The inference problem

Author:

Farkas Csilla1,Jajodia Sushil2

Affiliation:

1. University of South Carolina, Columbia, SC

2. George Mason University, Fairfax, VA

Abstract

Access control models protect sensitive data from unauthorized disclosure via direct accesses, however, they fail to prevent indirect accesses. Indirect data disclosure via inference channels occurs when sensitive information can be inferred from non-sensitive data and metadata. Inference channels are often low-bandwidth and complex; nevertheless, detection and removal of inference channels is necessary to guarantee data security. This paper presents a survey of the current and emerging research in data inference control and emphasizes the importance of targeting this so often overlooked problem during database security design.

Publisher

Association for Computing Machinery (ACM)

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1. Empowering Data Federation Security in Polystore Systems;2023 20th ACS/IEEE International Conference on Computer Systems and Applications (AICCSA);2023-12-04

2. Semantic Attack on Disassociated Transaction Data;SN Computer Science;2023-04-20

3. SparkAC: Fine-Grained Access Control in Spark for Secure Data Sharing and Analytics;IEEE Transactions on Dependable and Secure Computing;2023-03-01

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5. Detecting Inference Attacks Involving Raw Sensor Data: A Case Study;Sensors;2022-10-24

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