Catalic: Delegated PSI Cardinality with Applications to Contact Tracing

Duong, Thai; Phan, Duong Hieu; Trieu, Ni

doi:10.1007/978-3-030-64840-4_29

Cited by 47 publications

(42 citation statements)

References 25 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The comparison is presented in Table 1. The method of evaluation followed is as explained in [9], and outlined briefly here. The Google Apple approach, DP3T, and PACT publicly release tokens of the diagnosed users, and hence they are all vulnerable to the identification of the diagnosed user.…”

Section: Implementation and Evaluationmentioning

confidence: 99%

“…As a result, their PSI‐CA protocol has communication complexity O ( n log N ) which is linear in the size of the smaller set ( n ), and logarithmic in the larger set size N . However, it requires each user to perform O ( n ) exponentiations (public‐key operations) for DH‐based OPRF and O ( N ) symmetric‐key operations for keyword PIR computation. Delegated PSI‐CA [9]: Catalic, a delegated contact tracing system proposed in [9], allows multiple untrusted cloud servers to do the most of contact tracing computation so that the efficiency of the PSI‐CA protocol on the client's device can be improved. A set of non‐colluding cloud servers take the secret shares of the token from the client and jointly perform oblivious distributed key PRF (Odk‐PRF) [9] with a backend server holding a set of tokens from infected patients.…”

Section: Related Workmentioning

confidence: 99%

“…Delegated PSI‐CA [9]: Catalic, a delegated contact tracing system proposed in [9], allows multiple untrusted cloud servers to do the most of contact tracing computation so that the efficiency of the PSI‐CA protocol on the client's device can be improved. A set of non‐colluding cloud servers take the secret shares of the token from the client and jointly perform oblivious distributed key PRF (Odk‐PRF) [9] with a backend server holding a set of tokens from infected patients. In the end, only one cloud server learns the PRF value of the client's token and nothing else.…”

Section: Related Workmentioning

confidence: 99%

See 2 more Smart Citations

Secure contact tracing platform from simplest private set intersection cardinality

Gao

Surana

Trieu

2022

IET Information Security

Self Cite

View full text Add to dashboard Cite

Contact tracing is an essential tool for controlling the spread of disease through human populations. However, existing contact tracing applications are either vulnerable to privacy and security attacks or heavy bandwidth/computational requirements on the client's devices. In this work, we introduce SecureCT, a Secure Contact Tracing platform with strong privacy protection and lightweight cost. SecureCT prevents linkage attacks, eliminates replay and relay attacks, and allows the phone's holder to delegate their contact tracing computation to untrusted servers while maintaining the user's privacy. The technical core of our scheme is an efficient Private Set Intersection Cardinality protocol which only relies on symmetric-key primitives. We evaluate its performance to show the feasibility of our proposed system in practice.

show abstract

Section: Implementation and Evaluationmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

Secure contact tracing platform from simplest private set intersection cardinality

Gao

Surana

Trieu

2022

IET Information Security

Self Cite

View full text Add to dashboard Cite

show abstract

“…In this system, for each contact between two phones, a Diffie-Hellman key exchange between is established and stored on each phone, which makes a high barrier for resource-constrained devices. Finally, the Catalic [35] is presented as a generalization of the Epione system. The main feature of the Catalic protocol is supporting resource-constrained devices that have limited capacities for computation and storage.…”

Section: Privacy In Contact Tracingmentioning

confidence: 99%

Privacy in Advanced Cryptographic Protocols: Prototypical Examples

Phan

Yung

2021

JCC

View full text Add to dashboard Cite

Cryptography is the fundamental cornerstone of cybersecurity employed for achieving data confidentiality, integrity, and authenticity. However, when cryptographic protocols are deployed for emerging applications such as cloud services or big data, the demand for security grows beyond these basic requirements. Data nowadays are being extensively stored in the cloud, users also need to trust the cloud servers/authorities that run powerful applications. Collecting user data, combined with powerful machine learning tools, can come with a huge risk of mass surveillance or undesirable data-driven strategies for making profits rather than for serving the user. Privacy, therefore, becomes more and more important, and new techniques should be developed to protect personal information and to reduce trust requirements on the authorities or the Big Tech providers. In a general sense, privacy is ``the right to be left alone'' and privacy protection allows individuals to have control over how their personal information is collected and used. In this survey, we discuss the privacy protection methods of various cryptographic protocols, in particular we review: - Privacy in electronic voting systems. This may be, perhaps, the most important real-world application where privacy plays a fundamental role. %classical authentication with group, ring signatures, anonymous credentials. - Private computation. This may be the widest domain in the new era of modern technologies with cloud computing and big data, where users delegate the storage of their data and the computation to the cloud. In such a situation, ``how can we preserve privacy?'' is one of the most important questions in cryptography nowadays. - Privacy in contact tracing. This is a typical example of a concrete study on a contemporary scenario where one should deal with the unexpected social problem but needs not pay the cost of weakening the privacy of users. Finally, we will discuss some notions which aim at reinforcing privacy by masking the type of protocol that we execute, we call it the covert cryptographic primitives and protocols.

show abstract

“…However, this method is difficult to directly apply since additional interactions between users are needed to calculate the intersection and the load of client computation is relatively high. Recently, private set intersection cardinality (PSI-CA) protocols for contact tracing has been proposed [ 17 , 34 ]. Another way is to use an MCFE scheme for set intersection.…”

Section: Introductionmentioning

confidence: 99%