Cloning your mind: Security challenges in cognitive system designs and their solutions

Beiye Liu, Chunpeng Wu, Hai Li, Yiran Chen, Qing Wu, Mark Barnell, Qinru Qiu

Research output: Chapter in Book/Entry/PoemConference contribution

10 Scopus citations


With the booming of big-data applications, cognitive information processing systems that leverage advanced data processing technologies, e.g., machine learning and data mining, are widely used in many industry fields. Although these technologies demonstrate great processing capability and accuracy in the relevant applications, several security and safety challenges are also emerging against these learning based technologies. In this paper, we will first introduce several security concerns in cognitive system designs. Some real examples are then used to demonstrate how the attackers can potentially access the confidential user data, replicate a sensitive data processing model without being granted the access to the details of the model, and obtain some key features of the training data by using the services publically accessible to a normal user. Based on the analysis of these security challenges, we also discuss several possible solutions that can protect the information privacy and security of cognitive systems during different stages of the usage.

Original languageEnglish (US)
Title of host publication2015 52nd ACM/EDAC/IEEE Design Automation Conference, DAC 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781450335201
StatePublished - Jul 24 2015
Event52nd ACM/EDAC/IEEE Design Automation Conference, DAC 2015 - San Francisco, United States
Duration: Jun 8 2015Jun 12 2015

Publication series

NameProceedings - Design Automation Conference
ISSN (Print)0738-100X


Other52nd ACM/EDAC/IEEE Design Automation Conference, DAC 2015
Country/TerritoryUnited States
CitySan Francisco


  • Cognitive Systems
  • Machine Learning
  • Security

ASJC Scopus subject areas

  • Computer Science Applications
  • Control and Systems Engineering
  • Electrical and Electronic Engineering
  • Modeling and Simulation


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