DocumentCode :
726369
Title :
Cloning your mind: Security challenges in cognitive system designs and their solutions
Author :
Beiye Liu ; Chunpeng Wu ; Hai Li ; Yiran Chen ; Qing Wu ; Barnell, Mark ; Qinru Qiu
Author_Institution :
Univ. of Pittsburgh, Pittsburgh, PA, USA
fYear :
2015
fDate :
8-12 June 2015
Firstpage :
1
Lastpage :
5
Abstract :
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.
Keywords :
Big Data; cognition; security of data; Big-Data application; cognitive information processing systems; cognitive system design; data mining; data security; machine learning; sensitive data processing model; Data models; Neural networks; Predictive models; Security; Training; Training data; Cognitive Systems; Machine Learning; Security;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Design Automation Conference (DAC), 2015 52nd ACM/EDAC/IEEE
Conference_Location :
San Francisco, CA
Type :
conf
DOI :
10.1145/2744769.2747915
Filename :
7167279
Link To Document :
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