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Cognitive Science-Based Security Framework in Consumer Electronics
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DOI：10.1109/MCE.2019.2941455.png)
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摘要
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There is rapid utilization of social networking services (SNSs) in the consumer electronics (CE) industries for marketing. Unfortunately, with this rise of SNSs use, the traditional SNSs security techniques fail to address the unique security demands of the SNSs, such as the identification of malicious users that can temper the algorithms used to determine the consumer purchasing decisions on SNSs. To handle such security requirements, we propose a cognitive identification framework that relies on the concept of cognitive science to distinguish malicious user from legitimate user on SNSs. The framework takes benefit of social sensing and data processing competency of apache sparks to analyze real-time SNSs data and make identification decision using machine-learning techniques.
Keyword:
Consumer electronics
Real-time systems
Psychology
Security
Sensors
Twitter
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