• DocumentCode
    3100444
  • Title

    SQLI detection system for a safer web application

  • Author

    Pramod, Amith ; Ghosh, Agneev ; Mohan, Amal ; Shrivastava, Mohit ; Shettar, Rajashree

  • Author_Institution
    Dept. of Comput. Sci. & Eng., R.V. Coll. of Eng., Bangalore, India
  • fYear
    2015
  • fDate
    12-13 June 2015
  • Firstpage
    237
  • Lastpage
    240
  • Abstract
    SQL Injection (SQLI) is a quotidian phenomenon in the field of network security. It is a potent and effective way of intruding into secured databases thereby jeopardizing the confidentiality, integrity and availability of information in them. SQL Injection works by inserting malicious queries into legal queries thereby rendering it increasingly arduous for most detection systems to be able to discern its occurrence. Hence, the need of the hour is to build a coherent and a smart SQL Injection detection system to make web applications safer and thus, more reliable. Unlike a great majority of current detection tools and systems that are deployed at a region between the web server and the database server, the proposed system is deployed between client and the web server, thereby shielding the web server from the inimical impacts of the attack. This approach is nascent and efficient in terms of detection, ranking and notification of the attack designed using pattern matching algorithm based on the concept of hashing.
  • Keywords
    Internet; SQL; computer network security; cryptography; file organisation; file servers; pattern matching; SQL Injection; SQLI detection system; Web application; Web server; database security; database server; hashing function; network security; pattern matching algorithm; Algorithm design and analysis; Databases; Inspection; Security; Time factors; Web servers; Deep Packet Inspection; Hardware Network Analyzer; SQL injection attack;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Advance Computing Conference (IACC), 2015 IEEE International
  • Conference_Location
    Banglore
  • Print_ISBN
    978-1-4799-8046-8
  • Type

    conf

  • DOI
    10.1109/IADCC.2015.7154705
  • Filename
    7154705