Dishonest Server Research Articles

Perfectly Secure Oblivious Priority Queue

An Oblivious Priority Queue (OPQ) is a cryptographic primitive that enables a client to outsource its data to a dishonest server, and also to securely manage the data according to a priority queue algorithm. Though the first OPQ achieves perfect security, it supports only two operations; Inserting an element and extracting the top-priority element, which are the minimal requirement for a priority queue. In addition, this OPQ allows an adversary to observe operations in progress, which leaks the exact number of elements in the data structure. On the other hand, there are many subsequent works for OPQs that implement additional operations of a priority queue, hide the running operations, and improve efficiency. Though the recent works realize optimal efficiency, all of them achieve only statistical or computational security. Aiming to reconcile perfect security of the first OPQ with all functions (including the operation hiding) supported by recent OPQs, we construct a novel perfectly secure OPQ that can simulate the following operations while hiding which one is in progress; Inserting an element, extracting the top-priority one, deleting an element, and modifying the priority of an element. The efficiency of our scheme is O(log2 N), which is larger than that of the best known statistically secure OPQ but is the same as the known perfectly secure scheme.

Privacy-Preserving and verifiable [formula omitted]-based face recognition with cloud/edge server assistance

In the current cloud computing era, outsourcing overloaded computations to cloud servers has become an increasingly popular computing paradigm. Meanwhile, face recognition (FR), as a typical and extensively deployed biometric authentication technique in the real world, always involves time-consuming large-scale matrix operations or complex optimization problems. Therefore, it is a naturally actual demand to study the cloud/edge server-assisted FR algorithm. Nevertheless, the sensitivity of the FR data and the incredibility of the cloud/edge server make this intriguing computing paradigm suffer from many security challenges. In this paper, we focus on the popular SRC-based FR and, for the first time, present a high-efficiency and secure outsourcing design for this algorithm. The key technique ingredient that emerged in our design is a new norm-preserving matrix transformation which is utilized to outsource the heavy ℓ1-minimization problem in SRC-based FR. This novel technique makes our design well protect the critical privacy information in SRC-based FR and discern the dishonest server with an optimal probability of 1. Simultaneously, compared with existing linear programming outsourcing algorithms, our design is tailored for SRC-based FR and enables the client to gain considerable computational savings without significantly increasing the cloud/edge server’s computational load. Also, we corroborate our theoretical claims by conducting extensive experiments on the publicly available database.

A Secure Multiparty Quantum Homomorphic Encryption Scheme

The significant advantage of the quantum homomorphic encryption scheme is to ensure the perfect security of quantum private data. In this paper, a novel secure multiparty quantum homomorphic encryption scheme is proposed, which can complete arbitrary quantum computation on the private data of multiple clients without decryption by an almost dishonest server. Firstly, each client obtains a secure encryption key through the measurement device independent quantum key distribution protocol and encrypts the private data by using the encryption operator and key. Secondly, with the help of the almost dishonest server, the non-maximally entangled states are pre-shared between the client and the server to correct errors in the homomorphic evaluation of T gates, so as to realize universal quantum circuit evaluation on encrypted data. Thirdly, from the perspective of the application scenario of secure multi-party computation, this work is based on the probabilistic quantum homomorphic encryption scheme, allowing multiple parties to delegate the server to perform the secure homomorphic evaluation. The operation and the permission to access the data performed by the client and the server are clearly pointed out. Finally, a concrete security analysis shows that the proposed multiparty quantum homomorphic encryption scheme can securely resist outside and inside attacks.

Non-interactive verifiable privacy-preserving federated learning

Federated Learning (FL) has received widespread attention for its ability to conduct collaborative learning without collecting raw data. Recently, it has became a reality that more accurate model training is achieved through the large-scale deployment of FL on resource-constrained device, where the communication is expensive and clients dropping out is common, such as mobile phone or IoT devices etc. However, shared local gradients make the privacy of local data in FL vulnerable, and the client is easily deceived by the server for the returned forged results. To solve these problems, the existing schemes either only consider the privacy protection requirements under the communication-limited but not involving verifiability, or consider the privacy-protection and verification separately, which incurs expensive computation and communication costs. It is a challenge to design a lightweight verifiable privacy preserving gradient aggregation scheme for large-scale resource-constrained clients under the communication-limited condition. In this paper, we proposed a non-interactive verifiable privacy-preserving FL based on dual-servers (NIVP-DS) architecture, which improves the efficiency and security of the system and is robust to clients dropping out, based on the constraints that the communication overhead between client and server not more than 2× that of plaintext computation. Based on NIVP-DS, an efficient privacy gradient aggregation scheme is presented by exploiting random matrix coding and secure 2-party computation. The scheme only costs O(M) fully linear operation in the client side under the communication constraints. In order to realize the verifiability, a cross-verification method is introduce, which is based on credible matrix exchange to extend the privacy aggregation scheme to a verifiable scheme. The method only costs little additional overhead, meanwhile, guarantees that one dishonest server cannot forge the aggregate results to deceive the honest client, even if it colludes with multiple clients. The effectiveness of NIVP-DS in practice is corroborated by experiments. The results show that the performance of both secure aggregation and verification are efficiency, and the additional overhead of verification is minimal.

Interactive Verifiable Polynomial Evaluation

Cloud computing platforms have created the possibility for computationally limited users to delegate demanding tasks to strong but untrusted servers. Verifiable computing algorithms help build trust in such interactions by enabling the server to provide a proof of correctness of his results which the user can check very efficiently. In this article, we present a doubly-efficient interactive algorithm for verifiable polynomial evaluation. Unlike the mainstream literature on verifiable computing, the soundness of our algorithm is information-theoretic and cannot be broken by a computationally unbounded server. By relying on basic properties of error correcting codes, our algorithm enforces a dishonest server to provide false results to problems which become progressively easier to verify. After roughly $\log d$ rounds, the user can verify the response of the server against a look-up table that has been pre-computed during an initialization phase. For a polynomial of degree $d$ , we achieve a user complexity of $O(d^{\epsilon })$ , a server complexity of $O(d^{1+\epsilon })$ , a round complexity of $O(\log d)$ and an initialization complexity of $O(d^{1+\epsilon })$ .

Security Properties of Light Clients on the Ethereum Blockchain

Ethereum is a decentralized blockchain, known as being the second most popular public blockchain after Bitcoin. Since Ethereum is decentralised the canonical state is determined by the Ethereum network participants via a consensus mechanism without a centralized coordinator. The network participants are required to evaluate every transaction starting from the genesis block, which requires a large amount of network, computing, and storage resources. This is impractical for many devices with either limited computing resources or intermittent network connectivity. To overcome this drawback Ethereum defines a light client protocol where the light client fetches the blockchain state from a node operating as a light protocol server. Light clients are unable to maintain blockchain state internally, and as a consequence can only perform partial validation on blocks. Thus they rely on the light server for full block validation and to provide the updated blockchain state. Light clients connect to multiple light servers to mitigate the risk of relying on a single potentially dishonest server. Ethereum light clients are known to suffer from a probabilistic security model, but they are widely assumed to be secure under normal operating conditions. In fact, the implicit security assumptions of light clients have not been formally characterised in the literature. We present and analyse the probabilistic security guarantees under three different adversarial scenarios. The results show that for any adversary that is able to manipulate the network, the security assurances provided by the light protocol are severely impacted, and in some cases entirely lost. These results clearly demonstrate that the assumption of normal operating conditions is insufficient to justify the security assumptions of light clients. Our work also provides insight to the security of light clients under different security parameters, allowing light client implementers to more accurately understand the potential security trade-offs.

Survey on Cloud Computing Techniques for Data Integrity Checking

Cloud computing is a term that used instead of internet to describe the infrastructure, software services and storage via internet. Large data centers are available in cloud for remotely store user data. The users have no data control privileges when the data transferred to the Cloud and they are not aware of any security risk. Data can be altered by unauthorized user, threats and dishonest server. Farther more, Data which are either unused for a long a time or takes large memory space can be deleted by cloud service provider. The main issue of cloud computing today is data integrity and how can be maintaining. There for, security challenges users are need to ensure that their data are integral by periodically Data integrity checking. Several integrity checking techniques have been proposed to ensure the data integrity in cloud storage. This paper provides a survey of various data integrity checking techniques for cloud data stored. Objective of this survey focusing on existing integrity check techniques for cloud data storage and presenting their characteristics, benefits, functionality and limitations.

BeeKeeper 2.0: Confidential Blockchain-Enabled IoT System with Fully Homomorphic Computation.

Blockchain-enabled Internet of Things (IoT) systems have received extensive attention from academia and industry. Most previous constructions face the risk of leaking sensitive information since the servers can obtain plaintext data from the devices. To address this issue, in this paper, we propose a decentralized outsourcing computation (DOC) scheme, where the servers can perform fully homomorphic computations on encrypted data from the data owner according to the request of the data owner. In this process, the servers cannot obtain any plaintext data, and dishonest servers can be detected by the data owner. Then, we apply the DOC scheme in the IoT scenario to achieve a confidential blockchain-enabled IoT system, called BeeKeeper 2.0. To the best of our knowledge, this is the first work in which servers of a blockchain-enabled IoT system can perform any-degree homomorphic multiplications and any number of additions on encrypted data from devices according to the requests of the devices without obtaining any plaintext data of the devices. Finally, we provide a detailed performance evaluation for the BeeKeeper 2.0 system by deploying it on Hyperledger Fabric and using Hyperledger Caliper for performance testing. According to our tests, the time consumed between the request stage and recover stage is no more than 3.3 s, which theoretically satisfies the production needs.

Multiparty Delegated Quantum Computing

Quantum computing has seen tremendous progress in the past few years. However, due to limitations in the scalability of quantum technologies, it seems that we are far from constructing universal quantum computers for everyday users. A more feasible solution is the delegation of computation to powerful quantum servers on the network. This solution was proposed in previous studies of blind quantum computation, with guarantees for both the secrecy of the input and of the computation being performed. In this work, we further develop this idea of computing over encrypted data, to propose a multiparty delegated quantum computing protocol in the measurement-based quantum computing framework. We prove the security of the protocol against a dishonest server and against dishonest clients, under the assumption of common classical cryptographic constructions.

Remote data possession checking with enhanced security for cloud storage

Cloud storage allows users to enjoy the on-demand and high quality data storage services without the load of local data maintenance. However, the cloud server providers are not fully trusted. Whether the data over cloud servers are intact becomes a major concern of data owners. To offer cloud users with the capacity of data integrity verification, recently, Chen proposed a remote data possession checking (RDPC) protocol from algebraic signatures which achieves many desirable features such as high efficiency, short length of challenges and responses, non-block verification. Unfortunately, in this paper, we find that the protocol is vulnerable to replay attack and deletion attack launched by a dishonest server. Specifically, the server can deceive the users to believe that their data are well hold by replaying a previous evidence or re-constructing the deleted data blocks from the corresponding tags in the integrity checking process, while their data have been partially discarded in fact. Then, we present an improved scheme to fix the security flaws of the original protocol. Both the theoretical analysis and the implementation results show that the improvement is secure and practical.

Efficient and Verifiable Outsourcing Scheme of Sequence Comparisons

With the rapid development of cloud computing, the techniques for securely outsourcing prohibitively expensive computations are getting widespread attentions in the scientific community. In the outsourcing computation paradigm, the clients with resource-constrained abilities can outsource the heavy computation workloads into the cloud server and enjoy unlimited computing resources in a pay-per-use manner. One of the most critical functionalities in outsourcing computation is the verifiability of the result. That is, the client should efficiently verify the validity of the result returned by the cloud servers. In this paper, we solve the problem of verifiable outsourcing computation of sequence comparisons by integrating the technique of Yao’s garbled circuit with homomorphic encryption. Compared with the existing schemes, our proposed solution enables clients to efficiently detect the misbehavior of dishonest servers. Furthermore, our construction re-garbles the circuit only for malformed responses and th...

Eavesdropping on secure quantum telephone protocol with dishonest server

The crucial issue of quantum communication protocol is its security. In this paper, we show that in secure quantum telephone protocol proposed by Wen et al. [X. Wen et al., Opt. Commun. 275 (2007) 278–282] the dishonest server can obtain full information of the communication with zero risk of being detected.

Economical quantum secure direct communication network with single photons

A scheme for quantum secure direct communication (QSDC) network is proposed with a sequence of polarized single photons. The single photons are prepared originally in the same state |0> by the servers on the network, which will reduce the difficulty for the legitimate users to check eavesdropping largely. The users code the information on the single photons with two unitary operations which do not change their measuring bases. Some decoy photons, which are produced by operating the sample photons with a Hadamard, are used for preventing a potentially dishonest server from eavesdropping the quantum lines freely. This scheme is an economical one as it is the easiest way for QSDC network communication securely.

Quantum secure direct communication network with superdense coding and decoy photons

A quantum secure direct communication network scheme is proposed with quantum superdense coding and decoy photons. The servers on a passive optical network prepare and measure the quantum signal, i.e. a sequence of the d-dimensional Bell states. After confirming the security of the photons received from the receiver, the sender codes his secret message on them directly. For preventing a dishonest server from eavesdropping, some decoy photons prepared by measuring one photon in the Bell states are used to replace some original photons. One of the users on the network can communicate to any other one. This scheme has the advantage of high capacity, and it is more convenient than others as only a sequence of photons is transmitted in quantum line.

Quantum symmetrically-private information retrieval

Private information retrieval systems (PIRs) allow a user to extract an item from a database that is replicated over k⩾1 servers, while satisfying various privacy constraints. We exhibit quantum k-server symmetrically-private information retrieval systems (QSPIRs) that use sublinear communication, do not use shared randomness among the servers, and preserve privacy against honest users and dishonest servers. Classically, SPIRs without shared randomness do not exist at all.

96/01536 Armenia 2 back on line

Cloud storage allows users to enjoy the on-demand and high quality data storage services without the load of local data maintenance. However, the cloud server providers are not fully trusted. Whether the data over cloud servers are intact becomes a major concern of data owners. To offer cloud users with the capacity of data integrity verification, recently, Chen proposed a remote data possession checking (RDPC) protocol from algebraic signatures which achieves many desirable features such as high efficiency, short length of challenges and responses, non-block verification. Unfortunately, in this paper, we find that the protocol is vulnerable to replay attack and deletion attack launched by a dishonest server. Specifically, the server can deceive the users to believe that their data are well hold by replaying a previous evidence or re-constructing the deleted data blocks from the corresponding tags in the integrity checking process, while their data have been partially discarded in fact. Then, we present an improved scheme to fix the security flaws of the original protocol. Both the theoretical analysis and the implementation results show that the improvement is secure and practical.