We invite researchers to contribute original research papers and review articles that will seek high- quality contributions regarding the recent advances in applying machine learning for solving cyberthreat for WSS challenges.

Topics of interest include, but are not limited to ones listed below.

* Deep learning techniques in security and privacy.
* Reinforcement learning in security and privacy
* WSS threat and attack model generation based on machine learning
* Adversarial machine learning in WSS
* Insider threats and countermeasures
* Web semantics security
* Web services-based Biometrics security
* Personal data protection over WSS
* Ethical and legal implications of security and privacy in web services
* Critical infrastructure protection in WSS
* Security and privacy prevention in web services
* WSS privacy policies
* Secure web services development methodologies and modeling
* WSS challenges and future trends

The workshop solicits regular research papers and review papers in the focused areas mentioned above. Papers should be formatted according to Springer’s LNCS Formatting Guidelines. Submissions must be in English and must not exceed 15 pages. Each paper must be submitted on or before the provided deadlines.

The final submission should be formatted according to Springer’s LNCS Camera-ready instructions.