A Vector Space Model Approach for Web Attack Classification Using Machine Learning Technique

  • B. V. Ram Naresh Yadav
  • B. Satyanarayana
  • D. Vasumathi
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 381)


Web applications usage is increasing in online services in many ways in our day-to-day life. Business service providers have started deploying their business over the web through various e-commerce applications online. The growth of online web application increases the web complexity and vulnerability in terms of security which is a major concern in the current web security research. The extensive growth of various types of web attacks is a severe threat to web security. HTTP requests are usually secret code into a web attack spread through the injection and allow them to perform malicious actions on remote systems to execute arbitrary commands. This paper proposes an efficient approach for web attack classification, using a vector space model approach (VSMA), to improve the detection and classification accuracy. It is able to automatically classify the attacks from valid requests to detect the specific web attacks. The evaluation measure shows high precision and low recall rates than the existing classifiers in comparison.


Web security Vector space model Web attacks Classification Accuracy 


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Copyright information

© Springer India 2016

Authors and Affiliations

  • B. V. Ram Naresh Yadav
    • 1
  • B. Satyanarayana
    • 2
  • D. Vasumathi
    • 3
  1. 1.Department of CSEJNTUH College of EngineeringHyderabadIndia
  2. 2.Department of CSTSri Krishna Devaraya UniversityAnantapurIndia
  3. 3.Department of CSEJNTUH College of EngineeringHyderabadIndia

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