . This Intrusion Detection System combines the advantages of low false-positive rate of signature-based intrusion detection system (IDS) and the ability of anomaly detection system (ADS) to detect novel unknown attacks. By mining anomalous traffic episodes from Internet connections, we build an ADS that detects anomalies beyond the capabilities of signature-based SNORT or Bro systems. A weighted signature generation scheme is developed to integrate ADS with SNORT by extracting signatures from anomalies detected. Intrusion Detection System extracts signatures from the output of ADS and adds them into the SNORT signature database for fast and accurate intrusion detection. By testing our HIDS scheme over real-life Internet trace data mixed with 10 days of Massachusetts Institute of Technology/ Lincoln Laboratory (MIT/LL) attack data set, our experimental results show a 60 percent detection rate of the Intrusion Detection System, compared with 30 percent and 22 percent in using the SNORT and Bro systems, respectively. This sharp increase in detection rate is obtained with less than 3 percent false alarms. The signatures generated by ADS upgrade the SNORT performance by 33 percent.

 The Intrusion Detection System approach proves the vitality of detecting intrusions and anomalies, simultaneously, by automated data mining and  signature generation over Internet connection episodes.


For Explanation/Installation of above project by our expert faculty please register here

  Name:    *
  Mobile No:    *
  E-Mail:    *
  Preferred Time:   
  Preferred Date:   

* Fields are Mandatory