Sökning: "Upptäckt av sårbarheter"

Hittade 3 uppsatser innehållade orden Upptäckt av sårbarheter.

1. 1. Context-aware security testing of Android applications : Detecting exploitable vulnerabilities through Android model-based security testing

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Ivan Baheux; [2023]
   Nyckelord :Android Application Security; Vulnerability Detection; Context-Awareness; Model-Based Security Testing; Domain Specific Language; Sécurité des Applications Android; Détection de Vulnérabilités; Sensibilité au Contexte; Tests de Sécurité Basés sur les Modèles; Langage Dédiés; Android-applikationssäkerhet; Upptäckt av sårbarheter; Kontextmedvetenhet; Modellbaserad säkerhetstestning; Domänspecifikt språk;

   Sammanfattning : This master’s thesis explores ways to uncover and exploit vulnerabilities in Android applications by introducing a novel approach to security testing. The research question focuses on discovering an effective method for detecting vulnerabilities related to the context of an application. LÄS MER

3. 2. KARTAL: Web Application Vulnerability Hunting Using Large Language Models : Novel method for detecting logical vulnerabilities in web applications with finetuned Large Language Models

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Sinan Sakaoglu; [2023]
   Nyckelord :Broken Access Control; Vulnerability; Large Language Models; Web Application; API; Detection; Scanner; DAST; Application Security; Brutet åtkomstkontroll; Sårbarhet; Stora språkmodeller; Webbapplikation; API; Upptäckt; Skanner; DAST; Applikationssäkerhet;

   Sammanfattning : Broken Access Control is the most serious web application security risk as published by Open Worldwide Application Security Project (OWASP). This category has highly complex vulnerabilities such as Broken Object Level Authorization (BOLA) and Exposure of Sensitive Information. LÄS MER

4. 3. The Resilience of Deep Learning Intrusion Detection Systems for Automotive Networks : The effect of adversarial samples and transferability on Deep Learning Intrusion Detection Systems for Controller Area Networks

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Ivo Zenden; [2022]
   Nyckelord :Vehicle Security; Deep Learning; Controller Area Network; Intrusion Detection System; Adversarial Samples; Fordonssäkerhet; Deep Learning; Controller Area Network; Intrusion Detection System; kontradiktoriska prover;

   Sammanfattning : This thesis will cover the topic of cyber security in vehicles. Current vehicles contain many computers which communicate over a controller area network. This network has many vulnerabilities which can be leveraged by attackers. To combat these attackers, intrusion detection systems have been implemented. LÄS MER