Computer Science ›› 2020, Vol. 47 ›› Issue (6A): 352-359.doi: 10.11896/JsJkx.191200054

• Information Security • Previous Articles     Next Articles

SQL InJection Recognition Based on Improved BP Neural Network

ZHU Jun-wen   

  1. East China University of Political Science and Law,Shanghai 201620,China
  • Published:2020-07-07
  • About author:WU Wan-qing, born in 1981, Ph.D, lecturer.His main research interests include information security and quantum-resistant cryptography.
    ZHOU Guo-long, born in 1996, postgraduate.His main research interests include information security and so on.

Abstract: At present,the attack defense system of SQL inJection type is mostly designed from the perspective of static single sentence filtering threat statements.In view of its low inJection statement recognition and high false positives,a double-layer SQL inJection defense model is proposed.After the inJection process is continuous,dynamic modeling analysis is carried out,and BP neural network is introduced for self-learning and self-correction.Experiments show that in the Apache+MySQL environment,this model has a high inJection recognition rate,which has certain advantages for the recognition of SQL inJection.

Key words: Apache+MySQL environment, BP neural network, Data package, double layer defense system, SQL inJection

CLC Number: 

  • TP393
[1] 陈波,于泠,肖军模.计算机系统安全原理与技术.北京:机械工业出版社,2009.
[2] SUI M.Network security situation assessment model based on information fusion [J].Digital Communication World,2019(8):153.
[3] WANG X P.Computer network security analysis modelingbased on deep learning algorithm .Electronic Technology and Software Engineering,2019(16):195-196.
[4] LI X,DUAN Y C.Network security situation assessment methodbased on Improved Hidden Markov model .Computer Science,2020,47(5):1-5.
[5] YE M X.Design and research of SQL inJection vulnerabilityscanning system based on Web .Electronic Design Enginee-ring,2019,27(16):20-23,28.
[6] TIAN Y J,ZHAO Z M,WANG L J,et al.Research on the double layer defense model of SQL inJection attack based on classification .Information Network Security,2015(6):1-6.
[7] LU J Y,XIONG Y S,CHEN W,et al.Cyber security defense model based on spark .Electronic Technology and Software Engineering,2019(17):184-185.
[8] HOU P.SQL inJection attack model based on SGM model .Journal of Anyang Normal University,2019(2):38-43.
[9] KUGU Z Z.Public management paradigm of Japanese super intelligent society .Shanghai Quality,2019(7):25-26.
[10] SUN T T.Characteristics and challenges of intelligent society .Shanghai:Shanghai Academy of Social Sciences,2018.
[11] ZHANG Q Q,YOU J S,GAO Y F.Overview of big data forensics technology .Information Security Research,2017,3(9):795-802.
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