Private-keyless access, serving as an implementation mechanism within policy-based data custody, enables control and authorization based on predefined policies without requiring users to possess a private key. The unforgeability of both user identity and authorization decisions is ensured by the cryptosystem in private-keyless data custody. Hereby, we introduce a novel Cryptographic Resource Enabled Framework (CREF) to simplify key management, enhance security, and increase flexibility of access authorization. Firstly, in the data custody phase, data resource and its session key are uploaded in ciphertext form to CREF, and the access authorization complies with multiple policies designated by the provider. Secondly, in the dynamic authorization phase, traditional keys or keycards are replaced with adequate one-time attribute credentials issued by multiple authorities. CREF makes dynamically cryptographic policy decision according to the credentials and the cryptographic policy (cryptopolicy). Technically, we design the Credentials-Driven Cryptosystem (CDC) over ideal lattice to build anti-quantum confidence for CREF. In CDC, preimage Gaussian sampler is adopted to sample short vector as real-time attribute credential instead of user's private key. Small policy matrix is implemented to convert monotone policies into optimized cryptopolicies in order to reduce accumulated error. The security analysis confirms that both credentials and cryptopolicies are existentially unforgeable, ensuring the semantic security of the whole CREF. Experimental results indicate CREF has lower storage and computational costs than existing schemes. Meanwhile, with policies' continuous improvements as system evolves, CREF only need to select a suitable policy among multiple candidates to make authorization decisions without having to reencrypt data.

Trading of data is increasingly prevalent as data gain significant economic value, but existing data exchange schemes often suffer from third-party dependency, high verification costs, or inadequate protection of fairness and confidentiality. An efficient decentralized fair exchange scheme for data trading which uses cryptographic commitment scheme and smart contract was proposed in this paper. Our solution guarantees exchange fairness, which requires payments and data to be exchanged correctly between the data buyer and the data seller. First, we design a data verification method with constant verification cost by using polynomial commitments, ensuring that the buyer receives the data matching an agreed-upon commitment. Second, we employ smart contracts to complete the atomic exchange of data and funds, and design a key transmission method by using the properties of bilinear pairings to ensure the confidentiality of trading data. Moreover, our scheme was proved to satisfy the desired security properties: seller fairness, buyer fairness and confidentiality. Simulation results demonstrate the efficiency and practicality of the proposed scheme.

Ciphertext-Policy Attribute-Based Encryption (CP-ABE) is suited for securing electronic health records (EHRs), as it enables fine-grained access control over sensitive medical data while preserving interoperability. However, existing schemes face significant challenges in dynamic user revocation and efficient decryption, including privacy leakage during revocation and difficulties in tracing malicious users. To address these issues, we propose T-DRED, a traceable and dynamic revocation-enabled decryption scheme based on secure aggregation functions. T-DRED employs a secure aggregation function to dynamically insert revoked user identities into a revocation list, enabling selective ciphertext updates and reducing revocation overhead. To preserve privacy, revocation status is verified through membership determination without revealing user identities. To improve decryption efficiency, our scheme innovatively adopts a two-phase decryption process, separating user identity verification from policy verification. In the first phase, lightweight membership verification identifies valid users; in the second phase, attribute-policy matching is performed. Additionally, each user key contains a white-box tracing identifier, allowing the system to trace and revoke malicious users upon key leakage. Revoked users are denied access to both new and historical ciphertexts via list updates, realizing integrated trace-and-revoke functionality. In terms of security, under the standard model and based on theq-BDHE andl-SDH assumptions, the IND-CPA, traceability, and membership verification security of our T-DRED scheme are formally proven. Experimental results show that T-DRED improves encryption and decryption efficiency over existing related schemes.

In this article, our primary focus is on the current lack of privacy-preserving queries tailored to real-number fields rather than integers. We take multisource private data counting on real numbers (R-PDC) within IoT architecture as a breakthrough point to enable diverse query services without revealing sensitive data. The advantage of this is that the parameters required for queries remain stable and minimal in the scenario of wide numerical domain and dynamic changed data set. First, we present a general R-PDC method based on curve approximation, in which an approximate query function (AQF) is established to approximate the constructed ideal counting curve for element queries on target set. We also demonstrate curve construction process of AQF and provide the feasibility theorem of AQF for counting a target element within an allowable error. By integrating the R-PDC method with fixed-point fully homomorphic encryption, an efficient R-PDC scheme is presented to perform multiparty collaborative queries in IoT. In security aspect, the R-PDC scheme on$(m,\epsilon)$-AQF is proved to be statistically secure against chosen element attack (CEA) for cumulative error$\epsilon $and data set size$m$. Moreover, the scheme achieves$O(nm\gamma)$computation and$O(n^{2}m\gamma)$communication complexities for$n$servers and$\gamma $-length fraction. Finally, as an extension of AQF over single attribute, multidimensional R-PDC method is applied into privacy-preserving Naive Bayes classifier and Apriori algorithm over multiple attributes. Our work provides substantial support and insights for the advancement of privacy computation.

To face urgent concern of privacy leakage on mobile crowdsourcing, some Lattice-Based Cryptographic (LBC) schemes have been applied to the cloud-fog-edge data sharing platform for privacy protection. As an important factor of LBC’s security, current key generation usually involves Preimage Gaussian Sampling for Lattice Trapdoor (PGS-LT) to sample short preimage vector from dual lattice. However, there lacks researches on the implementation of PGS-LT according to entities’ computation and storage capacities. To address this issue, we present a fast double-perturbation scheme that is applied to the cloud-fog-edge data sharing platform. Firstly, we design a fast spherical G-lattice sampling algorithm including two samplers: G-perturbation sampler and G-lattice sampler. Among them, the fast non-spherical G-lattice sampling algorithm is extended to arbitrary bases, and deployed on the G-lattice sampler. Meanwhile, the G-perturbation sampler is designed to sample G-perturbation for converting the non-spherical distribution of output G-lattice vector to the spherical one. Secondly, we optimize the assignment of computational tasks in PGS-LT by considering entities’ abilities in the cloud-fog-edge platform. Moreover, we analyze three types of delegated preimage sampling in terms of Gaussian quality and complexity. The analysis and experimental results show that fast spherical G-lattice sampling provides high Gaussian quality of output vector. Meanwhile, in the aspect of complexity, the G-perturbation sampler has lower time & space complexity than the existing works. The G-lattice sampler remains good performance as it only involves extra integer multiplications in linear time complexity.

In the light of the advantages of ring, more and more Lattice-Based Cryptography (LBC) schemes are designed over it to provide small storage cost and high performance. Gaussian Sampler for Lattice Trapdoor (GSLT) plays an important role for these schemes, especially for key extraction. In this paper, we present an efficient GSLT scheme with On-line and Off-line stages. In the On-line stage, we extend the fast non-spherical Gadget-lattice sampling into the ring setting for high performance, and analyze the covariance matrix of output vectors. Subsequently, two optimized perturbation sampling constructions are designed for non-spherical Gadget-lattice sampler to avoid inefficient Cholesky decomposition during Off-line stage. The first construction aims to the spherical Gaussian distribution of preimage vectors, which is beneficial for theoretical analysis. In contrast, the second one is designed on the non-spherical distribution to improve the efficiency of perturbation sampling without leakage of trapdoor in statistic, and we further provide the method how to choose the Gaussian parameters. The complexity analysis and experimental results show that the On-line stage of our scheme has a better performance in comparison with the other works. In the Off-line stage, both of two perturbation sampling constructions can avoid low efficiency of Cholesky decomposition, and are more suitable for the non-spherical G-lattice sampling. In short, our work provides two candidates on either Gaussian parameter or sampling efficiency, thereby offering more options for key generation in LBC schemes.

Blockchain-based smart legal contract, as a legally binding executable contract, has attracted extensive attentions in trade finance. However, since the contract is deployed on open and transparent blockchain network, all transaction data are publicly visible, which brings to privacy disclosure problem. Aiming at this problem, we introduce an improved architecture of smart legal contract with privacy protection, involving contract development, deployment, and execution. In this architecture, the sensitive data of transaction are declared and protected in the form of contract terms. These terms allow the compiler to link predefined cryptographic algorithms into smart contract programs, and then to generate executable contract code. Furthermore, as predefined cryptographic algorithms, we construct a new dual-mode identity-based broadcast encryption (DM-IBBE) scheme to meet specific-purpose or generic-purpose privacy by using selective encryption mode or exclusive encryption mode, respectively. We proved that our DM-IBBE scheme is semantically secure under the decisional Diffie–Hellman assumption. In addition, our experimental results show that the proposed scheme can satisfy the privacy requirements of transaction, and it is practicable and easy-to-develop for introducing privacy preserving mechanisms into smart legal contract languages.

Multisource Private Data Counting (PDC) as a collaborative query service allows different organizations or individuals to combine their data and perform various queries without revealing sensitive information. It is especially crucial for multiple competing institutions, having economic interests and holding sensitive business information. To do it, we first design a practical privacy-preserving query service framework to meet the requirements of data and query privacy, computation fairness, and query flexibility. On this basis, we present a new PDC method over Finite Support Polynomials with Integer Coefficients (PDC-FSP-IC), in which curve fitting method is adopted to generate a query curve for given data set and target set. Especially, the symmetry of curve and Peak-Shift method are introduced to increase the flexibility and applicability for constructing query curves. By integrating PDC-FSP-IC with Multi-Party Fully Homomorphic Encryption (MP-FHE), we further present an efficient PDC scheme to perform collaborative query services on multisource data. This scheme is proved to be statistically secure against chosen element attack for both data privacy and query privacy. Furthermore, the scheme is applied into Private Blacklist-drived Credit Assessment (PBCA) and Privacy-Preserving ID3 (PP-ID3) to preserve data privacy of all participants in joint counting process. The results of performance evaluation demonstrate that our scheme is enough efficient for collaborative query services.

The increasing popularity of remote Cloud File Sharing (CFS) has become a major concern for privacy breach of sensitive data. Aiming at this concern, we present a new resource sharing framework by integrating enterprise-side Attribute-Based Access Control/eXtensible Access Control Markup Language (ABAC/XACML) model, client-side Ciphertext-Policy Attribute-Based Encryption (CP-ABE) scheme, and cloud-side CFS service. Moreover, the framework workflow is provided to support the encrypted-file writing and reading algorithms in accordance with ABAC/XACML-based access policy and attribute credentials. However, an actual problem of realizing this framework is that policy matrix, derived from access policy, seriously affects the performance of existing CP-ABE from Lattice (CP-ABE-L) schemes. To end it, we present an optimal generation algorithm of Small Policy Matrix (SPM), which only consists of small elements, and generates an all-one reconstruction vector. Based on such a matrix, the improved CP-ABE-L scheme is proposed to reduce the cumulative errors to the minimum and prevent the enlargement of error bounds. Furthermore, we give the optimal estimation of system parameters to implement a valid Error Proportion Allocation (EPA). Our experimental results indicate that our scheme has short size of parameters and enjoys efficient computation and storage overloads. Thus, our new framework with optimization methods is conducive to enhancing the security and efficiency of remote work on CFS.

In this article, we address the problem of data privacy in multisource data mining. To do it, we present a new multiparty fully homomorphic encryption (MP-FHE) scheme, in which all participants are completely fair to perform the same computation. At first, the proposed MP-FHE scheme is divided into five stages (i.e., calculation, configuration, recombination, resharing, and reconstruction stage) to achieve the unified computation form of addition and multiplication. Meanwhile, random bivariate polynomials and commutative encryption are used to achieve the degree reduction of polynomials and the continuity of computation. Moreover, we prove that the scheme meets result consistency and program termination under the fail-stop adversary model. Especially, three kinds of error detection criteria are presented to find errors in three different stages (i.e., recombination, resharing, and reconstruction stage), which provides the monitor basis for the fail-stop adversary model. In addition, the MP-FHE scheme is applied into privacy preserving k-means clustering algorithm. Finally, we evaluate the computation and communication performance of our scheme from both theoretical and experimental aspects, and the evaluation results show that the scheme is efficient enough for multisource data mining.

Usage-based pricing or Pay-as-You-Go is a relatively new SaaS business model that may provide customers the option to pay for only what they use. Yet, it is more challenging to implement than traditional Pay-before-Use subscriptions considering that it need not only realize financial payment on consumption-based behaviors, but also regulate the rights and obligations among the providers, consumers, and platforms in a legal form. To address these challenges, in this article Smart Legal Contract (SLC) is integrated into a service computing platform by introducing a new architecture, called Service as a Smart Contract (SaaSC). On the aspect of service legalization, through combining SaaS and SaaSC, we establish three kinds of terms in SLC-based software subscription contract to support service's registration, discovery and customization, so that a complete transaction procedure can be regulated in terms of service states, transaction process, and interactions among contracting parties. On the aspect of service financialization, we propose a new scheme of service interface declaration in the SLC-based SPESC contract. By automatically executing smart contracts and checking the terms, the pay-as-you-go billing form can be made fine-grained payment after using service interface calls. Moreover, we take weather forecast service as a case to implement and analyze the acquisition, delivery, and contractual payment of software service on Blockchain smart contract. The experimental results demonstrate the feasibility and effectiveness of the proposed SaaS+SaaSC architecture so that it provides a practicable approach for contractual software service.

The decentralization mechanism provides manufacturers and distributors with greater customization and flexibility they need through Internet of Things (IoT)-based industrial collaboration systems (IoT-ICS), but it has brought forward security concerns about the shared data-processing tasks and IoT-based access to services and resources. To address them, we propose a practical blockchain solution to achieve decentralized policy management and evaluation on attribute-based access control (ABAC). By offloading the responsibility of ABAC policy administration and decision making to blockchain nodes, a blockchain-based access control framework, called Policychain, is presented to ensure policy with high availability, autonomy, and traceability. To deliver a solid design, we first present a transaction-oriented policy expression scheme with a well-defined syntax and semantics. The scheme can translate ABAC policies into the blockchain transactions with JavaScript object notation (JSON) syntax and script-based logical expression. We further realize a script-driven policy evaluation by extending blockchain inherent scripting instructions to support attribute acquisition of ABAC entities. Furthermore, we propose a policy lifecycle management scheme from policy creation, renovation, to revocation, in which policies are verified by three validation principles at the transaction level. Finally, we provide sophisticated analysis and experiments to show that our framework is secure and practical for decentralized policy management on ABAC in IoT-ICS.

In this article, we address the problem of secure sensitive data sharing for the specified recipients in Blockchain Internet of Things (BIoT). To do it, we present a cryptographic solution to meet the requirements of decentralization and convenience through key management and programmable ciphertext. First, we design a new ciphertext-policy decentralized-key attribute-based encryption (CP-DK-ABE) scheme. After the master secret key is shared into all full nodes in the form of threshold secret sharing, a decentralized multiparty computation protocol is used to generate the user’s private key in an interactive way. Meanwhile, the attribute subkeys associated with the private key can be reconstructed by obtaining a fragment from each of full nodes, so as to achieve the cooperative management of attribute key through all of full nodes. Furthermore, following the blockchain’s script system, we introduce five new opcodes to represent ciphertext in the programmable format. Such a mechanism provides flexible capability to represent the logical relationship of the access control policy among attribute subciphers in the CP-DK-ABE ciphertext by the scripting language. As a result, the processes of encryption and decryption are implemented entirely by the script interpreter on the blockchain node, thereby greatly improving the convenience of programming in BIoT devices. In addition, we prove that the proposed CP-DK-ABE scheme is key private and semantically secure for a limited number of corrupted full nodes under the decisional linear and bilinear Diffie–Hellman assumption, respectively.

In recent years, advanced smart contract languages (ASCLs) have been proposed to solve the problem of difficult reading, comprehension, and collaboration when writing smart legal contracts among people in different fields. However, this kind of languages are still hard to put into practice due to the lack of an effective conversion method from the ASCLs to executable smart contract programs. Aiming at this problem, we take SPESC as example to explore how to design conversion rules from the contract in it to the target programming language in Solidity, and to propose a three-layer smart contract framework, including advanced smart-contract layer, general smart-contract layer, and executable machine-code layer. These rules provide an approach to convert the definition of SPESC contracting parties into party-contracts on target language, as well as to produce SPESC contract terms into main-contract on target language. Moreover, the proposed framework specifies not only program architecture and storage structure on general smart-contract layer, but also important mechanisms, including personnel management, timing control, exception handling, etc., which can assist programmers to write smart contract programs. Furthermore, taking four SPESC contracts as testing objects, we provide the whole process of converting from SPESC contracts to Solidity programs by the SPESC-Translator, and verify the efficiency and security of the conversion process, including coding, deploying, running, and testing through Ethereum. The instance results show that the conversion rules and the three-layer framework can simplify the writing of smart contracts, standardize the program structure, and help programmers to verify the correctness of the contract programs.

Smart contract is a set of digital executable protocols intended to make contractual clauses partially or fully self-executing, self-enforcing, or both. As the second-generation blockchain technology, smart contracts have greatly enriched the functional expression of blockchain to make application development more convenient. All related data of smart contracts, including program codes, intermediate states, and executed results, will be stored in blockchain to ensure that these data are not tampered with. Also, the consensus protocols of blockchain verify the correctness of the running process by executing the smart contract with the same input at all nodes. Therefore, the blockchain’s security mechanism with tamper-proof and traceable makes it possible for smart contracts to be recognized by law.

Aiming at insufficient situation to express and operate assets in smart contracts, in this article we attempt to add a new asset model into smart contract language (such as SPESC) through combing method of asset's expressions and transactions in real-world contracts. Moreover, a translation mechanism can be set up to accomplish a conversion from the asset model to an executable contract program. On this basis, we propose a new language design toward asset-driven specific smart contracts, called TA-SPESC. This language complies with the structure of real-world contracts and supports a formal definition composed of four modules: Party, asset, term, and contract attribute. This asset model on it can be used to define various types of rights (including the right of ownership, use, possession, usufruct, and disposition of assets), as well as five asset operations (including asset registration, deposit, withdrawal, transfer, and cancellation) to effectively support asset transaction. More important, a series of generation rules are proposed to translate the TA-SPESC contract to an executable contract program. Moreover, taking house rental contract as an example, we provide a TA-SPESC instance and its specific description of translation process according to the generation rules, which supports a semiautomatic generation to executable programs. Finally, the Solidity codes derived from TA-SPESC contracts are run and tested, and the experiment and comparison results indicate that TA-SPESC contracts have high abstraction and low complexity, as well as versatility and convenience of asset transaction, which lead to more reliable software with less errors and fewer misunderstanding.

With the advent of the big data era, information systems have exhibited some new features, including boundary obfuscation, system virtualization, unstructured and diversification of data types, and low coupling among function and data. These features not only lead to a big difference between big data technology (DT) and information technology (IT), but also promote the upgrading and evolution of network security technology. In response to these changes, in this paper we compare the characteristics between IT era and DT era, and then propose four DT security principles: privacy, integrity, traceability, and controllability, as well as active and dynamic defense strategy based on "propagation prediction, audit prediction, dynamic management and control". We further discuss the security challenges faced by DT and the corresponding assurance strategies. On this basis, the big data security technologies can be divided into four levels: elimination, continuation, improvement, and innovation. These technologies are analyzed, combed and explained according to six categories: access control, identification and authentication, data encryption, data privacy, intrusion prevention, security audit and disaster recovery. The results will support the evolution of security technologies in the DT era, the construction of big data platforms, the designation of security assurance strategies, and security technology choices suitable for big data.

This article aims to establish a cryptographic solution to improve security and reliability of the National Institute of Standards and Technology's attribute-based access control (ABAC) model. By breaking down the existing structure of attribute-based encryption, we propose a new cryptographic ABAC (C-ABAC) framework with dynamic policy authorization and real-time attribute credentials. Moreover, a practical C-ABAC construction is proposed to support provable policy decision making and verifiable attribute Tokens among multiple distributed authorities. In this construction, we develop a concrete approach of generating a cryptographic policy from access control markup language. We also prove that attribute Token has existential unforgeability under chosen-attribute and chosen-nonce attacks, and the cryptographic policy is existentially unforgeable under chosen-object attack. In addition, our C-ABAC construction provides semantic security against chosen-plaintext attack with Token and policy queries under the extended general Diffie-Hellman exponent assumption. Finally, we evaluate the performance of the C-ABAC system according to complexity analysis and experimental results. The results show that the C-ABAC system is reliable and easy to implement.

In this paper we focus on a new generation of secure resource sharing platform in a decentralized blockchain environment with flexible and diverse permission management, as well as verifiable and transparent access process. To do it, we present a new Transaction-based Access Control (TBAC) platform which integrates the standard attribute-based access control (ABAC) model and the blockchain system. In this platform, four types of transactions and Bitcoin-type cryptographic scripts are presented to describe the TBAC access control procedure corresponding to subject registration, object escrowing and publication, access request and grant. We also present a cryptosystem associated with TBAC (CryptoTBAC) for ensuring secure attribute-exchanging and decision-making of dynamic policy. We evaluate the security of CryptoTBAC from three aspects: transaction, authorization, and decision-making security.

In this paper, we present a new self-destructing data system, called retrograde storage. This system can randomly store messages into a storage pool built on frequently colliding hash table (FCHT) as an alternative way of DHT, and each message will be covered promptly after the expiry of validity period. This approach makes the message unrecoverable by multiple-pass Gutmann method and supports general secret sharing or encryption with counting control for personal data privacy. Moreover, we give a fundamental mathematical model of birth-death processes, in which we provide a detailed performance analysis by some theorems, including erasure distribution, recovery probability, secure erasure time, capacity of recycle pool. Experimental results indicated that our system is more efficient and accurate for controlling message self-destruction cycle, and makes it hard or impossible to recover data in a forensic investigation.

The smart contract is an interdisciplinary concept that concerns business, finance, contract law and information technology. Designing and developing a smart contract may require the close cooperation of many experts coming from different fields. How to support such collaborative development is a challenging problem in blockchain-oriented software engineering. This paper proposes SPESC, a specification language for smart contracts, which can define the specification of a smart contract for the purpose of collaborative design. SPESC can specify a smart contract in a similar form to real-world contracts using a natural-language-like grammar, in which the obligations and rights of parties and the transaction rules of cryptocurrencies are clearly defined. The preliminary study results demonstrated that SPESC can be easily learned and understood by both IT and non-IT users and thus has greater potential to facilitate collaborative smart contract development.

In this paper we address the problem of reliability and security in an open-access data sharing system. We propose a new framework, called cryptographic attribute-based access control (CABAC), in consistent with the standard ABAC model. Moreover, two new mechanisms, real-time Tokens and secure policy decision-making, are introduced for ensuring secure attribute authorization and verifiable policy decision-making. More important, we present a practical CABAC system to support adaptability and flexibility using dynamically chosen policy and real-time attribute acquisition. We prove that our CABAC system is provably secure in four aspects: the attribute Tokens are existentially unforgeable against chosen-time and chosen-attribute attacks, respectively; the secure policy is existentially unforgeable against chosen-object attack under eBDH assumption; and our entire system is semantically secure against chosen-plaintext attack with Token and policy queries under eGDHE assumption.

Recently, many enterprises have moved their data into the cloud by using file syncing and sharing (FSS) services, which have been deployed for mobile users. However, Bring-Your-Own-Device (BYOD) solutions for increasingly deployed mobile devices have also in fact raised a new challenge for how to prevent users from abusing the FSS service. In this paper, we address this issue by using a new system model involving anomaly detection, tracing, and revocation approaches. The presented solution applies a new threshold public key based cryptosystem, called partially-ordered hierarchical encryption (PHE), which implements a partial-order key hierarchy and it is similar to role hierarchy widely used in RBAC. PHE provides two main security mechanisms, i.e., traitor tracing and key revocation, which can greatly improve the efficiency compared to previous approaches. The security and performance analysis shows that PHE is a provably secure threshold encryption and provides following salient management and performance benefits: it can promise to efficiently trace all possible traitor coalitions and support public revocation not only for the users but for the specified groups.

Information Centric Networking (ICN) is a new network architecture that aims to overcome the weakness of existing IPbased networking architecture. Instead of establishing a connection between the communicating hosts, ICN focuses on the content, i.e., data, transmitted in network. Content copies in ICN can be cached at different locations. The content is out of its owner's control once it is published. Thus, enforcing access control policies on distributed content copies is crucial in ICN. Attribute-Based Encryption (ABE) is a feasible approach to enforce such control mechanisms in this environment. However, applying ABE in ICN faces two challenges: from management perspective, it is complicated to manage attributes in distributed manners; from privacy protection perspective, unlike in traditional networks, the enforced content access policies are public to all the ICN users. Thus, it is desirable that unauthorized content viewers are not able to retrieve the access policy. To this end, a privacy-preserving access control scheme for ICN and its corresponding attribute management solution are presented in this paper. The proposed approach is compatible with existing flat name based ICN architectures.

Online peer-to-peer (P2P) lending is an emerging wealth-management service for individuals, which allows lenders to directly bid and invest on the listings created by borrowers without going through any traditional financial intermediaries. As a nonbank financial platform, online P2P lending tends to have both high volatility and liquidity. Therefore, it is of significant importance to discern the hidden market states of the listings (e.g., hot and cold), which open venues for enhancing business analytics and investment decision making. However, the problem of market state modeling remains pretty open due to many technical and domain challenges, such as the dynamic and sequential characteristics of listings. To that end, in this paper, we present a focused study on market state modeling and analysis for online P2P lending. Specifically, we first propose two enhanced sequential models by extending the Bayesian hidden Markov model (BHMM), namely listing-BHMM (L-BHMM) and listing and marketing-BHMM (LM-BHMM), for learning the latent semantics between listings' market states and lenders' bidding behaviors. Particularly, L-BHMM is a straightforward model that only considers the local observations of a listing itself, while LM-BHMM considers not only the listing information but also the global information of current market (e.g., the competitive and complementary relations among listings). Furthermore, we demonstrate several motivating applications enabled by our models, such as bidding prediction and herding detection. Finally, we construct extensive experiments on two real-world data sets and make some deep analysis on bidding behaviors, which clearly validate the effectiveness of our models in terms of different applications and also reveal some interesting business findings.

Providing a creditable basis for access control decision-making is not an easy task for the resource pooling, dynamic, and multi-tenant cloud environment. The trust notation can provide this creditable basis, based on multiple factors that can accurately compute the user’s trust for the granting access entity. In this paper, the formal trust model has been introduced, which presents a novel method to provide the basis for granting access. It is based on three factors and their semantic relations, which investigate important measures for the cloud environment. Also, a new Trust-Based Access Control (TB-AC) model has been proposed. The proposed model supports dynamically changing the user’s assigned permissions based on its trust level. In addition, TB-AC ensures secure resource sharing among potential untrusted tenants. TB-AC has been deployed on a separated VM in our private cloud environment, which is built using OpenStack. The experimental results indicated that TB-AC can evaluate access requests within reasonable and acceptable processing times, which is based on the final trust level calculation and the communication between TB-AC and some of the intended OpenStack services. By considering very rough conditions and huge traffic overhead, the final trust level can be calculated in an average time of 200[Formula: see text]ms. Furthermore, the communication overhead between TB-AC and each of Keystone, Nova, and Neutron is very light. Finally, TB-AC has been tested under different scenarios and is provable, usable and scalable.

Blockchain is a radical innovation that has a significant impact on payments, stock exchanges, cybersecurity, and computational law. However, it has significant limitations regarding uncertainty for a transaction to be confirmed. This paper proposes a new system for exact confirmation of transactions in a block. Replacing original signature, a new Interactive Incontestable Signature (IIS) scheme is used between dealer and owner to confirm a transaction. By this signature, the dealer can assure the owner that a transaction will be included into blockchain in a non-repudiation way. The scheme is proved to be secure for owner's unforgeability and dealer's incontestability.

In this paper we present an identity-set-based broadcast encryption scheme with three working modes: positive membership (Select-mode), all member (All-mode), and negative membership (Cut-mode) over the user identity set, simultaneously. The core of our scheme is the implementation of cryptographic representation of subset by using two aggregation functions: Zeros-based aggregation and Poles-based aggregation. These two aggregation functions are capable of compressing any subset into one element in a bilinear map group for determining the membership between an element and a subset. Our scheme achieves the optimal bound of O(1)-size for either ciphertext (consisting of just two elements) or decryption key (one element) for an identity set of large size. We prove that our scheme is secure under the General Diffie-Hellman Exponent (GDHE) assumption.

Today, many cloud storage services have been available to small-to-medium business and individuals by file syncing-and-sharing (FSS) service. To meet the security requirement of FSS, we present a new architecture based on secure Player/Reader box with RBAC-compatible cryptosystem, which supports to access the encrypted data in the cloud, as well as traitor tracing and revocation mechanisms for pirate box. We improve a cryptosystem, called Partially-ordered Hierarchical Encryption (PHE) to realize this architecture. In this system, two security mechanisms, traitor tracing and revocation, are provided to support efficient digital forensics. The result of performance evaluation shows that our scheme is more efficient than the existing schemes with traitor tracing and revocation.

With the proliferation of mobile devices in recent years, there is a growing concern regarding secure data storage, secure computation, and fine-grained access control in data sharing for these resource-constrained devices in a cloud computing environment. In this work, we propose a new efficient framework named Constant-size Ciphertext Policy Comparative Attribute-Based Encryption (CCP-CABE) with the support of negative attributes and wildcards. It embeds the comparable attribute ranges of all the attributes into the user's key, and incorporates the attribute constraints of all the attributes into one piece of ciphertext during the encryption process to enforce flexible access control policies with various range relationships. Accordingly, CCP-CABE achieves the efficiency because it generates constant-size keys and ciphertext regardless of the number of involved attributes, and it also keeps the computation cost constant on lightweight mobile devices. We further discuss how to extend CCP-CABE to fit a scenario with multiple attribute domains, such that the decryption proceeds from the least privileged attribute domain to the most privileged one to help protect the privacy of the access policy. We provide security analysis and performance evaluation to demonstrate their efficiency at the end.

Malware is a burgeoning threat for smartphones and continuing advancing. Traditional defenses to malware, however, are not suitable for smartphones due to their resource intensive nature. This necessitates the design of novel mechanisms that can consider the specifics of the smartphone malware and smartphones themselves. In this paper, we introduce a lightweight permission enforcement approach-Tap-Wave-Rub (TWR)-for smartphone malware prevention. TWR is based on simple cyber-physical human interactions, i.e., human gestures, that are very quick and intuitive but less likely to be exhibited in users' daily activities. Presence or absence of such gestures, prior to accessing an application, can effectively inform the OS whether the access request is benign or malicious. In particular, we present the design of two mechanisms: 1) acceleration-based phone tapping detection and 2) proximity-based finger tapping, rubbing, or hand waving detection. The first mechanism is geared for near field communication applications, which usually require the user to tap her phone with another device. The second mechanism involves very simple gestures, i.e., tapping or rubbing a finger near the top of phone's screen or waving a hand close to the phone, and broadly appeals to many applications (e.g., SMS). In addition, we present the TWR-enhanced Android permission model, the prototypes implementing the underlying gesture recognition mechanisms, and a variety of novel experiments to evaluate these mechanisms. Our results suggest the proposed approach could be very effective for malware detection/prevention, with quite low false positives and false negatives, while imposing little to no additional burden on the users.

This paper addresses how to construct an RBAC-compatible secure cloud storage service with a user-friendly and easy-to-manage attribute-based access control (ABAC) mechanism. Similar to role hierarchies in RBAC, attribute hierarchies (considered as partial ordering relations) are introduced into attribute-based encryption (ABE) in order to define a seniority relation among all values of an attribute, whereby a user holding senior attribute values acquires permissions of his/her juniors. Based on these notations, we present a new ABE scheme called attribute-based encryption with attribute hierarchies (ABE-AH) to provide an efficient approach to implement comparison operations between attribute values on a poset derived from an attribute lattice. By using bilinear groups of a composite order, we present a practical construction of ABE-AH based on forward and backward derivation functions. Compared with prior solutions, our scheme offers a compact policy representation approach that can significantly reduce the size of private-keys and ciphertexts. To demonstrate how to use the presented solution, we illustrate how to provide richer expressive access policies to facilitate flexible access control for data access services in clouds.

We introduce a lightweight permission enforcement approach - Tap-Wave-Rub (TWR) - for smartphone malware prevention. TWR is based on simple human gestures (implicit or explicit) that are very quick and intuitive but less likely to be exhibited in users' daily activities. Presence or absence of such gestures, prior to accessing an application, can effectively inform the OS whether the access request is benign or malicious. In this paper, we focus on the design of an accelerometer-based phone tapping detection mechanism. This implicit tapping detection mechanism is geared to prevent malicious access to NFC services, where a user is usually required to tap her phone with another device. We present a variety of novel experiments to evaluate the proposed mechanism. Our results suggest that our approach could be very effective for malware prevention, with quite low false positives and false negatives, while imposing no additional burden on the users. As part of the TWR framework, we also briefly explore explicit gestures (finger tapping, rubbing or hand waving based on proximity sensor), which could be used to protect services which do not have a unique implicit gesture associated with them.

In this paper, we report on a new approach for enhancing security and privacy in certain RFID applications whereby location or location-related information (such as speed) can serve as a legitimate access context. Examples of these applications include access cards, toll cards, credit cards, and other payment tokens. We show that location awareness can be used by both tags and back-end servers for defending against unauthorized reading and relay attacks on RFID systems. On the tag side, we design a location-aware selective unlocking mechanism using which tags can selectively respond to reader interrogations rather than doing so promiscuously. On the server side, we design a location-aware secure transaction verification scheme that allows a bank server to decide whether to approve or deny a payment transaction and detect a specific type of relay attack involving malicious readers. The premise of our work is a current technological advancement that can enable RFID tags with low-cost location (GPS) sensing capabilities. Unlike prior research on this subject, our defenses do not rely on auxiliary devices or require any explicit user involvement.

Even though role-based access control (RBAC) can tremendously help us to minimize the complexity in administering users, it still needs to realize the notion of roles at the resource level. In this paper, we propose a practical cryptographic RBAC model, called role-key hierarchy model, to support various security features, including signature, identification, and encryption on role-key hierarchy. In addition, several advanced features, such as role or user revocation, tracing, and anonymity, are implemented as well. With the help of rich algebraic structure of elliptic curves, we introduce a unified and complete construction of role-based cryptosystem to verify the rationality and validity of our proposed model. In addition, a proof-of-concept prototype implementation and performance evaluation is discussed to demonstrate the feasibility and efficiency of our mechanisms.

In this paper, we propose a dynamic audit service for verifying the integrity of an untrusted and outsourced storage. Our audit service is constructed based on the techniques, fragment structure, random sampling, and index-hash table, supporting provable updates to outsourced data and timely anomaly detection. In addition, we propose a method based on probabilistic query and periodic verification for improving the performance of audit services. Our experimental results not only validate the effectiveness of our approaches, but also show our audit system verifies the integrity with lower computation overhead and requiring less extra storage for audit metadata.

Access control is one of the most important security mechanisms in cloud computing. However, there has been little work that explores various comparison-based constraints for regulating data access in clouds. In this paper, we present an innovative comparison-based encryption scheme to facilitate fine-grained access control in cloud computing. By means of forward/backward derivation functions, we introduce comparison relation into attribute-based encryption to implement various range constraints on integer attributes, such as temporal and level attributes. Then, we present a new cryptosystem with dual decryption to reduce computational overheads on cloud clients, where the majority of decryption operations are executed in cloud servers. We also prove the security strength of our proposed scheme, and our experiment results demonstrate the efficiency of our methodology.

Numerous cryptographic techniques have been developed to be used on mobile devices for various security and privacy protections. However, these cryptographic primitives, working under different mathematical assumptions, tend to become more and more complex and intricate, which makes it increasingly more difficult for proper implementation and management. Thus, it is desired to simplify management and improve efficiency by means of designing a general function family to meet a variety of security requirements. In this paper, we present such a family of square functions, including SqHash, SqMAC and SqPRF, based on a specially truncated function (MSB or LSB). We further improve the efficiency of these algorithms by using “circular convolution with carry bits” which makes parallel processing possible. We prove the security of these functions based on the privacy in hidden number problem and hard-core predicate of one-way function. We also show that the proposed schemes achieve better performance with a complexity reduction from O(n2) to O(kn/w) for n-bit message, k-bit output and w-bit word size.

Abstract—Access control is one of the most important security mechanisms in cloud computing. Attribute-based access control provides a flexible approach that allows data owners to integrate data access policies within the encrypted data. However, little work has been done to explore temporal attributes in specifying and enforcing the data owner’s policy and the data user’s privileges in cloud-based environments. In this paper, we present an efficient temporal access control encryption scheme for cloud services with the help of crypto-graphic integer comparisons and a proxy-based re-encryption mechanism on the current time. We also provide a dual comparative expression of integer ranges to extend the power of attribute expression for implementing various temporal constraints. We prove the security strength of the proposed scheme and our experimental results not only validate the effectiveness of our scheme, but also show that the proposed integer comparison scheme performs significantly better than previous bitwise comparison scheme.

A hybrid cloud is a cloud computing environment in which an organization provides and manages some internal resources and has others provided externally. However, this new environment could bring irretrievable losses to the clients due to a lack of integrity verification mechanism for distributed data outsourcing. To support scalable service and data migration, in this paper we address the construction of a collaborative integrity verification mechanism in hybrid clouds where we consider the existence of multiple cloud service providers to collaboratively store and maintain the clients' data. We propose a collaborative provable data possession scheme adopting the techniques of homomorphic verifiable responses and hash index hierarchy. In addition, we articulate the performance optimization mechanisms for our scheme and prove the security of our scheme based on multi-prover zero-knowledge proof system, which can satisfy the properties of completeness, knowledge soundness, and zero-knowledge. Our experiments also show that our proposed solution only incurs a small constant amount of communications overhead.

Provable data possession (PDP) is a technique for ensuring the integrity of data in storage outsourcing. In this paper, we address the construction of an efficient PDP scheme for distributed cloud storage to support the scalability of service and data migration, in which we consider the existence of multiple cloud service providers to cooperatively store and maintain the clients' data. We present a cooperative PDP (CPDP) scheme based on homomorphic verifiable response and hash index hierarchy. We prove the security of our scheme based on multiprover zero-knowledge proof system, which can satisfy completeness, knowledge soundness, and zero-knowledge properties. In addition, we articulate performance optimization mechanisms for our scheme, and in particular present an efficient method for selecting optimal parameter values to minimize the computation costs of clients and storage service providers. Our experiments show that our solution introduces lower computation and communication overheads in comparison with noncooperative approaches.

A hybrid cloud is a cloud computing environment in which an organization provides and manages some internal resources and the others provided externally. However, this new environment could bring irretrievable losses to the clients due to a lack of integrity verification mechanism for distribute

Even though role-based access control (RBAC) can tremendously help us minimize the complexity in administering users, it is still needed to realize the notion of roles at the resource level. In this paper, we propose a practical cryptographic RBAC model, called role-key hierarchy model, to support various security features including signature and encryption based on role-key hierarchy. With the help of rich algebraic structure of elliptic curve, we introduce a role-based cryptosystem construction to verify the rationality and validity of our proposed model. Also, a proof-of-concept prototype implementation and performance evaluation are discussed to demonstrate the feasibility and efficiency of our mechanisms.

Provable data possession is a technique for ensuring the integrity of data in outsourcing storage service. In this paper, we propose a cooperative provable data possession scheme in hybrid clouds to support scalability of service and data migration, in which we consider the existence of multiple cloud service providers to cooperatively store and maintain the clients' data. Our experiments show that the verification of our scheme requires a small, constant amount of overhead, which minimizes communication complexity.

With the wide use of online social networks (OSNs), the problem of data privacy has attracted much attention. Several approaches have been proposed to address this issue. One of privacy management approaches for OSN leverages a key management technique to enable a user to simply post encrypted conte

In this paper, a novel semi-fragile authentication scheme based on block-mean quantization in the wavelet domain is proposed for image authentication. The scheme is composed of a structural digital signature process and a semi-fragile watermarking/ fingerprinting algorithm. In the signature process, the invariants are extracted as authentication codes from the quantization relationships and hierarchy information of discrete wavelet decomposition. The authentication codes consist of inter-block and intrablock codes in order to detect and localize tampering. The semi-fragile fingerprinting algorithm is intended to embed the signature via the use of block-mean quantization. The proposed scheme can effectively detect and localize the malicious modification while tolerating lossy compression.

In a general additive watermarking model, a watermark signal is perceptually shaped and scaled with a global gain factor before embedding. This paper presents a new image-adaptive watermarking scheme based on perceptually shaping watermark blockwise. Instead of the global gain factor, a localized one is used for each block. And Watson's DCT-based visual model is adopted to measure the distortion of each block introduced by watermark, rather than the whole image. With the given distortion constraint, the maximum output value of linear correlation detector is derived in one block, which demonstrates the reachable maximum robustness in a sense. Meanwhile, an extended perceptually shaped watermarking (EX-PSW) is acquired through making detection value approach that upper limit. It is proved mathematically that EX-PSW outputs higher detection value than perceptually shaped watermarking (PSW) with the same distortion constraint. We also discuss the adjustment strategies of parameters in EX-PSW, which are helpful for improving the local image quality. Experimental results show our scheme provides very good results both in terms of image transparency and robustness.

Digital Fingerprinting is a technique for the merchant who can embed unique buyer identity marks into digital media copy, and also makes it possible to identify traitors who redistribute their illegal copies. At present, the fingerprinting scheme generally have many difficulties and disadvantages for large-size uses problems involve in the code construction with shorter length and effective traitor tracing. To resolve these problems, this paper presents the definition of Fingerprinting Information Code and a practical construction method by composing of convolutional codes and generally fingerprinting codes based on Boneh-Shaw model. Its decoding algorithm is presented by introducing the ideal of 'Optional Code Subset' and improving Viterbi algorithm. The security properties and performance are proved and analyzed by theory and example. As the results, the proposed scheme has shorter information encoding length and achieves optimal traitor searching in larger number of buyers.