Volume 8 (2021)
Volume 7 (2020)
Volume 6 (2019)
Volume 5 (2018)
Volume 4 (2017)
Volume 3 (2016)
Volume 2 (2015)
Volume 1 (2014)

Number of Volumes

9

Number of Issues

23

Number of Articles

114

Number of Contributors

231

Article View

93,770

PDF Download

25,563

View Per Article

822.54

PDF Download Per Article

224.24

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Number of Submissions

176

Rejected Submissions

55

Reject Rate

28

Accepted Submissions

107

Acceptance Rate

58

Number of Indexing Databases

9

Number of Reviewers

402

 

Journal of Computing and Security (JCS) is a peer-reviewed scientific journal which is committed to publication of original results in all areas of modern computing as well as information security.

We are pleased to invite you to submit your original English article(s), which is neither previously published nor under consideration for review or publication elsewhere. This journal is following of committee on publication Ethics (cope) and complies with the highest ethical standards in accordance with ethical laws. The notification of the first decision is sent in at most four months period from the date of submission to expedite the publication process.

The published issues are in English and distributed worldwide in open access fashion.  All the received manuscripts, before sending for the reviewing process, will be checked by plagiarism software. Journal of Computing and Security (JCS) uses systems and software similar to turnitin, Grammarly, Hamanandjou, iThenticate, SID, Google Scholar, Google, Magiran, to ensure that articles are not duplicated.

NOTE: Submissions to this journal are free of charge.

Research Article
Proxima: Process Mining for Extracting Configurable Process Models Using Software Product Line Concepts
1. Proxima: Process Mining for Extracting Configurable Process Models Using Software Product Line Concepts

Dina Khodayari Tehraninejad; Sedigheh Khoshnevis

Volume 9, Issue 1 , January 2022, Pages 1-29

http://dx.doi.org/10.22108/jcs.2021.130065.1080

Abstract
  In highly configurable information systems such as SaaS information systems, business process variability management is an important issue. The variability model, which is often called ...  Read More
BAS: An Answer Selection Method Using BERT Language Model
1. BAS: An Answer Selection Method Using BERT Language Model

Jamshid Mozafari; Afsaneh Fatemi; Mohammad Ali Nematbakhsh

Volume 8, Issue 2 , July 2021, , Pages 1-18

http://dx.doi.org/10.22108/jcs.2021.128002.1066

Abstract
  In recent years, Question Answering systems have become more popular and widely used by users. Despite the increasing popularity of these systems, their performance is not even sufficient ...  Read More
Intrusion Detection in IoT With Logistic Regression and Artificial Neural Network: Further Investigations on N-BaIoT Dataset Devices
2. Intrusion Detection in IoT With Logistic Regression and Artificial Neural Network: Further Investigations on N-BaIoT Dataset Devices

Fereshteh Abbasi; Marjan Naderan; Seyyed Enayatallah Alavi

Volume 8, Issue 2 , July 2021, , Pages 27-42

http://dx.doi.org/10.22108/jcs.2021.129807.1077

Abstract
  Due to the increasing development and applications of the Internet of Things (IoT), detection and prevention of intruders into the network and devices has gained much attention in the ...  Read More
Momentum Contrast Self-Supervised Based Training for Adversarial Robustness
3. Momentum Contrast Self-Supervised Based Training for Adversarial Robustness

Monireh Moshavash; Mahdi Eftekhari; Kaveh Bahraman

Volume 8, Issue 1 , January 2021, , Pages 33-43

http://dx.doi.org/10.22108/jcs.2021.126680.1063

Abstract
  By the rapid progress of deep learning and its use in a variety of applications, however, deep networks have shown that they are vulnerable to adversarial examples. Recently developed ...  Read More
Automatic Black-Box Detection of Resistance Against CSRF Vulnerabilities in Web Applications
4. Automatic Black-Box Detection of Resistance Against CSRF Vulnerabilities in Web Applications

Mohammad Ali Hadavi; Samira Sadeghi

Volume 8, Issue 1 , January 2021, , Pages 19-32

http://dx.doi.org/10.22108/jcs.2021.127261.1064

Abstract
  Cross-Site Request Forgery (CSRF) is an attack in which an infected website causes a victim's browser to perform an unwanted operation on a trusted website. The main solution to tackle ...  Read More
Model-Driven Software Engineering: A Bibliometric Analysis
5. Model-Driven Software Engineering: A Bibliometric Analysis

Hamed Barangi; Shekoufeh Kolahdouz Rahimi; Bahman Zamani; Ali Akbar Khasseh

Volume 8, Issue 1 , January 2021, , Pages 93-108

http://dx.doi.org/10.22108/jcs.2021.125400.1059

Abstract
  Model-Driven Software Engineering (MDSE) is a software development methodology that reduces the cost and production time of the final product by concentratingon a higher level of abstraction. ...  Read More

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