Results 71 to 80 of about 18,797 (191)

Securing the Unseen: A Comprehensive Exploration Review of AI‐Powered Models for Zero‐Day Attack Detection

Expert Systems, Volume 43, Issue 3, March 2026.
ABSTRACT Zero‐day exploits remain challenging to detect because they often appear in unknown distributions of signatures and rules. The article entails a systematic review and cross‐sectional synthesis of four fundamental model families for identifying zero‐day intrusions, namely, convolutional neural networks (CNN), deep neural networks (DNN ...
Abdullah Al Siam, Nuruzzaman Faruqui, Akm Azad, Mohammad Ali Moni   +3 more
wiley   +1 more source

ДОСЛІДЖЕННЯ ЕФЕКТИВНОСТІ БІБЛІОТЕК САНІТИЗАЦІЇ ДЛЯ XSS-АТАК В ВЕБ-ДОДАТКАХ

Кібербезпека: освіта, наука, техніка
Міжсайтові скриптові атаки (Cross-Site Scripting, XSS) залишаються однією з найбільш поширених і критичних уразливостей сучасних веб-додатків, оскільки дозволяють зловмисникам виконувати довільний шкідливий код у браузері користувача, порушуючи ...
Володимир Соколов, Богдан Поліковський, Максим Ворохоб, Олександр Цируль   +3 more
doaj   +1 more source

XSS in eXceSS: A "learn-XSS tool"

, 2007
kishord today presents a tool, called XSS in eXceSS and hosted by .mario that will allow you test attack vectors against a page in different contexts. On top of that it also incorporates PHP IDS, allowing you to skip whichever rules you choose. From kishord's post: Good stuff!
openaire   +2 more sources

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

Graded linearisations

, 2017
When the action of a reductive group on a projective variety has a suitable linearisation, Mumford's geometric invariant theory (GIT) can be used to construct and study an associated quotient variety.
Bérczi, Gergely, Doran, Brent, Kirwan, Frances   +2 more
core   +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

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

SSD: Single Shot MultiBox Detector

, 2016
We present a method for detecting objects in images using a single deep neural network. Our approach, named SSD, discretizes the output space of bounding boxes into a set of default boxes over different aspect ratios and scales per feature map location ...
Anguelov, Dragomir, Berg, Alexander C., Erhan, Dumitru, Fu, Cheng-Yang, Liu, Wei, Reed, Scott, Szegedy, Christian   +6 more
core   +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