With the development of Internet of Things (IoT) and 5G, edge computing, as a new computing paradigm, has been widely popularized in academia and industry. Due to the distributed architecture and being close to the us...
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With the development of Internet of Things (IoT) and 5G, edge computing, as a new computing paradigm, has been widely popularized in academia and industry. Due to the distributed architecture and being close to the user, edge computing can faster respond to the IoT device's request and provide a better quality of service for IoT applications. An important application of edge computing is to outsource the complicated computation task to the nearby edge nodes. Modular exponentiation is widely considered as one of the most common and expensive operations in cryptographic protocols. As far as we know, all secure outsourcing algorithms of modular exponentiation are based on the centralized cloud server, but not based on multiple edge nodes. In this article, we propose the first secure and distributed outsourcing algorithm for modular exponentiation (fixed base and variable exponent) under the multiple noncolluding edge node model. In our algorithm, the exponent is divided into a certain number of parts. In addition, we propose another secure and distributed outsourcing algorithm of modular exponentiation (variable base and variable exponent). The user can protect the privacy in the process of outsourcing and detect the invalid results from edge nodes with high probability. Finally, we provide the experimental evaluation to support that our proposed algorithms are efficient on both the user side and the edge node side.
secure computation outsourcing in Internet of Things (IoT) system is an ongoing research challenge, partly due to the resource-constrained nature of most (inexpensive) IoT devices. In this paper, we focus on the secur...
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secure computation outsourcing in Internet of Things (IoT) system is an ongoing research challenge, partly due to the resource-constrained nature of most (inexpensive) IoT devices. In this paper, we focus on the secure outsourcing of bilinear pairings (SOBP) (the most computationally expensive operation in pairing-based cryptographic protocols / algorithms). First, we analyze the limitations in existing SOBP-based schemes, such as the one malicious model (Strong Assumption), a secure channel (Insufficiency), and a trusted server (Centralization). Then, we propose a novel blockchain-based system for SOBP based on a permissioned version (i.e., a blockchain ledger maintained by some permissioned nodes), designed to efficiently address the limitations. Finally, we prove the security of our proposed approach in the one untrusted program model and implement it on Ethereum (an open-source blockchain system) to show its utility. (C) 2018 Elsevier Inc. All rights reserved.
Modular inversion is one of the most basic computations in algorithmic number theory. When it comes to cryptosystems, this computation is very time-consuming since the modulus is generally a large number. It is unreal...
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Modular inversion is one of the most basic computations in algorithmic number theory. When it comes to cryptosystems, this computation is very time-consuming since the modulus is generally a large number. It is unrealistic for some devices with limited computation capability (e.g. mobile devices and IC cards) to conduct such a time-consuming computation. In this paper, we investigate how to securely outsource the inversion modulo a large composite number. Based on the Chinese Remainder Theorem (CRT), we design a secure outsourcing algorithm for inversion modulo a large composite number with two known prime factors for the client. Besides the privacy of the number and its modular inversion, our algorithm also protects the privacy of the modulus. We can verify the correctness of the result with probability 1. Traditionally, the complexity of modular inversion for a l-bit modulus is 0(l(3)). By leveraging the cloud, our algorithm reduces the complexity to 0(l(2)) on the client side. Also, we prove the security of our algorithm based on the one-malicious version of two untrusted program model (one-malicious model). We conduct several experiments to demonstrate the validity and the practicality of our proposed algorithm. In appendix, we show that our proposed algorithm can be extended and applied in the secret key generation of RSA algorithm on the resource-constrained devices. (C) 2017 Elsevier Inc. All rights reserved.
Linear programming(LP) is often used in reality production and life, such as the use of resources, human resource management, production arrangement. The client should pay out huge amounts of overhead to dispose huge ...
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Linear programming(LP) is often used in reality production and life, such as the use of resources, human resource management, production arrangement. The client should pay out huge amounts of overhead to dispose huge data sets with its resource-constraint devices. Fortunately, Cloud computing can finish off this deficiency. The client outsources the computation to cloud servers. Then the servers accomplish the task and return the result to the client. But in the process, the correctness, verifiability and privacy should be emphasized. In our paper, based on the studies and analysis of previous protocols for secure outsourcing of linear programming in cloud computing, we find the obvious deficiencies in efficiency and safety. On the basis of the existing protocols, we propose a new protocol that combines the advantages of existing protocols and improves the shortcomings of existing protocols. We also analyze the security and efficiency of the new protocol and design a suitable simulation to verify the efficiency of this protocol.
The computation of bilinear pairings has been considered the most expensive operation in pairing-based cryptographic protocols. In this paper, we first propose an efficient and secure outsourcing algorithm for bilinea...
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The computation of bilinear pairings has been considered the most expensive operation in pairing-based cryptographic protocols. In this paper, we first propose an efficient and secure outsourcing algorithm for bilinear pairings in the two untrusted program model. Compared with the state-of-the-art algorithm, a distinguishing property of our proposed algorithm is that the (resource-constrained) outsourcer is not required to perform any expensive operations, such as point multiplications or exponentiations. Furthermore, we utilize this algorithm as a subroutine to achieve outsource-secure identity-based encryptions and signatures. (C) 2014 Elsevier B.V. All rights reserved.
With the rapid development in availability of cloud services, the techniques for securely outsourcing the prohibitively expensive computations to untrusted servers are getting more and more attentions in the scientifi...
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With the rapid development in availability of cloud services, the techniques for securely outsourcing the prohibitively expensive computations to untrusted servers are getting more and more attentions in the scientific community. In this paper, we investigate secure outsourcing for large-scale systems of linear equations, which are the most popular problems in various engineering disciplines. For the first time, we utilize the sparse matrix to propose a new secure outsourcing algorithm of large-scale linear equations in the fully malicious model. Compared with the state-of-the-art algorithm, the proposed algorithm only requires (optimal) one round communication (while the algorithm requires L rounds of interactions between the client and cloud server, where L denotes the number of iteration in iterative methods). Furthermore, the client in our algorithm can detect the misbehavior of cloud server with the (optimal) probability 1. Therefore, our proposed algorithm is superior in both efficiency and checkability. We also provide the experimental evaluation that demonstrates the efficiency and effectiveness of our algorithm.
Modular exponentiation with a large modulus, which is usually accomplished by repeated modular multiplications, has been widely used in public key cryptosystems for secure data communications. Hohenberger and Lysyansk...
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ISBN:
(纸本)9781479979042
Modular exponentiation with a large modulus, which is usually accomplished by repeated modular multiplications, has been widely used in public key cryptosystems for secure data communications. Hohenberger and Lysyanskaya [14] proposed the first algorithm for secure outsourcing of modular exponentiations, and then Chen et al. [16] improved the algorithm, which can implement simultaneous modular exponentiations of u(a)(1)u(b)(2). In this paper, we present a secure algorithm for resource-constrained customers, who outsource simulataneous modular exponentiations operation, a task of intensive computation workload, to untrusted servers in the model with one malicious adversary. Based on Chen's algorithm, our algorithm achieves n simultaneous modular exponentiations in outsourcing computation. Compared with [14] and [16], our algorithm is more efficiency.
With the rapid development of cloud services, the techniques for securely outsourcing the prohibitively expensive computations to untrusted servers are getting more and more attention in the scientific community. Expo...
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With the rapid development of cloud services, the techniques for securely outsourcing the prohibitively expensive computations to untrusted servers are getting more and more attention in the scientific community. Exponentiations modulo a large prime have been considered the most expensive operations in discrete-logarithm-based cryptographic protocols, and they may be burdensome for the resource-limited devices such as RFID tags or smartcards. Therefore, it is important to present an efficient method to securely outsource such operations to (untrusted) cloud servers. In this paper, we propose a new secure outsourcing algorithm for (variable-exponent, variable-base) exponentiation modulo a prime in the two untrusted program model. Compared with the state-of-the-art algorithm, the proposed algorithm is superior in both efficiency and checkability. Based on this algorithm, we show how to achieve outsource-secure Cramer-Shoup encryptions and Schnorr signatures. We then propose the first efficient outsource-secure algorithm for simultaneous modular exponentiations. Finally, we provide the experimental evaluation that demonstrates the efficiency and effectiveness of the proposed outsourcing algorithms and schemes.
Linear programming (LP) has been well studied in the scientific community for various engineering applications such as network flow problems, packet routing, portfolio optimization, and financial data management, etc....
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ISBN:
(纸本)9781479936298
Linear programming (LP) has been well studied in the scientific community for various engineering applications such as network flow problems, packet routing, portfolio optimization, and financial data management, etc. In this paper, we first utilize the sparse matrix to investigate secure outsourcing for large-scale LP systems, which is considered as a prohibitively expensive computation for the clients with resource-constraint devices. Besides, we propose a secure and practical scheme which is suitable for any LP problem (feasible, infeasible or unbounded) even in the fully malicious model. Compared with the state-of-the-art algorithm [30], our proposed algorithm only requires O(n(2)) computational overhead instead of O(n(rho)) for 2 < rho <= 3. Furthermore, the client C can detect the misbehavior of cloud server S with the (optimal) probability 1 under the computational complexity of O(n).
Linear programming (LP) has been well studied in the scientific community for various engineering applications such as network flow problems, packet routing, portfolio optimization, and financial data management, etc....
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ISBN:
(纸本)9781479936311
Linear programming (LP) has been well studied in the scientific community for various engineering applications such as network flow problems, packet routing, portfolio optimization, and financial data management, etc. In this paper, we first utilize the sparse matrix to investigate secure outsourcing for large-scale LP systems, which is considered as a prohibitively expensive computation for the clients with resource-constraint devices. Besides, we propose a secure and practical scheme which is suitable for any LP problem (feasible, infeasible or unbounded) even in the fully malicious model. Compared with the state-of-the-art algorithm [30], our proposed algorithm only requires O(n~2) computational overhead instead of O(n~ρ) for 2 < ρ ≤ 3. Furthermore, the client C can detect the misbehavior of cloud server S with the (optimal) probability 1 under the computational complexity of O(n).
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