Results 41 to 50 of about 5,960 (196)

Application Research of BiLSTM in Cross-Site Scripting Detection

Jisuanji kexue yu tansuo, 2020
At present, machine learning methods are used in the most traditional cross-site scripting (XSS) detection technologies, which have some defects, such as bad readability because of maliciously confused code, insufficient feature extraction and low ...
CHENG Qiqin, WAN Liang
doaj   +1 more source

Automatic generation of content security policy to mitigate cross site scripting [PDF]

, 2016
Content Security Policy (CSP) is powerful client-side security layer that helps in mitigating and detecting wide ranges of web attacks including cross-site scripting (XSS).
Atan, Rodziah, Din, Jamilah, Mhana, Samer Attallah   +2 more
core   +1 more source

Empowering Software Engineers to Design More Secure Web Applications: Guidelines and Potential of Using LLMs as a Recommender Tool

Journal of Software: Evolution and Process, Volume 38, Issue 2, February 2026.
ABSTRACT As software applications get increasingly connected and complex, cybersecurity becomes more and more important to consider during development and evaluation. Software engineers need to be aware of various security threats and the countermeasures that can be taken to mitigate them.
Raffaela Groner, Klara Svensson, Drake Axelrod, Ranim Khojah, Mazen Mohamad, Rebekka Wohlrab   +5 more
wiley   +1 more source

SQLi‐ScanEval: A Framework for Design and Evaluation of SQLi Detection Using Vulnerability and Penetration Testing Scanners

Engineering Reports, Volume 8, Issue 1, January 2026.
This paper proposes SQLi‐ScanEval Framework, a standardized SQLi detection system that integrates vulnerability and penetration testing scanners into a standardized framework. It tested seven prominent SQLi vulnerability scanners including OWASP ZAP, Wapiti, Vega, Acunetix, Invicti, Burp Suite, and Arachni on two prominent vulnerable testing ...
Hajira Bashir, Waseem Ullah Khan, Safdar Nawaz Khan Marwat, Shahid Khan, Imran Baig, Yasir Mehmood, Hammad Atta   +6 more
wiley   +1 more source

Detecting Cross-Site Scripting in Web Applications Using Fuzzy Inference System

Journal of Computer Networks and Communications, 2018
With improvement in computing and technological advancements, web-based applications are now ubiquitous on the Internet. However, these web applications are becoming prone to vulnerabilities which have led to theft of confidential information, data loss,
Bakare K. Ayeni, Junaidu B. Sahalu, Kolawole R. Adeyanju   +2 more
doaj   +1 more source

Dynamic feature selection model for adaptive cross site scripting attack detection using developed multi-agent deep Q learning model

Journal of King Saud University: Computer and Information Sciences, 2023
Web applications’ popularity has raised attention in various service domains, which increased the concern about cyber-attacks. One of these most serious and frequent web application attacks is a Cross-site scripting attack (XSS).
Isam Kareem Thajeel, Khairulmizam Samsudin, Shaiful Jahari Hashim, Fazirulhisyam Hashim   +3 more
doaj   +1 more source

Automated and Explainable Denial of Service Analysis for AI‐Driven Intrusion Detection Systems

IET Information Security, Volume 2026, Issue 1, 2026.
With the increasing frequency and sophistication of distributed denial of service (DDoS) attacks, it has become critical to develop more efficient and interpretable detection methods. Traditional detection systems often struggle with scalability and transparency, hindering real‐time response and understanding of attack vectors. This article presents an
Paul Badu Yakubu, Lesther Santana, Mohamed Rahouti, Yufeng Xin, Abdellah Chehri, Mohammed Aledhari, Jiwei Tian   +6 more
wiley   +1 more source

XSS-GUARD: Precise Dynamic Prevention of Cross-Site Scripting Attacks [PDF]

, 2008
This paper focuses on defense mechanisms for cross-site scripting attacks, the top threat on web applications today. It is believed that input validation (or filtering) can effectively prevent XSS attacks on the server side. In this paper, we discuss several recent real-world XSS attacks and analyze the reasons for the failure of filtering mechanisms ...
Prithvi Bisht, V. N. Venkatakrishnan
openaire   +1 more source

Detection of APTs by Machine Learning: A Performance Comparison

Expert Systems, Volume 43, Issue 1, January 2026.
ABSTRACT Recent advances in machine learning and deep learning have significantly impacted multiple domains, including computer vision, natural language processing and cybersecurity. In the context of increasingly sophisticated Advanced Persistent Threats (APTs), deep learning models have shown strong potential for network intrusion detection by ...
Marcos Luengo Viñuela, Jesús‐Ángel Román‐Gallego, María‐Luisa Pérez‐Delgado, Miguel A. Conde, María‐Concepción Vega‐Hernández, Hernando Silva Varela   +5 more
wiley   +1 more source

Lightweight Deep Learning Approach for Intelligent Intrusion Detection in IoT Networks

International Journal of Distributed Sensor Networks, Volume 2026, Issue 1, 2026.
Intrusion detection system (IDS) is designed to analyze and monitor the network traffic to identify unauthorized access or attacks in an Internet of Things (IoT). IDS assists in protecting IoT devices and networks by recognizing malicious activities and preventing potential breaches.
Srikanth Mudiyanuru Sriramappa, Ananda Babu Jayachandra, Swathi H. Y., Mohammed Jameel, Mohamed Abouhawwash, Francesco Longo   +5 more
wiley   +1 more source