The 2017 International Symposium on Big data and machine learning in information security, privacy and anonymity
December 12-15, 2017
Guangzhou, China
In conjunction with SpaCCS 2017
CALL FOR PAPERS
Advances in technology and its proliferation have resulted in an unprecedented data production, usage and storage. Individuals, institutions and cities now have a growing dependency on technology and the data processed to make decisions, provide improved and efficient services. These services have become such a vital part of human existence that the data processed by the technological systems that provide them is now required to be highly secured, i.e. constantly available, have high level of integrity and confidentiality.
Techniques and tools based on big data analytics and machine learning are increasingly been used and relied upon to monitor, detect and provide information security, privacy and anonymity across several individual, business and government applications.
This symposium aims to present the current and latest data security and information security, privacy and anonymity issues addressed by big data analytics, and machine learning techniques and tools.
This provides opportunities for researchers and industry practitioners to present their work at this forum comprising a wide spectrum of advances in big data and machine learning aspects of security, privacy and anonymity of computing systems, communication networks and storage services. Attendees from business and industry may engage with researchers/innovators to take up promising innovations into further development or exploitation.
Of particular interest will be:
- Techniques and algorithms for enhancing the performance of vulnerability assessment tools
- Techniques and tools for the detection of cybercrime and the provisioning of situational awareness.
- Visualization tools that will aid in uncovering hidden patterns of data, identify emerging vulnerabilities and attacks, as well as help in responding decisively with countermeasures that are far more likely to succeed than conventional methods.
- Strategies and methodologies for addressing growing risks in securing data and maintaining privacy
- Latest untraceable exploits along with solutions to stop them.
Proceedings: All accepted papers will be published by Springer LNCS in SpaCCS 2017 Workshops proceedings (indexed by Ei Compendex).
Submission and Publication Information: All papers need to be submitted electronically through the conference website (https://easychair.org/conferences/?conf=spdb2017) using PDF format. Submitted papers must not substantially overlap with papers that have been published or that are simultaneously submitted to a journal or a conference with proceedings. Papers must be clearly presented in English, must not exceed 10 pages in Springer LNCS format (or up to 14 pages with the pages over length charge), including tables, figures, references and appendices. Papers will be selected based on their originality, significance, relevance, and clarity of presentation assessed by at least two reviewers. Submission of a paper should be regarded as a commitment that, should the paper be accepted, at least one of the authors will register and attend the conference to present the work. SPABD-2017 reserves the right to exclude a paper from distribution after the conference (e.g., removal from the digital library and indexing services), if the paper is not presented at the conference.
Organizing Committee:
Vasilis Katos, Bournemouth University
Edward Apeh, Bournemouth University
Neetesh Saxena, Bournemouth University
Alexios Mylonas, Bournemouth University
Programme Committee:
Hongnian Yu, Bournemouth University
Peter Bednar, University of Portsmouth
Huseyin Dogan, Bournemouth University
Paul Yoo, Cranfield University
