Lightweight Secure Integer Comparison

We solve the millionaires problem in the semi-trusted model with homomorphic encryption without using intermediate decryptions. This leads to the computationally least expensive solution with homomorphic encryption so far, with a low bandwidth and very low storage complexity. The number of modular multiplications needed is less than the number...

Secure equality testing protocols in the two-party setting

Protocols for securely testing the equality of two encrypted integers are common building blocks for a number of proposals in the literature that aim for privacy preservation. Being used repeatedly in many cryptographic protocols, designing efficient equality testing protocols is important in terms of computation and communication overhead. In...

Secure matching of Dutch car license plates

License plate matching plays an important role in applications like law enforcement, traffic management and road pricing, where the plate is first recognized and then compared to a database of authorized vehicle registration plates. Unfortunately, there are several privacy related issues that should be taken care of before deploying plate...

Secure comparison protocols in the semi-honest model

Due to high complexity, comparison protocols with secret inputs have been a bottleneck in the design of privacy-preserving cryptographic protocols. Different solutions based on homomorphic encryption, garbled circuits and secret sharing techniques have been proposed over the last few years, each claiming high efficiency. Unfortunately, a fair...

Encrypted integer division and secure comparison

When processing data in the encrypted domain, homomorphic encryption can be used to enable linear operations on encrypted data. Integer division of encrypted data however requires an additional protocol between the client and the server and will be relatively expensive. We present new solutions for dividing encrypted data in the semi-honest...

Secure Processing Offload in Recombining Media Segments for Mobile Access

We develop an architecture for a federation of home gateways. We distinguish inner and outer circle friends and describe a mechanism for social-aware backup of content and sharing with friends. To facilitate remote access, content can be segmented and redundantly stored at gateways of friends. We develop innovative solutions that allow secure...

Generating private recommendations efficiently using homomorphic encryption and data packing

Recommender systems have become an important tool for personalization of online services. Generating recommendations in online services depends on privacy-sensitive data collected from the users. Traditional data protection mechanisms focus on access control and secure transmission, which provide security only against malicious third parties,...

Privacy-Preserving Content-Based Recommender System

By offering personalized content to users, recommender systems have become a vital tool in e-commerce and online media applications. Content-based algorithms recommend items or products to users, that are most similar to those previously purchased or consumed. Unfortunately, collecting and storing ratings, on which content-based methods rely,...

Improving the DGK comparison protocol

When processing signals in the encrypted domain, homomorphic encryption can be used to enable linear operations on encrypted data. Comparison of encrypted data however requires an additional protocol between the parties and will be relatively expensive. A well-known and frequently used comparison protocol is by Damgard, Geisler and Kroigaard. We...

Privacy-Preserving Content-Based Recommendations through Homomorphic Encryption

By offering personalized content to users, recommender systems have become a vital tool in ecommerce and online media applications. Content-based algorithms recommend items or products to users, that are most similar to those previously purchased or consumed. Unfortunately, collecting and storing ratings, on which content-based methods rely,...

Generating private recommendations in a social trust network

Recommender systems have become increasingly important in e-commerce as they can guide customers with finding personalized services and products. A variant of recommender systems that generates recommendations from a set of trusted people is recently getting more attention in social networks. However, people are concerned about their privacy as...

Privacy Enhanced Recommender System

Recommender systems are widely used in online applications since they enable personalized service to the users. The underlying collaborative filtering techniques work on user’s data which are mostly privacy sensitive and can be misused by the service provider. To protect the privacy of the users, we propose to encrypt the privacy sensitive data...

Efficiently Computing Private Recommendations

Online recommender systems enable personalized service to users. The underlying collaborative filtering techniques operate on privacy sensitive user data, which could be misused if it is leaked or by the service provider him self. To protect user’s privacy, we propose to encrypt the data and generate recommendations by processing them under...

Processing in the encrypted domain using a composite signal representation: Pros and cons

The current solutions for secure processing in the encrypted domain are usually based on homomorphic cryptosystems operating on very large algebraic structures. Recently, a composite signal representation has been proposed that allows to speed up linear operations on encrypted signals via parallel processing and to reduce the size of the...