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Introduction

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.

Call for paper

Important date

2017-08-15
Abstract submission deadline

Submission Topics

  • 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

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Important Date
  • Conference Date

    Dec 12

    2017

    to

    Dec 15

    2017

  • Aug 15 2017

    Abstract Submission Deadline

  • Dec 15 2017

    Registration deadline

Sponsored By
广州大学
中南大学