Volume 16 (2024)
Volume 15 (2023)
Volume 14 (2022)
Volume 13 (2021)
Volume 12 (2020)
Volume 11 (2019)
Volume 10 (2018)
Volume 9 (2017)
Volume 8 (2016)
Volume 7 (2015)
Volume 6 (2014)
Volume 5 (2013)
Volume 4 (2012)
Volume 3 (2011)
Volume 2 (2010)
Volume 1 (2009)
A Semi-Supervised IDS for Cyber-Physical Systems Using a Deep Learning Approach

Amirhosein Salehi; Siavash Ahmadi; Mohammad Reza Aref

Volume 15, Issue 3 , October 2023, , Pages 43-50


  Industrial control systems are widely used in industrial sectors and critical infrastructures to monitor and control industrial processes. Recently, the security of industrial control systems has attracted a lot of attention, because these systems are now increasingly interacting with the Internet. Classic ...  Read More

Cross-Device Deep Learning Side-Channel Attacks using Filter and Autoencoder

Maryam Tabaeifard; Ali Jahanian

Volume 15, Issue 3 , October 2023, , Pages 149-158


  Side-channel Analysis (SCA) attacks are effective methods for extracting encryption keys, and with deep learning (DL) techniques, much stronger attacks have been carried out on victim devices. However, carrying out this kind of attack is much more challenging in cross-device attacks when the profiling ...  Read More

Lightweight Identification of Android Malware with Knowledge Distillation and Deep Learning Approach

Somayeh Mozafari; Amir Jalaly Bidgoly

Volume 14, Issue 3 , October 2022, , Pages 81-92


  Today, with the advancement of science and technology, the use of smartphones has become very common, and the Android operating system has been able to gain lots of popularity in the meantime. However, these devices face manysecurity challenges, including malware. Malware may cause many problems in both ...  Read More

Data Enhancement for Date Fruit Classification Using DCGAN

Norah Alajlan; Meshael Alyahya; Noorah Alghasham; Dina M. Ibrahim

Volume 13, Issue 3 , November 2021, , Pages 39-48


  Date fruits are considered essential food and the most important agricultural crop in Saudi Arabia. Where Saudi Arabia produces many of the types of dates per year. Collecting large data for date fruits is a difficult task and consumedtime, besides some of the date types are seasonal. Wherein convolutional ...  Read More

Anomaly-Based Network Intrusion Detection Using Bidirectional Long Short Term Memory and Convolutional Neural Network

Isra Al-Turaiki; Najwa Altwaijry; Abeer Agil; Haya Aljodhi; sara Alharbi; Lina Alqassem

Volume 12, Issue 3 , November 2020, , Pages 37-44


  With present-day technological advancements, the number of devices connected to the Internet has increased dramatically. Cybersecurity attacks are increasingly becoming a threat to individuals and organizations. Contemporary security frameworks incorporate Network Intrusion Detection Systems (NIDS). ...  Read More