Titlebook: Algorithms for Data and Computation Privacy; Alex X. Liu,Rui Li Book 2021 The Editor(s) (if applicable) and The Author(s), under exclusive

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觀點

cogent

Nearest Neighbor Queries over Encrypted Data invertible matrices to encrypt data, is a widely adopted Secure Nearest Neighbor (SNN) query scheme. Encrypting data by matrices is actually a linear combination of the multiple dimensions of the data, which is completely consistent with the relationship between the source signals and observed sign

overrule

K-Nearest Neighbor Queries Over Encrypted Datats near his/her current location. For some small or medium location service providers, they may rely on commercial cloud services, e.g., Dropbox, to store the tremendous geospatial data and deal with a number of user queries. However, it is challenging to achieve a secure and efficient location-base

Arctic

Top-k Queries for Two-Tiered Sensor Networksetween sensors and the sink, could be compromised and allow attackers to learn sensitive data and manipulate query results. Prior schemes on secure query processing are weak because they reveal non-negligible information and therefore, attackers can statistically estimate the data values using domai

設(shè)施

aviator

Privacy Preserving Quantification of Cross-Domain Network Reachabilityes across the network. While quantifying network reachability within one administrative domain is a difficult problem in itself, performing the same computation across a network spanning multiple administrative domains presents a novel challenge. The problem of quantifying network reachability acros

Contend

Cross-Domain Privacy-Preserving Cooperative Firewall Optimizationr to accept or discard the packet based on its policy. Optimizing firewall policies is crucial for improving network performance. Prior work on firewall optimization focuses on either intra-firewall or inter-firewall optimization within one administrative domain where the privacy of firewall policie

江湖郎中

Privacy Preserving String Matching for Cloud Computingata stored on cloud servers. While encryption of data provides sufficient protection, it is challenging to support rich querying functionality, such as ., over the encrypted data. In this work, we present the first ever symmetric key based approach to support privacy preserving string matching in cl

艦旗