Detecting web application attacks using an intelligent technique / (Record no. 177425)

MARC details
000 -LEADER
fixed length control field 05263namaa22004331i 4500
003 - CONTROL NUMBER IDENTIFIER
control field EG-GICUC
005 - أخر تعامل مع التسجيلة
control field 20260120095400.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 260105s2025 ua a|||frm||| 000 0 eng d
040 ## - CATALOGING SOURCE
Original cataloguing agency EG-GICUC
Language of cataloging eng
Transcribing agency EG-GICUC
Modifying agency EG-GICUC
Description conventions rda
041 0# - LANGUAGE CODE
Language code of text/sound track or separate title eng
Language code of summary or abstract eng
-- ara
049 ## - Acquisition Source
Acquisition Source Deposit
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 005.8
092 ## - LOCALLY ASSIGNED DEWEY CALL NUMBER (OCLC)
Classification number 005.8
Edition number 21
097 ## - Degree
Degree Ph.D
099 ## - LOCAL FREE-TEXT CALL NUMBER (OCLC)
Local Call Number Cai01.20.03.Ph.D.2025.Ah.D
100 0# - MAIN ENTRY--PERSONAL NAME
Authority record control number or standard number Ahmed Anas Hassan Elmenyawy,
Preparation preparation.
245 10 - TITLE STATEMENT
Title Detecting web application attacks using an intelligent technique /
Statement of responsibility, etc. by Ahmed Anas Hassan Elmenyawy ; Supervision Prof. Dr. Salwa Ahmed Saad Ali El-Gamal, Dr. Basheer Abdel Fattah Youssef.
246 15 - VARYING FORM OF TITLE
Title proper/short title كشف هجمات تطبيقات الويب باستخدام تقنية ذكية
264 #0 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE
Date of production, publication, distribution, manufacture, or copyright notice 2025.
300 ## - PHYSICAL DESCRIPTION
Extent 84 Leaves :
Other physical details illustrations ;
Dimensions 30 cm. +
Accompanying material CD.
336 ## - CONTENT TYPE
Content type term text
Source rda content
337 ## - MEDIA TYPE
Media type term Unmediated
Source rdamedia
338 ## - CARRIER TYPE
Carrier type term volume
Source rdacarrier
502 ## - DISSERTATION NOTE
Dissertation note Thesis (Ph.D)-Cairo University, 2025.
504 ## - BIBLIOGRAPHY, ETC. NOTE
Bibliography, etc. note Bibliography: pages 76-84.
520 #3 - SUMMARY, ETC.
Summary, etc. Vertical Broken Access Control (VBAC) vulnerability is one of the most commonly identified<br/>issues in web applications, posing significant risks. Consequently, addressing this pervasive<br/>threat is crucial for ensuring system confidentiality and integrity. A comprehensive survey on<br/>detecting and preventing Broken Access Control attacks has been performed, emphasizing the<br/>importance of this challenge, elaborating on existing solutions, their limitations, and the open<br/>problems that remain. Broken access control attack detector (BACAD) is a novel framework<br/>that leverages advanced AI techniques to neutralize VBAC exploits and attacks in real-time<br/>using a dynamic and practical technique. The detection process consists of two steps. The first<br/>step is user role classification using an advanced Artificial Intelligence (AI) model created in<br/>a learning phase. The learning phase includes BACAD initial configuration and application<br/>user roles traffic generation used for AI model training. The AI model at the core of BACAD<br/>framework analyzes web requests and responses utilizing a robust feature extraction, and<br/>dynamic hyperparameter tuning to ensure optimal performance across diverse scenarios. The<br/>second step is the decision step, which determines whether the incoming request-response pair<br/>is benign or an attack by validating it Vs the BACAD session information set. The evaluation<br/>against a spectrum of real-world and demonstration web applications highlights remarkable<br/>efficiency in detecting VBAC exploits, providing robust application protection against<br/>different sets of VBAC attacks. Furthermore, it shows that BACAD framework addresses the<br/>VBAC problem by presenting an applicable, dynamic, flexible, and technology-independent<br/>solution to counter VBAC vulnerability risks. Thus, BACAD framework contributes<br/>significantly to the ongoing efforts aimed to enhance web application security.
520 #3 - SUMMARY, ETC.
Summary, etc. ثغرة كسر التحكم في الوصول الرأسي (VBAC) تُعد من أكثر الثغرات شيوعًا وخطورة في تطبيقات الويب، مما يجعل معالجتها أمرًا ضروريًا لحماية سرية وسلامة الأنظمة. تم إجراء دراسة شاملة لاستكشاف طرق الكشف عن هذه الهجمات والوقاية منها، مع التركيز على الحلول الحالية ومحدودياتها. وفي هذا السياق، تم ابتكار إطار جديد يُسمى BACAD، يعتمد على تقنيات الذكاء الاصطناعي لاكتشاف هجمات VBAC والتصدي لها في الوقت الفعلي. يتكون BACAD من مرحلتين: الأولى تصنيف دور المستخدم باستخدام نموذج ذكاء اصطناعي مدرّب، والثانية اتخاذ القرار من خلال مقارنة الطلبات مع معلومات الجلسة للتحقق من كونها هجمات أم لا. يتميز BACAD بكفاءته العالية ومرونته، ويُظهر فاعلية في حماية التطبيقات من أنواع متعددة من هجمات VBAC، مما يجعله مساهمة مهمة في تحسين أمان تطبيقات الويب
530 ## - ADDITIONAL PHYSICAL FORM AVAILABLE NOTE
Issues CD Issues also as CD.
546 ## - LANGUAGE NOTE
Text Language Text in English and abstract in Arabic & English.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Computer security
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element أمن الحاسوب
653 #1 - INDEX TERM--UNCONTROLLED
Uncontrolled term Broken Access Control
-- Vertical Access Control Vulnerabilities
-- Vertical Access Control Exploitation
-- Vertical Access Control Attacks
-- Broken Access Control Attack Detector
-- Web Application Security
-- Logical Vulnerabilities
-- Exploit Detection
-- كاشف هجمات كسر التحكم في الوصول
-- ثغرات التحكم الرأسي في الوصول
700 0# - ADDED ENTRY--PERSONAL NAME
Personal name Salwa Ahmed Saad Ali El-Gamal
Relator term thesis advisor.
700 0# - ADDED ENTRY--PERSONAL NAME
Personal name Basheer Abdel Fattah Youssef
Relator term thesis advisor.
900 ## - Thesis Information
Grant date 01-01-2025
Supervisory body Salwa Ahmed Saad Ali El-Gamal
-- Basheer Abdel Fattah Youssef
Universities Cairo University
Faculties Faculty of Computers and Artificial Intelligence
Department Department of Computer Science
905 ## - Cataloger and Reviser Names
Cataloger Name Shimaa
Reviser Names Eman Ghareb
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme Dewey Decimal Classification
Koha item type Thesis
Edition 21
Suppress in OPAC No
Holdings
Source of classification or shelving scheme Home library Current library Date acquired Inventory number Full call number Barcode Date last seen Effective from Koha item type
Dewey Decimal Classification المكتبة المركزبة الجديدة - جامعة القاهرة قاعة الرسائل الجامعية - الدور الاول 05.01.2026 93061 Cai01.20.03.Ph.D.2025.Ah.D 01010110093061000 05.01.2026 05.01.2026 Thesis
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