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The transition from paper-based information to Electronic-Health-Records (EHRs) has driven various advancements in the modern healthcare industry. In many cases, patients need to share their EHR with healthcare professionals. Given the sensitive and security-critical nature of EHRs, it is essential to consider the security and privacy issues of storing and sharing EHR. However, existing security solutions excessively encrypt the whole database, thus requiring the entire database to be decrypted for each access request, which is time-consuming. On the other hand, the use of EHR for medical research (e.g., development of precision medicine and diagnostics techniques) and optimisation of practices in healthcare organisations require the EHR to be analysed. To achieve that, they should be easily accessible without compromising the patient's privacy. In this paper, we propose an efficient technique called E-Tenon that not only securely keeps all EHR publicly accessible but also provides the desired security features. To the best of our knowledge, this is the first work in which an Open Database is used for protecting EHR. The proposed E-Tenon empowers patients to securely share their EHR under their own multi-level, fine-grained access policies. Analyses show that our system outperforms existing solutions in terms of computational complexity. [ABSTRACT FROM AUTHOR]

Searchable asymmetric encryption (SAE) enables a client to search over a data owner's encrypted data. Nevertheless, state-of-the-art SAE schemes allow a data owner to specify access control policy for a client, while they have not considered the threat case of a malicious data owner. To address the problem, this work presents a non-interactive SAE scheme with bilateral access control: (i) allowing data owner and client to both specify policies toward the other party; (ii) allowing client to perform arbitrary boolean queries with sub-linear search complexity. Technically, we extend Cash et al.'s highly scalable SSE into an asymmetric setting and introduce the property of data owner authenticity. By refining identity-based matchmaking encryption, we formalize the syntax and security definition of our SAE with identity-based bilateral access control. Moreover, the security of the proposed SAE can be reduced to discrete logistic assumption and decisional bilinear Diffie–Hellman assumption. As an enhanced extension, we present a non-interactive multi-client SAE scheme with fuzzy identity-based bilateral access control. In addition, we implement the proposed schemes in real cloud platform and evaluate their performance on a real-world dataset. The result confirms that our SAE schemes achieve bilateral access control for both data owner and client with highly acceptable efficiency. [ABSTRACT FROM AUTHOR]

Dynamic searchable symmetric encryption (DSSE) with forward and backward privacy makes it possible to perform search on the outsourced encrypted database efficiently while still allowing updates under acceptable leakage. Current forward and backward private DSSE (FB-DSSE) scheme proposed by Zuo et al. cannot support conjunctive keyword query and the cloud server needs to be honest-but-curious. Recent FB-DSSE scheme supporting conjunctive keyword query proposed by Patranabis et al. cannot verify search results. On the other hand, searchable symmetric encryption scheme proposed by Wang et al. that supports conjunctive keyword query and the verification of search results cannot achieve forward and backward privacy. The problem of constructing a verifiable conjunctive FB-DSSE scheme is still open. In this paper, we propose a verifiable conjunctive dynamic searchable symmetric encryption scheme (VCDSSE). VCDSSE is a FB-DSSE scheme that additionally supports the verification of search results and conjunctive keyword query. We revisit homomorphic MAC to enable efficient verification of search results, adopt the technique of oblivious cross-tags to achieve conjunctive keyword query and utilize state chain to ensure forward and backward privacy. The formal security analysis and performance evaluation demonstrate that VCDSSE is secure and practical as compared with Mitra scheme in terms of search time. [ABSTRACT FROM AUTHOR]

Public key encryption with keyword search is a promising primitive which enables search over encrypted data in secure data outsourcing services. In traditional construction, the associated keywords may be recovered from a given trapdoor by a malicious server through keyword guessing attacks. Therefore, the notion of public-key authenticated encryption with keyword search (PAEKS) was introduced, where a sender encrypts (and authenticates) the keywords using a receiver's public key and its secret key. In this paper, we consider the forward security for PAEKS and introduce a new primitive: forward secure public-key authenticated encryption with keyword search (FS-PAEKS), which captures the information leakage risk from previously issued queries due to the updates on the outsourced data. Technically, we embed a non-interactively agreed key into the cipher-keyword generation algorithm, and bind the cipher-keyword and the trapdoor with a set converted from algorithm-generation time. Finally, we present an efficient FS-PAEKS scheme supporting conjunctive query, and prove its forward security against chosen keyword attacks and keyword guessing attacks. To illustrate practical performance, we implement our FS-PAEKS and related PAEKS schemes based on Enron dataset in real cloud environment. [ABSTRACT FROM AUTHOR]

Secure cloud-assisted data publish/subscribe (Pub/Sub) service provides an asynchronous method for publishers and subscribers to non-interactively exchange encrypted messages. Besides performing conjunctive subscription policy, numerous data Pub/Sub systems have recently been proposed to provide dynamic access control enforced from the publisher side to the subscriber side. However, these solutions fail to consider the following properties: (i) bilateral access control for both publishers and subscribers; (ii) the anonymity of the publisher; (iii) high matching time cost between publication and subscription. Therefore, we present P/S-BiAC, a secure and boolean cloud-assisted data Pub/Sub system with attribute-based bilateral access control that achieves authenticity and anonymity of publishers. In particular, P/S-BiAC enables cloud-based brokers to use the subscriber’s trapdoor to match published data with sub-linear time complexity. Technically, we introduce a “BiAC-and-Hidden” technique to refine publication tuples and trapdoor in classic searchable symmetric encryption solutions. Moreover, we implement P/S-BiAC and evaluate its practical performance based on Enron dataset in real cloud environment. To deal with a conjunctive subscription policy, P/S-BiAC runs $27.8\times $ faster for matching time cost (with $s$ -term=10) compared to state-of-the-art solutions, which demonstrates its feasibility in practical data Pub/Sub services with strong security properties. [ABSTRACT FROM AUTHOR]

Despite the myriad benefits offered by blockchain technology, most of them still face several interrelated issues, such as limited transaction throughput, exorbitant transaction fees, and protracted confirmation times. Payment channel networks have emerged as a promising scalability solution, allowing two mutually distrustful users to engage in multiple off-chain transactions. However, existing schemes based on Hash Time Lock Contract or Anonymous Multi-hop Lock generally cannot ensure strong unlinkability of payments, due to the fact that the time-lock information still remains on the blockchain. To enhance on-chain privacy, a versatile tool was recently proposed by Thyagarajan et al. (CCS’20), named Verifiable Timed Signatures, but it suffers from the dual insufficiencies of linear-increasing performance and time unverifiability (i.e., performance is linear to the number of signature shares, and signatures cannot be ensured recoverable after the specified time). In this paper, we first propose an approach to reduce computational overhead of VTS, which can be applied to enhance other established schemes, such as VTD (S&P’22) and VTLRS (ESORICS’22). To further reduce the computational complexity from $\mathcal {O}(n)$ to $\mathcal {O}(1)$ , we introduce a new cryptographic primitive called Verifiable Timed Adaptor Signatures. Moreover, we extend the VTAS to VTAS+ which provides the security property of verifiable recovery. We demonstrate the practicality of our proposal via presenting a concrete instantiation and constructing a privacy-enhanced payment channel network. Finally, the comprehensive evaluation reveals that our solutions exhibit superior performance than the state-of-the-art schemes. [ABSTRACT FROM AUTHOR]

Cloud computing has been widely accepted as a computing paradigm to offer high-quality data services on demand. However, it suffers from various attacks as the cloud service provider and data owners are not in the same trusted domain. To support data confidentiality, existing cloud-based systems apply cryptographic tools to issue the decryption key to data users to share data in a controlled way. However, fine-grained cloud data sharing still faces many challenges, especially when dealing with dynamic user groups. In this paper, we introduce a secure and efficient cloud-based data-sharing system with fine-grained access control and dynamic user groups. Our system enjoys 1) adaptive security in prime-order groups, 2) forward secrecy against revoked user fetches data generated before being revoked, and 3) decryption key exposure resistance against the compromise of the frequently used decryption key, where the previous solutions only concentrate on one or two above-mentioned properties. More specifically, we introduce two timestamp management mechanisms that manage the timestamp in each ciphertext to support dynamic user groups with forward secrecy. By applying the proposed timestamp management mechanisms, we introduce two novel designs of attribute-based encryption schemes with formal definition and security analyses. The proposed schemes are adaptively secure in prime-order groups under a standard assumption and support decryption key exposure resistance. We conduct theoretical analysis and experimental simulation to demonstrate the outperformance of our solutions. [ABSTRACT FROM AUTHOR]

Deep neural networks (DNNs) have profoundly changed our lifeways in recent years. The cost of training a complicated DNN model is always overwhelming for most users with limited computation and storage resources. Consequently, an increasing number of people are considering to resort to a cloud for an outsourced DNN model training. However, the DNN models training process outsourced to the cloud faces privacy and security issues due to the semi-honest and malicious cloud environments. To preserve the privacy of the data and the parameters in DNN models during the outsourced training and to detect whether the models are injected with backdoors, this paper presents DeepGuard, a framework of privacy-preserving backdoor detection and identification in an outsourced cloud environment for multi-participant computation. In particular, we design a privacy-preserving reverse engineering algorithm for recovering the triggers and detecting the backdoor attacks among three cooperative but non-collusion servers. Moreover, we propose a backdoor identification algorithm adapting to single-label and multi-label attack detection. Finally, extensive experiments on the prevailing datasets such as MNIST, SVHN, and GTSRB confirm the effectiveness and efficiency of backdoor detection and identification in a privacy-preserving DNN model. [ABSTRACT FROM AUTHOR]

Cloud-based VANETs are designed to enable communication between high-speed vehicles. In such a highly dynamic environment, how to provide secure and anonymous communication service is a challenge. In this article, we affirmatively address the challenge by proposing a traitor-resistant and dynamic anonymous communication framework (TD-ACF) for cloud-based VANETs, which supports several advantageous features. In TD-ACF, each vehicle is represented by a set of attributes instead of its real identity, and the driving data is transmitted in encrypted form. Therefore, the anonymous authentication and the confidentiality of driving data are achieved in this way. Meanwhile, TD-ACF supports two practical requirements in cloud-based VANETs: the revocation and the traceability of traitor. For the former, TD-ACF can force a vehicle to exit the communication network at any moment. We employ an efficient binary tree algorithm to reduce the size of key updates for revocation from the traditional linear to the logarithmic level. For the latter, we overcome the barrier of the one-to-many relationship between a vehicle and the shared set of attributes to support traitor tracing. In TD-ACF, unlike most existing schemes, the Semi-Trusted Cloud (STC) can directly capture and punish a traitor instead of querying all the records in the list of unrevoked vehicles. In addition, we solve the key escrow problem that plagues most existing attribute-based schemes. The theoretical analysis and experimental simulation show that the proposed scheme is feasible and effective. [ABSTRACT FROM AUTHOR]

Secure cloud search service allows resource-constrained clients to effectively search over encrypted cloud storage. Towards enabling owner-enforced search authorization, the notion of attribute-based keyword search (ABKS) has been introduced and widely deployed in practice. To enhance traditional security of ABKS, two state-of-the-art solutions are presented to address keyword guessing attacks or setup inconsistency for secret key. Nevertheless, they have not simultaneously considered the following threats to a data user: (i) inconsistent secret key/cipher-index caused by outside dishonest authority and/or data owner; (ii) algorithm substitution attacks (ASA) launched by inside adversarial eavesdropping. These attacks may unfortunately lead to cloud data breach and user information exposure. To tackle such outside and inside threats, we introduce subversion-resistance and consistency for secure and fine-grained cloud document search services. In particular, we propose a consistent ABKS system with cryptographic reverse firewalls (CRF). Technically, we refer to verifiable functional encryption and employ non-interactive zero-knowledge proofs of discrete logarithm equality to ensure strong input consistency for ABKS. In addition, we build a trusted CRF zone for sanitizing algorithm outputs against ASA attacks. Moreover, we formalize the security model and formally prove security of our system. To clarify practical performance, we implement state-of-the-art solutions and our system in real cloud environment based on Enron dataset. The results show that our system achieves more enhanced security properties without obviously sacrificing performance. In particular, our system achieves comparable time and storage cost for document-index encryption and document search, as compared to state-of-the-art solutions. [ABSTRACT FROM AUTHOR]

Image licensing regulates the scope, type, and limitations of using an image through an agreement. However, it is challenging to verify whether an agreement has been fulfilled honestly. Existing techniques, such as watermarking and perceptual hashing, help check image originality and editing operations specified in the agreement, but fail to achieve editor designation. In this paper, we propose a verifiable image licensing system (VILS) which provides an effective solution to verify if a received image is used legally according to its licensing agreement. The core building block of our design is a new kind of cryptographic primitive, called accumulator with a designated entity. The new accumulator helps achieve not only editing restriction, but also editor designation in image authentication. Our VILS has the following two appealing features: (1) Authorization: Only an authorized licensee who edits an image with operations declared in a licensing agreement can produce valid images; (2) Efficiency: The verification of VILS is efficient and independent of the number of operations or image size. Compared with the most relevant schemes from the state-of-the-art, the new design enriches the functionality of image authentication but reduces the verification time by 40%. [ABSTRACT FROM AUTHOR]

Outsourcing encrypted data to cloud servers that has become a prevalent trend among Internet users to date. There is a long list of advantages on data outsourcing, such as the reduction cost of local data management. How to securely operate encrypted data (remotely), however, is the top-rank concern over data owner. Liang et al. proposed a novel encrypted cloud-based data share and search system without loss of privacy. The system allows users to flexibly search and share encrypted data as well as updating keyword field. However, the search complexity of the system is of extreme inefficiency, $O(n d)$ O (n d) , where $d$ d is the total number of system files and $n$ n is the size of query formula. This article, for the first time, leverages the “oblivious cross search” technology in public key searchable encryption context to reduce the search complexity to only $O(nf(w))$ O (n f (w)) , where $f(w)$ f (w) is the number of files embedded with the “least frequent keyword” $w$ w . The new scheme maintains efficient encrypted data share and keyword field update as well. This article further revisits the security models for payload security, keyword privacy and search token privacy (i.e., search pattern privacy) and meanwhile, presents security and efficiency analysis for the new scheme. [ABSTRACT FROM AUTHOR]

With the fantastic development of cloud computing technology, cloud storage has been widely applied in the field of medical data sharing due to its efficiency and flexibility. Attribute-based encryption (ABE), as a promising technology, plays an important role in the fine-grained sharing of medical data. However, there are two issues: (1) an access policy specified in the encryption phase may need to be updated after a period of time, and (2) the considerable decryption overhead in ABE is too heavy for resource-limited devices. To address these issues, a fine-grained medical data sharing scheme with ciphertext reencryption is proposed. Users with decryption permission can produce reencryption keys and cloud server can reencrypt initial ciphertext. The cloud server can predecrypt ciphertext, which reduces user's decryption overhead. Moreover, the traditional centralized server is replaced with a decentralized blockchain that performs system initialization, key management, and user revocation. We compared the proposed scheme with some existing schemes in terms of function and efficiency; the results show that the efficiency of the proposed scheme outperforms other related schemes. The security analysis shows that the proposed scheme is security and correctness. [ABSTRACT FROM AUTHOR]

Big data analytics has been regarded as a promising technology to yield better insights into future development by government and industry. Data collection and aggregation are necessary pre-steps to enable data analysis. However, data may be dispersed across multiple places and in different formats. Even worse, data can be encrypted under various encryption mechanisms when data owners try to secure the confidentiality of the data. This makes data aggregation extremely challenging, if not impossible, especially when the encryption keys cannot be shared for various reasons. In this paper, we take the first step in addressing this problem. More specifically, we propose a new notion of cross-domain encryption switching service that securely bridges two well-studied encryption mechanisms, namely traditional public key encryption and identity-based encryption. As of independent interest, our notion supports keyword search over encrypted data, i.e., after encryption switching one may search over the (outsourced) data without loss of data and query secrecy. We provide a provably-secure instantiation satisfying the notion, and further present the efficiency analysis to show the scalability. Our proposed scheme may be applicable in multi-domain cloud storage system. [ABSTRACT FROM AUTHOR]

As a versatile technique, cloud-fog computing extends the traditional cloud server to offer various on-demand data services. Maintaining data confidentiality is one of the most crucial requirements for data services, many cryptosystems have been proposed to reserve information privacy against such an untrusted environment. However, in cloud-fog computing, how to confidentially and efficiently share data and fetch desirable data without expensive data decryption for resource-constrained end-devices is challenging. In this paper, we propose a cloud-fog system for the Internet-of-Things (IoT) ecosystem by introducing a cryptographic primitive called server-aided revocable bilateral attribute-based encryption (SRB-ABE). Our solution is a secure and lightweight bilateral access control system with dynamic user groups, including (1) fine-grained data user and data owner access control simultaneously; (2) outsourced data source identification; (3) server-aided user revocation with publicly updatable ciphertexts; and (4) lightweight data decryption mechanism with one exponentiation computation. We present the formal definition and concrete construction of SRB-ABE with security proofs to build cloud-fog systems. The extensive comparison and experimental analysis demonstrate that our construction has superior functionality and comparable performance than the most relevant solutions. [ABSTRACT FROM AUTHOR]

Contact tracing is a critical tool in containing epidemics such as COVID-19. Researchers have carried out a lot of work on contact tracing. However, almost all of the existing works assume that their clients and authorities have large storage space and powerful computation capability and clients can implement contact tracing on their own mobile devices such as mobile phones, tablet computers, and wearable computers. With the widespread outbreaks of the epidemics, these approaches are of less robustness to a larger scale of datasets when it comes to resource-constrained clients. To address this limitation, we propose a publicly verifiable contact tracing algorithm in cloud computing (PvCT), which utilizes cloud services to provide storage and computation capability in contact tracing. To guarantee the integrity and accuracy of contact tracing results, PvCT applies a novel set accumulator-based authentication data structure whose computation is outsourced, and the client can check whether returned results are valid. Furthermore, we provide rigorous security proof of our algorithm based on the q -Strong Bilinear Diffie–Hellman assumption. Detailed experimental evaluation is also conducted on three real-world datasets. The results show that our algorithm is feasible within milliseconds of client CPU time and can significantly reduce the storage overhead from the size of datasets to a constant 128 bytes. [ABSTRACT FROM AUTHOR]

Proxy re-encryption (PRE) allows a proxy to transform one ciphertext to another under different encryption keys while keeping the underlying plaintext secret. Because of the ciphertext transformability of PRE, there are many potential private communicating applications of this feature. However, existing PRE schemes are not as full-fledged as expected. The lack of necessary features makes them hard to apply in real-world scenarios. So far, there does not exist a unidirectional multihop PRE scheme with constant decryption efficiency and constant ciphertext size without extensions. Impractical performance and weak scalability also hinder PRE from most real-world applications. In this work, we present a new PRE scheme with secure hardware enclave named hPRESS (hardware-enhanced PRE scheme using secure enclave). To the best of our knowledge, hPRESS is the first unidirectional multihop PRE scheme which achieves both constant decryption efficiency and constant ciphertext size without extensions. A detailed security analysis demonstrates that our proposal is CCA secure based on the security of the underlying encryption schemes and the secure enclave. We also implement a prototype based on Intel SGX, one of the most popular secure enclave techniques in recent years, and evaluate its performance. The experimental results show that, compared with previous PRE schemes, our hPRESS is almost one order of magnitude faster in terms of the decryption and transformation. [ABSTRACT FROM AUTHOR]

When machine learning meets the IoT security, it can be divided into two parts: (i) use the machine learning to detect the malicious attacks; (ii) use the privacy-preserving methods to protect the machine learning model and data. Keywords: Internet-of-Things; Privacy; Security EN Internet-of-Things Privacy Security 1 4 4 05/10/21 20210501 NES 210501 INTRODUCTION With billions of Internet-of-Thing (IoT) devices collecting data interoperate within the existing Internet infrastructure technology, IoT techniques have been considered as a necessary part of our daily life, such as wearable IoT devices to monitor personal health status, banking and financial services, life sciences, retail and industrial, and home automation. The paper by Y. Jiang et al, entitled " I A verifiable and privacy-preserving multi-dimensional data aggregation scheme in mobile crowdsensing, i " proposed a verifiable privacy-preserving data aggregation scheme, which is based on data double-masking, Shamir's secret sharing, and bilinear mapping. [Extracted from the article]