Verifiable delegation of computation on outsourced data

Backes, Michael; Fiore, Dario; Reischuk, Raphael M.

doi:10.1145/2508859.2516681

Cited by 161 publications

(143 citation statements)

References 49 publications

(106 reference statements)

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“…The problem of verifiable matrix computation has been studied in recent literature [24,39,4,9]. In addition to computation verification, existing solutions offer other important security features that are: 1) data protection, i.e., protection of both input and output matrices throughout the computation; 2) public verifiability, i.e., the ability of any entity to verify the result of outsourced computation; and 3) deterministic verification, i.e., the ability to detect faulty cells in an output matrix with probability 1.…”

Section: Related Workmentioning

confidence: 99%

“…Note that we treat deterministic verification as a property that is non-trivial to achieve and thus consider only the work of Fiore et al [24] and Backes et al [9]. The construction of [9], however, is based on the scheme of [24] and would offer the same performance as that of [24] in our setting (the advantage of [9] is that it allows for more flexible function specification and scheduling).…”

Section: Related Workmentioning

confidence: 99%

“…The construction of [9], however, is based on the scheme of [24] and would offer the same performance as that of [24] in our setting (the advantage of [9] is that it allows for more flexible function specification and scheduling). Thus, we list only performance of [24] as the representative of both [24] and [9].…”

Section: Related Workmentioning

confidence: 99%

“…That is, corrupting a single cell of the product matrix invalidates the values in all other cells that follow, and verifying the result of the final stage is sufficient in ensuring that the entire task was performed correctly. Other publications (such as [24,9]), on the other hand, require verification of every matrix cell to ensure correctness of the output.…”

Section: Introductionmentioning

confidence: 99%

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Efficient Secure and Verifiable Outsourcing of Matrix Multiplications

Zhang

Blanton

2014

Lecture Notes in Computer Science

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With the emergence of cloud computing services, a resource-constrained client can outsource its computationally-heavy tasks to cloud providers. Because such service providers might not be fully trusted by the client, the need to verify integrity of the returned computation result arises. The ability to do so is called verifiable delegation or verifiable outsourcing. Furthermore, the data used in the computation may be sensitive and it is often desired to protect it from the cloud throughout the computation. In this work, we put forward solutions for verifiable outsourcing of matrix multiplications that favorably compare with the state of the art. Our goal is to minimize the cost of verifying the result without increasing overhead associated with other aspects of the scheme. In our scheme, the cost of verifying the result of computation uses only a single modulo exponentiation and the number of modulo multiplications linear in the size of the output matrix. This cost can be further reduced to avoid all cryptographic operations if the cloud is rational. A rational cloud is neither honest nor arbitrarily malicious, but rather economically motivated with the sole purpose of maximizing its monetary reward. We extend our core constructions with several desired features such as data protection, public verifiability, and computation chaining.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Efficient Secure and Verifiable Outsourcing of Matrix Multiplications

Zhang

Blanton

2014

Lecture Notes in Computer Science

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“…Delegation of data storage and computation to the cloud has become common practice for individuals and big enterprises alike [1,2]. As a result, often the need arises for clients to perform computation on their outsourced private data jointly, ideally without the need to download the data.…”

Section: Introductionmentioning

confidence: 99%

O-PSI: Delegated Private Set Intersection on Outsourced Datasets

Abadi¹,

Terzis²,

Dong³

2015

ICT Systems Security and Privacy Protection

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Abstract. Private set intersection (PSI) has a wide range of applications such as privacy-preserving data mining. With the advent of cloud computing it is now desirable to take advantage of the storage and computation capabilities of the cloud to outsource datasets and delegate PSI computation. In this paper we design O-PSI, a protocol for delegated private set intersection on outsourced datasets based on a novel point-value polynomial representation. Our protocol allows multiple clients to independently prepare and upload their private datasets to a server, and then ask the server to calculate their intersection. The protocol ensures that intersections can only be calculated with the permission of all clients and that datasets and results remain completely confidential from the server. Once datasets are outsourced, the protocol supports an unlimited number of intersections with no need to download them or prepare them again for computation. Our protocol is efficient and has computation and communication costs linear to the cardinality of the datasets. We also provide a formal security analysis of the protocol. IntroductionCloud computing allows clients with limited computation and storage capabilities to outsource their private data and at a later time, ask the cloud to perform computation on them. Delegation of data storage and computation to the cloud has become common practice for individuals and big enterprises alike [1,2]. As a result, often the need arises for clients to perform computation on their outsourced private data jointly, ideally without the need to download the data.In this paper, we consider a particular such scenario, in which the private data take the form of sets and the computation of interest is set intersection, i.e. private set intersection (PSI).In PSI, two parties want to find out the intersection of their sets and also want to prevent the other party from finding out anything more about their own set than the elements of the intersection. In general, PSI captures a wide range of real-world applications such as privacy preserving data mining [3], homeland security [4] and so on. For example, consider a case where a law enforcement agency has a list of suspects and wants to compare it against flight passenger lists. Here the names of the suspects should be kept hidden from the airlines while the agency should not be able to find out about other passengers in order to protect their privacy. As another example, consider the situation where a social welfare organization wants to know whether any of its members receives income from another organization, but neither organization can reveal their list of members.Although a number of protocols have been proposed for PSI (see section 2 for a survey), cloud computing introduces additional challenges as the private datasets are outsourced and the private set intersection is delegated to cloud servers. In addition to keeping their sets confidential, clients are also interested in preventing cloud servers from finding out anything about their sets...

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Towards a secure incremental proxy re‐encryption for e‐healthcare data sharing in mobile cloud computing

Bhatia

Verma

Sharma³

2019

Concurrency and Computation

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Cloud computing provides universal access to a pool of shared resources to numerous stakeholders/shareholders of the e-healthcare industry. The speedy adoption of cloud computing has inevitably raised security concerns for the outsourced data. Since mobile devices are resource constrained, the security solutions must discharge the computing comprehensive operations on the cloud for implementation. Conventionally, any modification to uploaded record would compel the mobile client to encrypt and compute the hash value from scratch. Through this paper, we intend to propose a pairing-free incremental proxy re-encryption scheme, without certificates, which would run proportionate to the number of modifications in time, instead of the document length for improvement in the file modification tasks. The proposed scheme shows a significant improvement in the file modification system regarding the energy consumption and the turnaround timer taken. The proposed scheme has been verified through a formal method using Z 3 solver. KEYWORDScloud computing, e-healthcare, incremental cryptography, mobile Cloud, proxy re-encryption, security INTRODUCTIONThe life-saving efforts in the eleventh hour have often fallen hard back even with advancements in the health care industry and medical services.One of the reasons for such situation is the unavailability of the patient's records that are generally stacked in the piles of paperwork. Firstly, these records are highly ambiguous with multiple gaps in information. Secondly, these records are generally scattered at several heath care centers through the region with different physicians, pharmacies, and hospitals. A number of information systems that contribute to the development of a more complete electronic health record (EHR) are being implemented by the hospitals nowadays to address these problems. Information regarding the patient's health care can be accessed instantly with the help of the electronic systems. An EHR is a centralized source storing medical and treatment history of patients' health information. These valuable patient-centered records can be accessed easily by all the approved healthcare providers (laboratories, specialists, pharmacists, etc).E-health applications generate a lot of data that become difficult for the health care units to store on a single computer because of catastrophic failures. Cloud services thus provide techniques for outsourcing the restrictive expensive computations and data in a secure manner, and this is prevalent in the research community. 1-6 Muhameed et al 7 proposed a ubiquitous health care framework (UbeHealth) encompassing edge computing, Internet of things (IoT), high-performance computing to address the challenges including network latency, deep learning, reliability, big data, bandwidth requirement, rising costs, etc, for satisfying next-generation health care needs.The clients owning resource-constraint mobiles can outsource the heavy computations and massive data onto the suspicious cloud servers and benefit from the unlimited comput...

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Verifiable delegation of computation on outsourced data

Cited by 161 publications

References 49 publications

Efficient Secure and Verifiable Outsourcing of Matrix Multiplications

Efficient Secure and Verifiable Outsourcing of Matrix Multiplications

O-PSI: Delegated Private Set Intersection on Outsourced Datasets

Towards a secure incremental proxy re‐encryption for e‐healthcare data sharing in mobile cloud computing

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