SPCSS: Social Network Based Privacy-Preserving Criminal Suspects Sensing | Java | web security | IEEE (Copy)

For more details 7338345250 , skstech.in@gmail.com

Abstract:

With the development of online social networks, many criminal suspects use social networks to communicate with each other. In order to obtain valuable criminal clues, considerable research works have been done to analyze criminal suspects’ social data. However, most of them did not pay much attention to privacy-preserving problems, which may leak some sensitive data in the analysis process. To solve this problem, we propose a novel analysis approach of criminal suspects by exploiting social data and crime data that are collected by social networks and police information systems. We enable the social cloud server and public security cloud server to exchange social information of criminal suspects and users’ public information in a privacy-preserving way. Specifically, we propose a privacy-preserving data retrieving method based on the oblivious transfer to guarantee that only the authorized entities can perform queries on suspects’ social data, while the social cloud server cannot infer anything during the query. Moreover, several building blocks, such as encrypted data comparing, secure classification, and regression tree (CART) model are also proposed. Based on these building blocks, we designed privacy-preserving criminal suspects sensing scheme. Finally, we demonstrate a performance evaluation that shows that our scheme can enhance the analysis of criminal suspects without privacy leakage, while with low overhead.

Technology:

• Java
• JDK
• Web Security
• Cyber Security
• Social Network Security
• MySql

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• Supporting Softwares
• Source Code
• Documentation
• Presentation Slides
• System architecture
• Data Flow Diagram            
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• Execution Procedure
• Database File

Specialization

• Video On Demand *
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