AC-PT : An efficient technique for detecting SQL injection attacks / Randa Osman Morsi ; Supervised Elsayed E. Hemayed , Mona F. Ahmed
Material type: TextLanguage: English Publication details: Cairo : Randa Osman Morsi , 2020Description: 93 P . : charts ; 30cmOther title:- لمقارنه المدخلات AC والخوارزم PT التكن{u٠٦أأ}ك الفعال لالتقاط مھاجمى قواعد الب{u٠٦أأ}انات باستخدام التكن{u٠٦أأ}ك [Added title page title]
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Item type | Current library | Home library | Call number | Copy number | Status | Date due | Barcode | |
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Thesis | قاعة الرسائل الجامعية - الدور الاول | المكتبة المركزبة الجديدة - جامعة القاهرة | Cai01.13.06.M.Sc.2020.Ra.A (Browse shelf(Opens below)) | Not for loan | 01010110083380000 | |||
CD - Rom | مخـــزن الرســائل الجـــامعية - البدروم | المكتبة المركزبة الجديدة - جامعة القاهرة | Cai01.13.06.M.Sc.2020.Ra.A (Browse shelf(Opens below)) | 83380.CD | Not for loan | 01020110083380000 |
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Cai01.13.06.M.Sc.2020.Ma.A Automatic multi-style egyptian license plate detection and classification in high-resolution videos using deep learning methods / | Cai01.13.06.M.Sc.2020.Ma.A Automatic multi-style egyptian license plate detection and classification in high-resolution videos using deep learning methods / | Cai01.13.06.M.Sc.2020.Ra.A AC-PT : An efficient technique for detecting SQL injection attacks / | Cai01.13.06.M.Sc.2020.Ra.A AC-PT : An efficient technique for detecting SQL injection attacks / | Cai01.13.06.M.Sc.2020.Sh.N N-ARY Tree- CNN for Arabic sentiment analysis / | Cai01.13.06.M.Sc.2020.Sh.N N-ARY Tree- CNN for Arabic sentiment analysis / | Cai01.13.06.M.Sc.2021.Ab.C CU-SDAH : a platform for iot hardware security, SW/HW partitioning, extended algorithm hopping and SCA resistance using ZYNQ SOC / |
Thesis (M.Sc.) - Cairo University - Faculty of Engineering - Department of Computer Engineering
SQLIA is one of the most severe threats to the database. In general, the approaches that provide the best guard for the database against SQLIA are those that make use of a mix of primitive approaches as this leads to strengthening their merits and improving their weaknesses. One of the most powerful algorithms, Parsing Tree validation (PT), depends only on accurate detection but takes much time so combining it with a fast-dynamic algorithm with the purpose of learning and storing the malicious input patterns to compare with the next coming inputs will be a great achievement. An algorithm was proposed that is based on the combination of two of the existing detection algorithms: pattern matching algorithm using Aho-Corasick (AC) and PT. The results showed that the proposed approach guarantees high accuracy of 99.9%, reasonable time which was 53.6% of PT's time and less memory usage
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