1.
Abbas Acar, Hidayet Aksu, A. Selcuk Uluagac, Mauro Conti
A Survey on Homomorphic Encryption Schemes: Theory and Implementation Journal Article
ACM Computing Surveys, 2018.
Abstract | Links | BibTeX | Tags: Cryptography, Privacy-preserving
@article{Acar2018HomomEncb,
title = {A Survey on Homomorphic Encryption Schemes: Theory and Implementation},
author = {Abbas Acar and Hidayet Aksu and A. Selcuk Uluagac and Mauro Conti},
url = {https://doi.org/10.1145/3214303},
year = {2018},
date = {2018-07-01},
urldate = {2018-07-01},
journal = {ACM Computing Surveys},
publisher = {Association for Computing Machinery (ACM)},
address = {New York, NY, USA},
abstract = {Legacy encryption systems depend on sharing a key (public or private) among the peers involved in exchanging an encrypted message. However, this approach poses privacy concerns. The users or service providers with the key have exclusive rights on the data. Especially with popular cloud services, control over the privacy of the sensitive data is lost. Even when the keys are not shared, the encrypted material is shared with a third party that does not necessarily need to access the content. Moreover, untrusted servers, providers, and cloud operators can keep identifying elements of users long after users end the relationship with the services. Indeed, Homomorphic Encryption (HE), a special kind of encryption scheme, can address these concerns as it allows any third party to operate on the encrypted data without decrypting it in advance. Although this extremely useful feature of the HE scheme has been known for over 30 years, the first plausible and achievable Fully Homomorphic Encryption (FHE) scheme, which allows any computable function to perform on the encrypted data, was introduced by Craig Gentry in 2009. Even though this was a major achievement, different implementations so far demonstrated that FHE still needs to be improved significantly to be practical on every platform. Therefore, this survey focuses on HE and FHE schemes. First, we present the basics of HE and the details of the well-known Partially Homomorphic Encryption (PHE) and Somewhat Homomorphic Encryption (SWHE), which are important pillars for achieving FHE. Then, the main FHE families, which have become the base for the other follow-up FHE schemes, are presented. Furthermore, the implementations and recent improvements in Gentry-type FHE schemes are also surveyed. Finally, further research directions are discussed. This survey is intended to give a clear knowledge and foundation to researchers and practitioners interested in knowing, applying, and extending the state-of-the-art HE, PHE, SWHE, and FHE systems.},
howpublished = {ACM Computing Surveys},
keywords = {Cryptography, Privacy-preserving},
pubstate = {published},
tppubtype = {article}
}
Legacy encryption systems depend on sharing a key (public or private) among the peers involved in exchanging an encrypted message. However, this approach poses privacy concerns. The users or service providers with the key have exclusive rights on the data. Especially with popular cloud services, control over the privacy of the sensitive data is lost. Even when the keys are not shared, the encrypted material is shared with a third party that does not necessarily need to access the content. Moreover, untrusted servers, providers, and cloud operators can keep identifying elements of users long after users end the relationship with the services. Indeed, Homomorphic Encryption (HE), a special kind of encryption scheme, can address these concerns as it allows any third party to operate on the encrypted data without decrypting it in advance. Although this extremely useful feature of the HE scheme has been known for over 30 years, the first plausible and achievable Fully Homomorphic Encryption (FHE) scheme, which allows any computable function to perform on the encrypted data, was introduced by Craig Gentry in 2009. Even though this was a major achievement, different implementations so far demonstrated that FHE still needs to be improved significantly to be practical on every platform. Therefore, this survey focuses on HE and FHE schemes. First, we present the basics of HE and the details of the well-known Partially Homomorphic Encryption (PHE) and Somewhat Homomorphic Encryption (SWHE), which are important pillars for achieving FHE. Then, the main FHE families, which have become the base for the other follow-up FHE schemes, are presented. Furthermore, the implementations and recent improvements in Gentry-type FHE schemes are also surveyed. Finally, further research directions are discussed. This survey is intended to give a clear knowledge and foundation to researchers and practitioners interested in knowing, applying, and extending the state-of-the-art HE, PHE, SWHE, and FHE systems.
2.
Xiaojing Liao, A. Selcuk Uluagac, Raheem A. Beyah
S-MATCH: Verifiable Privacy-Preserving Profile Matching for Mobile Social Services Conference Paper
In the proceedings of the 44th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN), 2014.
Abstract | Links | BibTeX | Tags: Mobile Security , Privacy-preserving, Social Networks Security
@conference{LiaoS-matchIEEE2014,
title = {S-MATCH: Verifiable Privacy-Preserving Profile Matching for Mobile Social Services},
author = {Xiaojing Liao and A. Selcuk Uluagac and Raheem A. Beyah},
url = {https://ieeexplore.ieee.org/abstract/document/6903587/},
year = {2014},
date = {2014-01-01},
urldate = {2014-01-01},
booktitle = {In the proceedings of the 44th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN)},
abstract = {Mobile social services utilize profile matching to help users find friends with similar social attributes (e.g., interests, location, background). However, privacy concerns often hinder users from enabling this functionality. In this paper, we introduce S-MATCH, a novel framework for privacy-preserving profile matching based on property-preserving encryption (PPE). First, we illustrate that PPE should not be considered secure when directly used on social attribute data due to its key-sharing problem and information leakage problem. Then, we address the aforementioned problems of applying PPE to social network data and develop an efficient and verifiable privacy-preserving profile matching scheme. We implement both the client and server portions of S-MATCH and evaluate its performance under three real-world social network datasets. The results show that S-MATCH can achieve at least one order of magnitude better computational performance than the techniques that use homomorphic encryption.},
keywords = {Mobile Security , Privacy-preserving, Social Networks Security},
pubstate = {published},
tppubtype = {conference}
}
Mobile social services utilize profile matching to help users find friends with similar social attributes (e.g., interests, location, background). However, privacy concerns often hinder users from enabling this functionality. In this paper, we introduce S-MATCH, a novel framework for privacy-preserving profile matching based on property-preserving encryption (PPE). First, we illustrate that PPE should not be considered secure when directly used on social attribute data due to its key-sharing problem and information leakage problem. Then, we address the aforementioned problems of applying PPE to social network data and develop an efficient and verifiable privacy-preserving profile matching scheme. We implement both the client and server portions of S-MATCH and evaluate its performance under three real-world social network datasets. The results show that S-MATCH can achieve at least one order of magnitude better computational performance than the techniques that use homomorphic encryption.
3.
Xiaojing Liao, A. Selcuk Uluagac, Raheem A. Beyah
S-Match: An efficient privacy-preserving profile matching scheme Conference Paper
In the proceedings of IEEE Conference on Communications and Network Security (CNS), 2013.
Abstract | Links | BibTeX | Tags: Authentication, Privacy-preserving
@conference{LiaoS-MatchIEEE2013,
title = {S-Match: An efficient privacy-preserving profile matching scheme},
author = {Xiaojing Liao, A. Selcuk Uluagac and Raheem A. Beyah},
url = {https://ieeexplore.ieee.org/abstract/document/6682736},
year = {2013},
date = {2013-01-01},
urldate = {2013-01-01},
booktitle = {In the proceedings of IEEE Conference on Communications and Network Security (CNS)},
abstract = {Profile matching is a fundamental and significant step for mobile social services to build social relationships and share interests. Given the privacy and efficiency concerns of mobile platforms, we propose a cost-effective profile matching technique called S-Match for mobile social services in which matching operations are achieved in a privacy-preserving manner utilizing property-preserving encryption (PPE). Specifically, in this poster, we first analyze the challenges of directly using PPE for profile matching. Second, we introduce a solution based on entropy increase. Our initial results, with three real-world datasets, show that S-Match achieves at least an order of magnitude improvement over other relevant schemes.},
keywords = {Authentication, Privacy-preserving},
pubstate = {published},
tppubtype = {conference}
}
Profile matching is a fundamental and significant step for mobile social services to build social relationships and share interests. Given the privacy and efficiency concerns of mobile platforms, we propose a cost-effective profile matching technique called S-Match for mobile social services in which matching operations are achieved in a privacy-preserving manner utilizing property-preserving encryption (PPE). Specifically, in this poster, we first analyze the challenges of directly using PPE for profile matching. Second, we introduce a solution based on entropy increase. Our initial results, with three real-world datasets, show that S-Match achieves at least an order of magnitude improvement over other relevant schemes.
Citations: 8413
h-index: 44
i10-index: 107
