Security Applications of Machine Learning

A special issue of Algorithms (ISSN 1999-4893).

Deadline for manuscript submissions: closed (31 July 2017) | Viewed by 596

Special Issue Editors

E-Mail Website
Guest Editor
Dipartimento di Informatica, Università degli Studi di Torino, corso Svizzera 185, 10149 Torino, Italy
Interests: security and privacy; identity and access management; machine learning
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
1. DistriNet - KULeuven, Celestijnenlaan 200A B-3001 Heverlee, Belgium
2. Department of Information Engineering and Computer Science (DISI), University of Trento, Via Sommarive 14, I-38123 Povo (TN), Italy
Interests: behavioural biometrics; mobile platforms security and privacy; encrypted queries for cloud; automotive security and privacy

Special Issue Information

Dear Colleagues, 

Machine Learning techniques are increasingly used in the field of Security. They are applied to solve quite different problems, ranging from Malware Detection to Biometric Authentication, from Code Analysis to Network Traffic analysis, and in many privacy-related scenarios. 

Furthermore, the support of Machine Learning algorithms is becoming essential as security problems face an increasing complexity in terms of the amount of data that needs to be analyzed and of the number and diversity of the attacks and vulnerabilities that need to be detected. 

The open access journal Algorithms will host a Special Issue on ``Security Applications of Machine Learning''. The aim of the Special Issue is to offer a forum for exchanging and proposing new ideas and techniques related with the design and usage of Machine Learning techniques and algorithms in Security. 

The following is a (non-exhaustive) list of topics of interest:    

  • machine learning to advance cyber security analytics   
  • deep learning applied to security and privacy   
  • machine learning for malware analysis and classification   
  • machine learning for anomaly detection   
  • biometric authentication   
  • machine learning for discovering vulnerabilities and attacks   
  • machine learning used for large scale security analysis   
  • privacy-preserving machine learning   
  • privacy-preserving classifier learning   
  • machine Learning on Encrypted Data   
  • learning in presence of a Security adversary   

Prof. Dr. Francesco Bergadano
Prof. Dr. Bruno Crispo
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Algorithms is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.


  • anomaly detection 
  • malware detection 
  • biometric authentication 
  • security analytics
  • adversarial learning

Published Papers

There is no accepted submissions to this special issue at this moment.
Back to TopTop