Traceable Inner Product Functional Encryption

Thanh, Xuan; Phan, Duong Hieu; Pointcheval, David

doi:10.1007/978-3-030-40186-3_24

Cited by 11 publications

(9 citation statements)

References 25 publications

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“…The functional decryption key will not only be specific to a function but to a user too, in such a way that if some users collude to produce a pirate decoder that successfully evaluates a function on the plaintext, from the ciphertext only, one can trace back at least one of them. In [81], Do et al propose a traceable IP-FE with black-box confirmation, using the pairing. 8.9.…”

Section: Other Fe Schemesmentioning

confidence: 99%

“…Adding traitor tracing to public-key encryption indeed requires a very high extra cost: even in the bounded model, the cost grows proportionally with the number of traitors. In [78], a new primitive, called Traceable Functional Encryption, is defined: the functional decryption key will not only be specific to a function, but to a user too, in such a way that if some users collude to produce a pirate decoder that successfully evaluates a function on the plaintext, from the ciphertext only, one can trace back at least one of them. In [78], Do et al propose a traceable IP-FE with black-box confirmation, using the pairing.…”

Section: Multi-input Fe Multi-input Functional Encryption (Mi-fementioning

confidence: 99%

See 1 more Smart Citation

A survey on functional encryption

Mascia¹,

Sala²,

Villa³

2023

AMC

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<p style='text-indent:20px;'>Functional Encryption (FE) expands traditional public-key encryption in two different ways: it supports fine-grained access control and allows learning a function of the encrypted data. In this paper, we review all FE classes, describing their functionalities and main characteristics. In particular, we mention several schemes for each class, providing their security assumptions and comparing their properties. To our knowledge, this is the first survey that encompasses the entire FE family.</p>

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Section: Other Fe Schemesmentioning

confidence: 99%

Section: Multi-input Fe Multi-input Functional Encryption (Mi-fementioning

confidence: 99%

A survey on functional encryption

Mascia¹,

Sala²,

Villa³

2023

AMC

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“…Boneh and Franklin [46] introduced the first algebraic traitor tracing scheme, which is also the basis of many follow-up works, including public-key based schemes [47][48][49][50][51][52][53][54][55], identity-based schemes [56][57][58][59][60], and attribute-based schemes [52,54,[61][62][63][64]. In particular, Do et al [65] recently introduced the concept called traceable inner product function encryption, which gives the generalization of the identity-based and attribute-based traitor tracing schemes to support more flexible policies.…”

Section: Traitor Tracingmentioning

confidence: 99%

“…In particular, Do et al. [65] recently introduced the concept called traceable inner product function encryption, which gives the generalization of the identity‐based and attribute‐based traitor tracing schemes to support more flexible policies.…”

Section: Related Workmentioning

confidence: 99%

Quantum‐resistant anonymous identity‐based encryption with trable identities

Liu

Tseng

Tso

et al. 2021

IET Information Security

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Identity-based encryption (IBE), introduced by Shamir, eliminates the need for publickey infrastructure. The sender can simply encrypt a message by using the recipient's identity (such as email or IP address) without needing to look up the public key. In particular, when ciphertexts of an IBE do not reveal recipient's identity, this scheme is known as an anonymous IBE scheme. Recently, Blazy et al. (ARES '19) analysed the trade-off between public safety and unconditional privacy in anonymous IBE and introduced a new notion that incorporates traceability into anonymous IBE, called anonymous IBE with traceable identities (AIBET). However, their construction is based on the discrete logarithm assumption, which is insecure in the quantum era. In this paper, we first formalize the consistency of tracing key of the AIBET scheme to ensure that a ciphertext cannot be traced with the use of wrong tracing keys. Subsequently, we present a generic formulation concept that can be used to transform structure-specific latticebased anonymous IBE schemes into an AIBET. Finally, we apply this concept to Katsumata and Yamada's compact anonymous IBE scheme (Asiacrypt '16) to obtain the first quantum-resistant AIBET scheme that is adaptively secure under the ring learning with errors assumption without random oracle.

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“…The tracing problem becomes critical for this situation. In [33], a new primitive, called Traceable Functional Encryption (TFE), was defined in order to deal with multi-user setting and traceability. By exploiting the similarities between the Boneh and Franklin's traitor tracing scheme [15] and the Abdalla et al's IPFE scheme [6], it was shown how to integrate the Boneh-Franklin tracing technique into the IPFE scheme of Abdalla et al, which allows in particular the personalization of functional decryption keys.…”

Section: Functional Encryption: Moving From Revealing All-or-nothing To Partial Informationmentioning

confidence: 99%

Privacy in Advanced Cryptographic Protocols: Prototypical Examples

Phan

Yung

2021

JCC

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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.

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Traceable Inner Product Functional Encryption

Cited by 11 publications

References 25 publications

A survey on functional encryption

A survey on functional encryption

Quantum‐resistant anonymous identity‐based encryption with trable identities

Privacy in Advanced Cryptographic Protocols: Prototypical Examples

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