EL-NAHL: Exploring labels autoencoding in augmented hidden layers of feedforward neural networks for cybersecurity in smart grids

T Berghout, M Benbouzid - Reliability Engineering & System Safety, 2022 - Elsevier
Reliability and security of power distribution and data traffic in smart grid (SG) are very
important for industrial control systems (ICS). Indeed, SG cyber-physical connectivity is …

Understanding the influence of AST-JS for improving malicious webpage detection

MF Rozi, S Ozawa, T Ban, S Kim, T Takahashi… - Applied Sciences, 2022 - mdpi.com
JavaScript-based attacks injected into a webpage to perpetrate malicious activities are still
the main problem in web security. Recent works have leveraged advances in artificial …

Detecting Malicious JavaScript Using Structure-Based Analysis of Graph Representation

MF Rozi, T Ban, S Ozawa, A Yamada… - IEEE …, 2023 - ieeexplore.ieee.org
Malicious JavaScript code in web applications poses a significant threat as cyber attackers
exploit it to perform various malicious activities. Detecting these malicious scripts is …

MM-ConvBERT-LMS: detecting malicious Web pages via multi-modal learning and pre-trained model

X Tong, B Jin, J Wang, Y Yang, Q Suo, Y Wu - Applied Sciences, 2023 - mdpi.com
In recent years, the number of malicious web pages has increased dramatically, posing a
great challenge to network security. While current machine learning-based detection …

Multi-Modal Deep Learning for Effective Malicious Webpage Detection.

AE Belfedhal - Revue d'Intelligence Artificielle, 2023 - search.ebscohost.com
The pervasive threat of malicious webpages, which can lead to financial loss, data
breaches, and malware infections, underscores the need for effective detection methods …

LightJD: A Lightweight JavaScript Drive-by Download Detection Framework

T Wang, J Hou, Y He, J Han - 2024 IEEE 2nd International …, 2024 - ieeexplore.ieee.org
The proliferation of web applications has transformed the way individuals interact with
information and services. Concurrently, the rise of the web has led to increased cyber …

Proactive Detection of Malicious Webpages Using Hybrid Natural Language Processing and Ensemble Learning Techniques

A Ali A, R Devi K, SS Ahmed N - Journal of Information and …, 2024 - hrcak.srce.hr
Sažetak The proliferation of malicious webpages presents a growing threat to online
security, necessitating advanced detection methods to mitigate risks. This paper proposes a …

LISP-TBCNN: An AutoCAD Malware Detection Approach

H Chi, Z Fei, P Li, B Yang, Z Wang… - 2022 7th IEEE …, 2022 - ieeexplore.ieee.org
AutoCAD is a famous computer-aided design software widely used by engineers and
designers. AutoCAD relies on AutoLISP scripting language to achieve powerful design …