• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.8
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• pp.2708-2721
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• 2014

Data outsourcing in the cloud (DOC) is a promising solution for data management at the present time, but it could result in the disclosure of outsourced data to unauthorized users. Therefore, protecting the confidentiality of such data has become a very challenging issue. The conventional way to achieve data confidentiality is to encrypt the data via asymmetric or symmetric encryptions before outsourcing. However, this is computationally inefficient because encryption/decryption operations are time-consuming. In recent years, a few DOC schemes based on secret sharing have emerged due to their low computational complexity. However, Dautrich and Ravishankar pointed out that most of them are insecure against certain kinds of collusion attacks. In this paper, we proposed a novel DOC scheme based on Shamir's secret sharing to overcome the security issues of these schemes. Our scheme can allow an authorized data user to recover all data files in a specified subset at once rather than one file at a time as required by other schemes that are based on secret sharing. Our thorough analyses showed that our proposed scheme is secure and that its performance is satisfactory.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.2
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• pp.826-845
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• 2017

Outsourcing computation is one of the most important applications in cloud computing, and it has a huge ability to satisfy the demand of data centers. Modular exponentiation computation, broadly used in the cryptographic protocols, has been recognized as one of the most time-consuming calculation operations in cryptosystems. Previously, modular exponentiations can be securely outsourced by using two untrusted cloud servers. In this paper, we present two practical and secure outsourcing modular exponentiations schemes that support only one untrusted cloud server. Explicitly, we make the base and the index blind by putting them into a matrix before send to the cloud server. Our schemes provide better performance in higher efficiency and flexible checkability which support single cloud server. Additionally, there exists another advantage of our schemes that the schemes are proved to be secure and effective without any cryptographic assumptions.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.1
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• pp.281-298
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• 2020

Fog computing has become a popular concept in the application of internet of things (IoT). With the superiority in better service providing, the edge cloud has become an attractive solution to IoT networks. The data outsourcing scheme of IoT devices demands privacy protection as well as computation verification since the lightweight devices not only outsource their data but also their computation. Existing solutions mainly deal with the operations over encrypted data, but cannot support the computation verification in the same time. In this paper, we propose a data outsourcing scheme based on an encrypted database system with linear computation as well as efficient query ability, and enhance the interlayer program in the original system with homomorphic message authenticators so that the system could perform computational verifying. The tools we use to construct our scheme have been proven secure and valid. With our scheme, the system could check if the cloud provides the correct service as the system asks. The experiment also shows that our scheme could be as effective as the original version, and the extra load in time is neglectable.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.2
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• pp.1043-1063
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• 2019

With delegating proxy to process data before outsourcing, data owners in restricted access could enjoy flexible and powerful cloud storage service for productivity, but still confront with data integrity breach. Identity-based data auditing as a critical technology, could address this security concern efficiently and eliminate complicated owners' public key certificates management issue. Recently, Yu et al. proposed an Identity-Based Public Auditing for Dynamic Outsourced Data with Proxy Processing (https://doi.org/10.3837/tiis.2017.10.019). It aims to offer identity-based, privacy-preserving and batch auditing for multiple owners' data on different clouds, while allowing proxy processing. In this article, we first demonstrate this scheme is insecure in the sense that malicious cloud could pass integrity auditing without original data. Additionally, clouds and owners are able to recover proxy's private key and thus impersonate it to forge tags for any data. Secondly, we propose an improved scheme with provable security in the random oracle model, to achieve desirable secure identity based privacy-preserving batch public auditing with proxy processing. Thirdly, based on theoretical analysis and performance simulation, our scheme shows better efficiency over existing identity-based auditing scheme with proxy processing on single owner and single cloud effort, which will benefit secure big data storage if extrapolating in real application.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.27 no.4
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• pp.971-980
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• 2017

Data deduplication can be utilized to reduce storage space in cloud storage services by storing only a single copy of data rather than all duplicated copies. Users who are concerned the confidentiality of their outsourced data can use secure encryption algorithms, but it makes data deduplication ineffective. In order to reconcile data deduplication with encryption, Liu et al. proposed a new server-side cross-user deduplication scheme by exploiting password authenticated key exchange (PAKE) protocol in 2015. In this paper, we demonstrate that this scheme has side channel which causes insecurity against the confirmation-of-file (CoF), or duplicate identification attack.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.1
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• pp.145-164
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• 2023

Cloud computing offers a platform that is both adaptable and scalable, making it ideal for outsourcing data for sharing. Various organizations outsource their data on cloud storage servers for availing management and sharing services. When the organizations outsource the data, they lose direct control on the data. This raises the privacy and security concerns. Cryptographic encryption methods can secure the data from the intruders as well as cloud service providers. Data owners may also specify access control policies such that only the users, who satisfy the policies, can access the data. Attribute based access control techniques are more suitable for the cloud environment as they cover large number of users coming from various domains. Multi-authority attribute-based encryption (MA-ABE) technique is one of the propitious attribute based access control technique, which allows data owner to enforce access policies on encrypted data. The main aim of this paper is to comprehensively survey various state-of-the-art MA-ABE schemes to explore different features such as attribute and key management techniques, access policy structure and its expressiveness, revocation of access rights, policy updating techniques, privacy preservation techniques, fast decryption and computation outsourcing, proxy re-encryption etc. Moreover, the paper presents feature-wise comparison of all the pertinent schemes in the field. Finally, some research challenges and directions are summarized that need to be addressed in near future.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.4
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• pp.1892-1903
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• 2016

Mobile social network is becoming more and more popular with respect to the development and popularity of mobile devices and interpersonal sociality. As the amount of social data increases in a great deal and cloud computing techniques become developed, the architecture of mobile social network is evolved into cloud-based that mobile clients send data to the cloud and make data accessible from clients. The data in the cloud should be stored in a secure fashion to protect user privacy and restrict data sharing defined by users. Ciphertext-policy attribute-based encryption (CP-ABE) is currently considered to be a promising security solution for cloud-based mobile social network to encrypt the sensitive data. However, its ciphertext size and decryption time grow linearly with the attribute numbers in the access structure. In order to reduce the computing overhead held by the mobile devices, in this paper we propose a new Outsourcing decryption and Match-then-decrypt CP-ABE algorithm (OM-CP-ABE) which firstly outsources the computation-intensive bilinear pairing operations to a proxy, and secondly performs the decryption test on the attributes set matching access policy in ciphertexts. The experimental performance assessments show the security strength and efficiency of the proposed solution in terms of computation, communication, and storage. Also, our construction is proven to be replayable choosen-ciphertext attacks (RCCA) secure based on the decisional bilinear Diffie-Hellman (DBDH) assumption in the standard model.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.7
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• pp.3375-3400
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• 2018

With the advent of database-as-a-service (DAAS) and cloud computing, more and more data owners are motivated to outsource their data to cloud database in consideration of convenience and cost. However, it has become a challenging work to provide security to database as service model in cloud computing, because adversaries may try to gain access to sensitive data, and curious or malicious administrators may capture and leak data. In order to realize privacy preservation, sensitive data should be encrypted before outsourcing. In this paper, we present a secure and practical system over encrypted cloud data, called QSDB (queryable and secure database), which simultaneously supports SQL query operations. The proposed system can store and process the floating point numbers without compromising the security of data. To balance tradeoff between data privacy protection and query processing efficiency, QSDB utilizes three different encryption models to encrypt data. Our strategy is to process as much queries as possible at the cloud server. Encryption of queries and decryption of encrypted queries results are performed at client. Experiments on the real-world data sets were conducted to demonstrate the efficiency and practicality of the proposed system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.11
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• pp.4226-4241
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• 2014

Cloud storage provides an easy, cost-effective and reliable way of data management for users without the burden of local data storage and maintenance. Whereas, this new paradigm poses many challenges on integrity and privacy of users' data, since users losing grip on their data after outsourcing the data to the cloud server. In order to address these problems, recently, Worku et al. have proposed an efficient privacy-preserving public auditing scheme for cloud storage. However, in this paper, we point out the security flaw existing in the scheme. An adversary, who is on-line and active, is capable of modifying the outsourced data arbitrarily and avoiding the detection by exploiting the security flaw. To fix this security flaw, we further propose a secure and efficient privacy-preserving public auditing scheme, which makes up the security flaw of Worku et al.'s scheme while retaining all the features. Finally, we give a formal security proof and the performance analysis, they show the proposed scheme has much more advantages over the Worku et al.'s scheme.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.8
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• pp.3826-3851
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• 2016

With traditional data storage solutions becoming too expensive and cumbersome to support Big Data processing, enterprises are now starting to outsource their data requirements to third parties, such as cloud service providers. However, this outsourced initiative introduces a number of security and privacy concerns. In this paper, homomorphic encryption is suggested as a mechanism to protect the confidentiality and privacy of outsourced data, while at the same time allowing third parties to perform computation on encrypted data. This paper also discusses the challenges of Big Data processing protection and highlights its differences from traditional data protection. Existing works on homomorphic encryption are technically reviewed and compared in terms of their encryption scheme, homomorphism classification, algorithm design, noise management, and security assumption. Finally, this paper discusses the current implementation, challenges, and future direction towards a practical homomorphic encryption scheme for securing outsourced Big Data computation.