2016 | OriginalPaper | Chapter
1. Introduction
Authors : Wen Ming Liu, Lingyu Wang
Published in: Preserving Privacy Against Side-Channel Leaks
Publisher: Springer International Publishing
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Abstract
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data publishing (e.g., adversarial knowledge about a generalization algorithm may allow adversaries to potentially infer more sensitive information from the disclosed data);
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Web-based Application (e.g., exact user inputs can potentially be inferred from the packet sizes even if the traffic between client and server sides is encrypted);
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smart metering (e.g., the fine-grained meter readings may be used to track the appliance’s usage patterns and consequently sensitive information about the household, such as daily activities or individuals’ habits);
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cloud computing (e.g., the sharing of physical infrastructure among tenants allows adversaries to extract sensitive information about other tenants’ co-resident VMs);
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Android smartphone (e.g., per data-usage statistics and speakers’ status may allow an unauthorized application to obtain the smartphone user’s identity, geo-location, or driving routes);
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VoIP telephony (e.g., users’ conversations can be partially reconstructed from encrypted VoIP packets due to the use of VBR codecs for compression and length-preserving stream ciphers for encryption in VoIP protocols);
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cryptography (e.g., information about the secret key may be retrieved from the physical characteristics of the cryptographic modules during algorithm execution, such as timing, power consumption, and so on).