Semi-trusted Party Research Articles

Privacy protection based distributed clustering with deep learning algorithm for distributed data mining

Distributed Data Mining (DDM) is vital in various applications for processing large volumes of data. The datasets are saved in the local databases and operated by local communities, but it provides the solution locally and globally. However, the datasets are stored in a distributed manner which affects the scalability and reliability issues. In addition, locally stored data is influenced by security and privacy challenges. In addition, the third party may access the DDM, which causes authorization issues. Therefore, the DDM process fuses sensor data from different sources to improve knowledge discovery. During this process, the DDM faces several issues such as security concerns, privacy restrictions, technical barriers, and trust issues. To address these issues, distributed data mining (DDM) should be improved to handle homogeneous and heterogeneous data. This work uses the privacy protection-based distributed clustering (PPDC) algorithm to handle the privacy and security challenges while analyzing the distributed data. The clustering algorithm generates the semi-trusted third parties to form the cluster, which protects the data from unauthorized users. The semi-trusted party protect the locally analyzed solution by creating the random vector-based trusted process. Further, the process uses the optimized deep learning approach and clustering to improve the heterogeneous data analysis. Then the effectiveness of the introduced PPDC method is compared with existing methods, and the PPDC algorithm ensures the 0.202 error rate, 0.95 % of accuracy and manages the data security.

Efficient public-key encryption with equality test from lattices

Public-key encryption with equality (PKEET) test enables testing if two ciphertexts, possibly under two different public keys, encrypt the same messages. Recent research on PKEET considers the setting where the testing ability is delegated to semi-trusted parties to negate unfettered chosen-plaintext attacks. In this work, we revise and enhance the PKEET security model, and introduce a new property of unmaskability which further prevents an attacker from skirting the test. We then propose a simple and efficient PKEET system with adaptive chosen-ciphertext security, provably secure under our revised security model, from either plain or ring lattice assumptions. The construction adopts a direct approach which significantly departs from the existing way of building such systems. Compared with existing literature, our system relies on weaker learning-with-errors assumptions while also being more efficient and providing better security.

Multiauthority Access Control With Anonymous Authentication for Personal Health Record

A personal health record (PHR) system is a smart health system that serves patients and doctors. A PHR is usually stored in a cloud and managed by a semitrusted cloud provider. However, there is still a possibility of the exposure of personal health information to semitrusted parties and unauthorized users. To protect the privacy of patients and ensure that patients can control their PHRs, a patient-centric PHR sharing framework is proposed in this article. In this framework, all PHRs are protected with multiauthority attribute-based encryption before outsourcing, which solves the key hosting problem and achieves fine-grained access control to PHRs. Furthermore, an anonymous authentication between the cloud and the user is proposed to ensure data integrity on the cloud while not exposing the user’s identity during authentication. The proposed authentication is issued from a new online–offline attribute-based signature. It can make the encrypted PHRs resist collusion attacks and not be forged during the period of sharing, which enhances patients’ control of their PHRs. Online–offline and outsourcing decryption also reduces calculation costs and improves operational efficiency. Finally, comparisons are given based on numerical experiments.

A Secure Three-factor Authenticated Key Agreement Scheme for Multi-Server Environment

Multi-server authenticated key agreement schemes have attracted great attention to both academia and industry in recent years. However, traditional authenticated key agreement schemes in the single-server environment are not suitable for the multi-server environment because the user has to register on each server when he/she wishes to log in various servers for different service. Moreover, it is unreasonable to consider all servers are trusted since the server in a multi-server environment may be a semi-trusted party. In order to overcome these difficulties, we designed a secure threefactor multi-server authenticated key agreement protocol based on elliptic curve cryptography, which needs the user to register only once at the registration center in order to access all semi-trusted servers. The proposed scheme can not only against various known attacks but also provides high computational efficiency. Besides, we have proved our scheme fulfills mutual authentication by using the authentication test method.

Secure real-time image protection scheme with near-duplicate detection in cloud computing

With advancements in technologies of the Internet and multi-media, various images need to be generated and transmitted anytime. Restricted by local constrained storage space, users can store their images with the assist of the cloud. However, the cloud is a remote semi-trusted party that may extract stored images for adversaries due to monetary reasons. In this paper, a secure real-time image protection scheme is proposed, which can be used to enhance the security of the stored images in cloud computing. Moreover, the convergent encryption is used to construct our scheme, which can provide functionalities of image deduplication checking and near-duplicate detection for the image owner. To improve the efficiency of the near-duplicate detection, deep learning is exploited in our scheme to extract images. Security analysis indicates that the proposed scheme can meet the security requirements of correctness and security. Performance analysis shows that the proposed scheme can be performed with low computational cost.

OTP-IoT: An ownership transfer protocol for the Internet of Things

An RFID ownership transfer protocol enables a tag owner to transfer the ownership of the tag to a new owner. While there have been a large number of such protocols in the literature, designing secure and efficient protocols remains a challenging task. In this paper, we propose a scalable and secure RFID ownership transfer protocol that can be deployed in resource-constrained EPC class tags in a large RFID inventory system. The contribution of this paper include: employing a Semi-Trusted Party (STP) to leverage the essence of typical complex ownership transfer process for the end users, introducing a new variant of mutual authentication scheme from Learning Parity from Noise (LPN) problem to the typical ownership transfer protocol, allowing multiple tags from an owner to be transferred to the new owner by combining homomorphic aggregated signature (HomSig) and pseudo-inverse matrix properties. We demonstrate that the scheme is secure under the standard model. To the best of our knowledge, this is the first provably secure LPN-based ownership transfer protocol that allows relatively small gate-count and code size suitable for the low-cost and resource-constrained IoT devices.

Securely outsourcing the ciphertext-policy attribute-based encryption

Attribute-based Encryption (ABE) is a new and promising public key encryption that allows fine-grained authorization on data based on user attributes. Such property is favorable for multiple applications that require encrypted storage or access control on data, in particular: eHealth applications. However, ABE schemes are known not to be efficient in the encryption phase because ciphertext size and the time required to encrypt grow with the complexity of the access policy. Such drawback is critical in the context of pervasive computing, for instance, in the Internet of Things, where data producers are usually resource-constrained devices, e.g. smart phones or sensing platforms. In this work, we propose OEABE standing for Outsourcing mechanism for the Encryption of Ciphertext-Policy ABE (CP-ABE). We show how a user can offload expensive operations of CP-ABE encryption to a semi-trusted party in a secure manner. Our proposed mechanism requires only one exponentiation on resource-constrained devices. We provide also an informal security analysis of possible attacks from a semi-honest adversary against the proposed solution. To demonstrate the performance gains of our mechanism, we first conducted a performance estimation on an emulated Wismote sensor platform. Then, we implemented our proposal and did comparison to an existing implementation of CP-ABE on a laptop.

Dynamic Encrypted Data Sharing Scheme Based on Conditional Proxy Broadcast Re-Encryption for Cloud Storage

Since Cloud Service Provider is a semi-trusted party in cloud storage, to protect data from being disclosed, users’ data are encrypted before being uploaded to a cloud server. Undoubtedly, flexible encrypted data sharing is a very important demand required by cloud storage users, whereas few schemes have being designed to satisfy this demand. In this paper, based on conditional proxy broadcast re-encryption technology, an encrypted data sharing scheme for secure cloud storage is proposed. The scheme not only achieves broadcast data sharing by taking advantage of broadcast encryption, but also achieves dynamic sharing that enables adding a user to and removing a user from sharing groups dynamically without the need to change encryption public keys. Moreover, by using proxy re-encryption technology, our scheme enables the proxy (cloud server) to directly share encrypted data to the target users without the intervention of data owner while keeping data privacy, so that greatly improves the sharing performance. Meanwhile, the correctness and the security are proved; the performance is analyzed, and the experimental results are shown to verify the feasibility and the efficiency of the proposed scheme.

Private Personal Information Verification

Physical document verification is a necessary task in the process of reviewing applications for a variety of services, such as loans, insurance, and mortgages. This process consumes a large amount of time, money, and human resources, which leads to limited business throughput. Furthermore, physical document verification poses a critical risk to clients’ personal information, as they are required to provide sensitive details and documents to verify their information. In this paper, we present a systematic approach to address shortcomings in the current state of the processes used for physical document verification. Our solution leverages a semi-trusted party data source (i.e. a governmental agency) and cryptographic protocols to provide a secure digital service. We make use of homomorphic encryption and secure multi-party computation to develop a series of protocols for private integer comparison and (non-) membership testing. Secure boolean evaluation and secure result aggregation schemes are proposed to combine the results of the evaluation of multiple predicates and produce the final outcome of the verification process. We also discuss possible improvements and other applications of the proposed secure system of protocols. Our framework not only provides a cost-efficient and secure solution for document verification, but also creates space for a new service.

Cryptoleq: A Heterogeneous Abstract Machine for Encrypted and Unencrypted Computation

The rapid expansion and increased popularity of cloud computing comes with no shortage of privacy concerns about outsourcing computation to semi-trusted parties. Leveraging the power of encryption, in this paper, we introduce Cryptoleq: an abstract machine based on the concept of one instruction set computer, capable of performing general-purpose computation on encrypted programs. The program operands are protected using the Paillier partially homomorphic cryptosystem, which supports addition on the encrypted domain. Full homomorphism over addition and multiplication, which is necessary for enabling general-purpose computation, is achieved by inventing a heuristically obfuscated software re-encryption module written using Cryptoleq instructions and blended into the executing program. Cryptoleq is heterogeneous, allowing mixing encrypted and unencrypted instruction operands in the same program memory space. Programming with Cryptoleq is facilitated using an enhanced assembly language that allows the development of any advanced algorithm on encrypted data sets. In our evaluation, we compare Cryptoleq's performance against a popular fully homomorphic encryption library, and demonstrate correctness using a typical private information retrieval problem.

Secure of personal health records shared in cloud computing using cipher-text attribute based encryption

Storing critical medical data in third parties like semi-trusted cloud servers can be the subject of cloud data rupture incidents that happened intensively in recent years, for this reasons, secure methods become the most important issue in healthcare domain. This paper presents a design and development of personal healthcare record PHR system, as well as the security process of the data while stored at un-trusted or semi-trusted party. Through our system, patients can participate on the control over access to their own PHR. In order to achieve the security of PHRs, we use a combination between the advanced encryption standard AES and the attribute based encryption ABE to encrypt the data before outsourcing it, and elliptic curve cryptography ECC that secured the exchange of the users' private key. The proposed scheme guarantees a high degree of patients privacy, and owner full control of his medical data.

Provably Security Identity-based Sanitizable Signature Scheme Without Random Oracles

A sanitizable signature scheme is a signature which allows a semi-trusted party called sanitizer to hide parts of the original message after the message is signed, without interacting with the signer. A verifier can confirm the integrity of disclosed parts of the sanitized document from the signature. Sanitizable signatures are quite useful in governmental or military offices, where there is a dilemma between disclosure requirements of documents and private secret. In this paper, we give a formal definition and secure model of identity-based sanitizable signature by combining identity-based cryptography and sanitizable signature. Motivated by Waters’ signature scheme, we present an identity-based sanitizable signature scheme without random oracles (in the standard model) using bilinear pairing. Finally, security analysis shows that our proposed scheme satisfies all the security requirements.

Sanitizable Signatures Reconsidered

A sanitizable signature scheme allows a semi-trusted party, designated by a signer, to modify pre-determined parts of a signed message without interacting with the original signer. To date, many sanitizable signature schemes have been proposed based on various cryptographic techniques. However, previous works are usually built upon the paradigm of dividing a message into submessages and applying a cryptographic primitive to each submessage. This methodology entails the computation time (and often signature length) in linear proportion to the number of sanitizable submessages. We present a new approach to constructing sanitizable signatures with constant overhead for signing and verification, irrespective of the number of submessages, both in computational cost and in signature size.

Fair threshold decryption with semi-trusted third parties

A threshold decryption scheme is a multi-party public key cryptosystem that allows any sufficiently large subset of participants to decrypt a ciphertext, but disallows the decryption otherwise. Many threshold cryptographic schemes have been proposed so far, but fairness is not generally considered in this earlier work. In this paper, we present fair threshold decryption schemes, where either all of the participants can decrypt or none of them can. Our solutions employ semi-trusted third parties (STTP) and offline semi-trusted third parties (OTTP) previously used for fair exchange. We consider a number of variants of our schemes to address realistic alternative trust scenarios. Although we describe our schemes using a simple hashed version of ElGamal encryption, our methods generalise to other threshold decryption schemes and threshold signature schemes as well.