Multiple Data Users Research Articles

Multi-ciphertext equality test heterogeneous signcryption scheme based on location privacy

The scale of network communication users is increasing daily, and massive user information are interacted with and stored in the network. The exchange of information between entities in different communication environments will not only promote the dynamic development of culture and economy, but also bring the risk of data redundancy and privacy leakage, which will have many negative effects. With the development of digitalization of privacy information on the Internet, incidents of privacy data leakage continue to occur. Interacting with network data not only provides each communication user with a shared space for personal information but also poses a great risk of exposing user privacy data. To solve the above problems, our work proposes a heterogeneous signcryption scheme for multi-party and multi-ciphertext equality test. In the scheme, the communication users in the Identity-Based Cryptosystem (IBC) and the Certificateless Cryptosystem (CLC) can communicate securely in many ways; Different cryptographic systems use different system parameters. In addition, our scheme has the advantage of high communication efficiency compared with the equality test of a single ciphertext. The signcryption system based on IBC and CLC is adopted, which eliminates the problem of certificate management in the traditional public key cryptosystem and ensures the confidentiality and authentication of data. The introduction of multi-ciphertext equality test can enable secure retrieval of multiple ciphertexts by multiple data users at the same time and improve the efficiency of ciphertext retrieval in multi-user environments. Under the random oracle model, the proposed scheme has proved to satisfy unforgeability, confidentiality under the computational Diffie–Hellman problem. Experimental results indicate that our proposal achieves better performance.

An optimized and efficient multiuser data sharing using the selection scheme design secure approach and federated learning in cloud environment

An optimized and efficient multiuser data sharing using the selection scheme design secure approach and federated learning in cloud environment

A Sanitizable Access Control With Policy-Protection for Vehicular Social Networks

As an emerging field of communication, Vehicular Social Networks (VSNs) can reduce traffic congestion while enhancing road safety by sharing data among groups of commuters. In VSNs, Vehicular Cloud Server (VCS) based data sharing technology with encrypted primitives allows local users to outsource encrypted data for reducing the storage burden on the user side and sharing data without location restrictions. However, existing data encryption solutions that have been applied in VSNs environments still encounter weaknesses in efficiency, security, or privacy due to the following problems: (1) lack of effective access policies for flexible authorizing ciphertext to multiple data users; (2) data breaches caused by malicious data publishers; (3) necessity in hiding the private information of receivers. To date, no such solution has been available that securely enables one-to-many user authorization with privacy protection, while greatly resisting malicious data publishers. We propose a Sanitizable Access Control System with Policy-protection (SASP) for VSNs in this paper. Our SASP enables a sanitizer to test and sanitize encrypted data to defend against malicious data publishers, ensuring that the plaintext can only be recovered if an authorized user has a valid key. Furthermore, in our SASP system, the access policy is separated into attribute names and attribute values. Wherein, the attribute values contain a lot of private information, which is hidden in the ciphertext to guarantee data users’ privacy. Rigorous security analysis and performance evaluations demonstrate the practicality of SASP for VSNs.

Enabling Traceable and Verifiable Multi-User Forward Secure Searchable Encryption in Hybrid Cloud

Forward secure searchable encryption (FSSE) scheme allows one data user to search on encrypted databases while resisting the file injection attack. The data utilization can be further improved by extending the single-user scenario to the multi-user scenario. However, there are some issues needed to be considered when a data owner shares data with multiple data users. First, the public cloud server can not be completely trusted as it may be dishonest returning incorrect or incomplete results. Second, authorized users may trade their private keys for financial benefit. To our knowledge, state-of-the-art searchable encryption schemes only consider part of the following desirable features: the verifiability of results, the resistance to file injection attacks, the traceability and revocation of malicious users who abuse their private keys in the multi-user setting. Based on these motivations, we first propose enabling traceable and verifiable multi-user FSSE, which achieves the above functionalities. Besides, we carry out the security proof which demonstrates that our scheme can meet the requirements of security. We also assess the performance from theoretical analysis and experimental analysis, which shows that compared with other similar schemes, our scheme has richer functionalities with comparable efficiency.

A designated tester-based certificateless public key encryption with conjunctive keyword search for cloud-based MIoT in dynamic multi-user environment

One of the essential technologies in the medical industry for achieving high performance and accuracy is the Medical Internet of Things (MIoT). The MIoT technology processes a large amount of patient information in real-time. And therefore, it poses a high risk of leaking personal information. Furthermore, as data is sent over public networks, security is critical in MIoT. To overcome the above issues, we developed a designated tester-based Certificateless Public-key Encryption with Conjunctive Keyword search for cloud-based MIoT in dynamic multi-user environment (dCL-PECK). This study explores three features: (1). A secure channel is not necessary to transfer the data from the data-user (i.e., data owner or data receiver) to the designated tester (i.e., medical cloud server) and allows only the designated tester to execute the test algorithm. (2). Data is encrypted only once for multiple data users and supports conjunctive keyword search. (3). Users are added and revoked dynamically. Furthermore, the proposed scheme is provably secure under ciphertext indistinguishable against inside and outside adversaries and trapdoor indistinguishable against outside adversaries. Finally, theoretical and experimental analyses have been performed, demonstrating that the proposed system is better than similar Certificateless Keyword Search (CLKS) systems. As a result, we feel that it is suitable for cloud-based MIoT.

Scaling mmWave WLANs With Single RF Chain Multiuser Beamforming

Multi-user transmission in 60 GHz Wi-Fi can achieve data rates up to 100 Gbps by multiplexing multiple user data streams. However, a fundamental limit in the approach is that each RF chain is limited to supporting one stream or one user. In this paper, we scale multi-user 60 GHz WLAN data rate by overcoming this limit and propose SIngle RF chain Multi-user BeAmforming (SIMBA), a novel framework for multi-stream multi-user downlink transmission via a single RF chain. We build on single beamformed transmission via overlayed constellations to multiplex multiple users’ modulated symbols such that grouped users at different locations can share the same transmit beam from the AP. For this, we introduce user grouping and beam selection policies that span tradeoffs in data rate, training, and computation overhead. We implement a programmable WLAN testbed using software-defined radios and commercial 60 GHz transceivers and collect over-the-air measurements for different indoor WLAN deployments using a 12-element phased antenna array as well as horn antennas with varying beamwidth. We show that in comparison to single-user transmissions, SIMBA achieves <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$2\times $ </tex-math></inline-formula> improvement in aggregate rate and two-fold delay reduction for simultaneous transmission to four users.

AoI-Minimal Task Assignment and Trajectory Optimization in Multi-UAV-Assisted IoT Networks

This article investigates an unmanned-aerial-vehicle (UAV)-assisted Internet of Things system, where multiple UAVs take off from a data center (DC), collect data from multiple ground sensor nodes (SNs), distribute data for multiple users, and finally return to DC. A centralized information-sharing mechanism is designed among UAVs before data distribution, such that UAVs’ repeatedly visiting the same user can be avoided to save energy and time. A nonconvex Age-of-Information (AoI) minimization problem is formulated, where the task assignment, selection of interaction point (IPT), and UAVs’ trajectories are optimized jointly. It is decomposed into two subproblems: one is a joint task assignment and UAV trajectory optimization problem, which is solved by a multipopulation-based genetic algorithm (MPGA), as well as a hybrid algorithm combining dynamic programming (DP) with an improved <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$K$ </tex-math></inline-formula> -means clustering; and the other is an IPT selection problem, which is modeled as a Fermat–Weber location problem and is solved by the convex optimization technique. Simulation results show that the MPGA performs better than the hybrid algorithm as well as several benchmark algorithms.

Efficient and Secure Multi-Keyword Ranked Search and Group Data Sharing for Encrypted Cloud Data

Nowadays due to the popularity of clouds and their quality services, many of the users such as organizations, industries as well as individuals are migrating towards the cloud to store their important, confidential data and get easy access to their data anywhere anytime over the internet. Different encryption techniques are employed in cloud computing to ensure data confidentiality, security, and privacy. This makes it harder for endusers to retrieve precise data. Due to the huge amount of data over the cloud and multiple data users, secure data storage and retrieval are required. So in this paper develop an efficient data group sharing and multi-keyword ranked search method for encrypted cloud data collection in this research work. The developed system is implemented using the El-Gamal cryptography algorithm to provide security through effective key generation techniques and encryption strategy. Here, a multi-owner data setting is used instead of a centralized data owner setting; each member of the system in one particular group gets equal rights for both searching and sharing functionality and this may increase system usability. By taking into consideration lots of data in the cloud, the vector space model and TF-IDF model are utilized and according to the cosine similarity score, the method generates a ranked multikeyword search result to deliver effective query result from numerous data and enhance secrecy in the situation of numerous data owners. In this system searching efficiency is improved by developing an index-based search structure. In the group, data can disperse with co-owners/users by developing a role-based access policy (RBAP), and a user revocation strategy is developed with low computation time as well as communication overhead. At last, the efficiency and security of a developed system are exhibited by broad exploratory assessment.

An efficient 2D encoding/decoding technique for optical communication system based on permutation vectors theory

One dimensional encoding in optical communications has limitations in terms of the number of supported users and large bandwidth consumption. This study presents a new algorithm to generate two-dimensional (2D) encoding utilizing permutation vectors (PV) theory for incoherent multiple access network to suppress multiple access interference (MAI) and system complexity. The proposed code design approach is based on spectral/spatial techniques for code generation. All possible combinations of PV code-sets are obtained by utilizing all permutations of the vectors with the repetition of each vector weight (W) times. Furthermore, the 2D-PV code-set is constructed by combining two code sequences of the 1D-PV code. Furthermore, the transmitter–receiver architecture of the 2D-PV spectral/spatial (S/S) code based OCDMA system is presented. The Gaussian approximation is used to analyze the performance of the proposed OCDMA system with 2D- PV code by considering various noise sources (shot, thermal, and PIIN). Results indicate that the 2D-PV code provides increased cardinality by eliminating phase induced intensity noise (PIIN) effects with a minimum likelihood of interference between multiple user data. Simulation implementations validate the proposed system performance for an agreeable bit error rate (BER) of 10–9

Secure Fine-Grained Keyword Search With Efficient User Revocation and Traitor Tracing in the Cloud

Fine-grained searching is an important feature in multi-user cloud environment and a combination of attribute-based encryption (ABE) and searchable encryption (SE) is used to facilitate it. This combination provides a powerful tool where multiple data owners can share their data with multiple data users in an independent and differential manner. In this article, the authors have used key-policy design framework of attribute-based encryption to construct the multi-keyword search scheme where access rights assigned to a data user are associated with his/her secret key. This leads to a situation where a data user can abuse his secret key to distribute it illegally to the unauthorized users to perform search over the shared data which is not intended for him/her. Therefore, to track such kind of key abusers the authors have embedded an extra functionality of tracing the traitors. For this purpose, each user is assigned a unique identity in the form of binary string where each bit represents an attribute related to his identity. In addition to the normal attributes, the access structure of a user also possesses identity-related attributes which are hidden from the user along with some normal attributes. Hence, the proposed scheme supports partial anonymity. Further, in the event of user revocation the proposed scheme efficiently handles the system update process by delegating the computationally intensive tasks to the cloud server. Finally, the proposed scheme is proved secure under Decisional Bilinear Diffie-Hellman (DBDH) assumption and decision linear assumption in the selective security model.

Uplink transceiver design for coded GFDMA systems

In the generalized frequency division multiplexing (GFDM) technique, non-orthogonal pulse shapes are used to transmit data symbols on both time and frequency. This procedure causes self-interference among transmitted symbols. Recently, a modified version of GFDM, coded GFDM (CGFDM), has been introduced in which the transmitter matrix is unitary, avoiding the noise enhancement during self-interference cancellation. In this paper, we generalize the CGFDM for the multiuser uplink transmission scenario, and develop a zero-forcing (ZF) receiver to detect the data of multiple users. Simulation results show that the proposed ZF receiver outperforms the conventional ZF based generalized frequency division multiple access (GFDMA) receiver when the prototype filters are less localized and the number of subsymbols is high; however, with an increase in computational complexity. Moreover, a receiver with remarkably lower computational complexity is proposed based on the unitarity of the transmitter matrix in CGFDM and the assumption of relatively low frequency selectivity of the communication channels. This low-complexity receiver provides the same bit error rate (BER) performance of the ZF receiver in the low to mid range SNRs.

Two-Dimensional Permutation Vectors' (PV) Code for Optical Code Division Multiple Access Systems.

In this paper, we present a new algorithm to generate two-dimensional (2D) permutation vectors’ (PV) code for incoherent optical code division multiple access (OCDMA) system to suppress multiple access interference (MAI) and system complexity. The proposed code design approach is based on wavelength-hopping time-spreading (WHTS) technique for code generation. All possible combinations of PV code sets were attained by employing all permutations of the vectors with repetition of each vector weight (W) times. Further, 2D-PV code set was constructed by combining two code sequences of the 1D-PV code. The transmitter-receiver architecture of 2D-PV code-based WHTS OCDMA system is presented. Results indicated that the 2D-PV code provides increased cardinality by eliminating phase-induced intensity noise (PIIN) effects and multiple user data can be transmitted with minimum likelihood of interference. Simulation results validated the proposed system for an agreeable bit error rate (BER) of 10−9.

Public key encryption with conjunctive keyword search on lattice

Outsourcing data in cloud storage is gaining popularity recently. For protecting data privacy, the data should be encrypted, and it is thus critical to provide search services for encrypted outsourced data. However, it becomes a problem about how to retrieve encrypted data while protecting data privacy at the same time. Therefore, public key encryption with keyword search (PEKS) is proposed. Nevertheless, the majority of the existing PEKS schemes are based on bilinear mappings and do not provide quantum security. Although some lattice-based PEKS schemes have been proposed, they cannot support conjunctive keyword search. In this paper, we first propose a public key encryption with conjunctive keyword search (PECK) using lattices. Our PECK scheme provides efficient search over encrypted data containing multiple keywords for a single data user. To support multiple data users, a multi-user PECK scheme is also presented. The two schemes are proved secure against indistinguishable chosen keyword attacks (IND-CKA) based on learning with errors (LWE) problem in the random oracle model. Finally, we provide performance evaluation of our proposed scheme by theoretical analysis and experimental simulation.

Union Bound Analysis and Code Design for Multilevel Flash Memory Channels

Multilevel flash memories enable multiple bits to be stored in a single memory cell and hence a significant increase of the storage capacity. The multiple bits that are used for labeling the threshold voltage level of a memory cell belong to different pages. A multilevel flash memory channel resembles a multi-user channel with asymmetric noise, while the data of different pages, which are encoded independently, resembles data of multiple users. In this paper, performance analyses are proposed for this channel by using the union bound technique. In particular, we investigated two different binary labeling schemes of a cell level, the Gray labeling and non-Gray labeling with three maximum-likelihood (ML)-based decoding schemes, which are the joint multi-page ML decoding, page-separate ML decoding, and default setting ML decoding. Our analysis reveals an asymptotic diminishing rate of decoding errors as the channel noise approaches zero, based on which the code design criteria are proposed. It is shown theoretically that the Gray mapping has no joint (i.e., multi-page) decoding gain. The corresponding diminishing decoding error rate is dominated by the weakest code in each page and hence a separate decoding scheme is adequate. On the other hand, the non-Gray mapping has a joint decoding gain which means the weak code can exploit the decoding of the strong code and the diminishing rate of its decoding errors is not subject to the cask effect. Therefore, for Gray mapping, a symmetric coding scheme using equal-strength code for each page achieves better error performance, while for non-Gray mapping with joint decoding, the symmetric coding is not necessary. Moreover, by using the asymmetric coding scheme through assigning different code rates to different pages, the non-Gray mapping can achieve higher overall sum rate than Gray mapping with a similar decoding error rate performance.

Multiuser Variable Rate GO-OFDMA Architecture and Its FPGA Prototype

With the advancements in next-generation communications systems, the demand for integration of services, such as video, audio, text, image of variable rates, etc., is a challenging issue. Internet of Things needs to integrate billions of devices and sensor nodes with different sampling rates. To integrate these services of multiple devices with variable rates, group orthogonal–orthogonal frequency division multiple access (GO-OFDMA) is an efficient multicarrier scheme. But to the authors’ knowledge and literature survey, there is no hardware architecture of GO-OFDMA for real-time testing. Therefore, a new architecture is proposed for GO-OFDMA baseband transmitter and receiver and prototyped on commercially available virtex5 field-programmable gate array (FPGA) device. Further challenges of this proposed architecture are integration of multiple user data with variable rates in the baseband transmitter and decoding of multiple user data within the same class at the baseband receiver. To validate the GO-OFDMA baseband transmitter and receiver, the transmitted and received bits in real time are captured using chipscope analyzer. The bit error rate and peak-to-average power ratio performance of the proposed architecture are presented. The hardware resource utilization of the GO-OFDMA architecture along with the maximum operating frequency is also reported.

Singular value decomposition assisted multicarrier continuous-variable quantum key distribution

We define the singular value decomposition (SVD) assisted multicarrier continuous-variable quantum key distribution (CVQKD) protocol. The proposed protocol uses the singular value decomposition of the Gaussian quantum channel, which yields an additional degree of freedom for the phase space transmission. This additional degree of freedom can further be exploited in a multiple-access scenario. The SVD-assistance defines the eigenchannels of the Gaussian physical link, which can be used for the simultaneous reliable transmission of multiple user data streams. Our transmission model also includes the singular interference avoider (SIA) precoding scheme. The proposed SIA precoding scheme prevents the eigenchannel interference to reach an optimal transmission over a Gaussian link. We demonstrate the results through the adaptive multicarrier quadrature division–multiuser quadrature allocation (AMQD-MQA) CVQKD multiple-access scheme. The singular value assisted transmission provides improved simultaneous transmission rates for the users, particularly in crucial low signal-to-noise ratio regimes.

Multi-Writer Multi-Reader Conjunctive Keyword Searchable Encryption

We explore the area of searchable encryption aiming to identify the schemes supporting multiple data owner (writers) and multiple data users (readers). Especially, we observe multi-writer multi-reader (MWMR) searchable encryption schemes focusing on multi-keyword search. However, such MWMR schemes offer a centralised token generation approach whereby an enterprise trusted authority (ETA) issues a search token to each reader in system, and thus introduce two serious issues, viz. leakage of keywords to ETA and O(q · R) communication overhead for R readers and q queries per reader. In this paper, we alleviate these issues by proposing an MWMR scheme with a decentralised token generation approach. With such an approach, a registered data reader constructs a search token without interacting with ETA and thus provides an efficient token generation with keyword privacy from ETA. Additionally, we incorporate a more expressive especially, conjunctive keyword search with the scheme. With formal security analysis, we prove that the scheme effectively stands against chosen keyword attack performed by inside or outside attacker. With theoretical and empirical analysis, we justify the effectiveness of the proposed scheme.

An Efficient Outsourced Privacy Preserving Machine Learning Scheme With Public Verifiability

Cloud computing has been widely applied in numerous applications for storage and data analytics tasks. However, cloud servers engaged through a third party cannot be fully trusted by multiple data users. Thus, security and privacy concerns become the main obstructions to use machine learning services, especially with multiple data providers. Additionally, some recent outsourcing machine learning schemes have been proposed in order to preserve the privacy of data providers. Yet, these schemes cannot satisfy the property of public verifiability. In this paper, we present an efficient privacy-preserving machine learning scheme for multiple data providers. The proposed scheme allows all participants in the system model to publicly verify the correctness of the encrypted data. Furthermore, a unidirectional proxy re-encryption (UPRE) scheme is employed to reduce the high computational costs along with multiple data providers. The cloud server embeds noise in the encrypted data, allowing the analytics to apply machine learning techniques and preserve the privacy of data providers’ information. The results and experiments tests demonstrate that the proposed scheme has the ability to reduce computational costs and communication overheads.

Achieving Semantic Secure Search in Cloud Supported Information-Centric Internet of Things

With the support of cloud computing, the scalability of the information-centric Internet of Things (IC-IoT) can be increased greatly. In the cloud-supported IC-IoT, how to make search more secure and efficient is a key issue to deal with. Searchable encryption is a potential technique to solve the above problem. In the cloud-supported IC-IoT, sensitive data are provided by multiple data users and can be accessed by specific data users. Then, the expression ability, search authorization, dynamic updates, and search efficiency become major concerns of search in the cloud-supported IC-IoT. In this paper, SASDQ, a semantic and authorized search scheme with dynamic updates and quick response, is proposed. In SASDQ, by constructing users’ personal dictionaries, dynamic updates and efficient index generation are achieved, and by leveraging ciphertext policy attribute-based encryption and conceptual graphs, semantic search with file-level fine-grained access authorization can be realized. In addition, quick search response is implemented by the preprocessing of time-consuming authorization tasks. The analysis shows that the proposed scheme can meet the data security requirement of the cloud-supported IC-IoT, and it also has less cost compared with other popular models.

Focus on Area Tracking Based on Deep Learning for Multiple Users

Most eye-tracking experiments are limited to single subjects because gaze points are difficult to track when multiple users are involved and environmental factors might cause interference. To overcome this problem, this paper proposes a method for gaze tracking that can be applied for multiple users simultaneously. Four models, including FASEM, FAEM and FAFRCM in the signal-user environment, as well as FAEM and FAMAM in the multiple-user environment, are proposed, and we collected raw data of gazing behaviors to train the models. Through a modified VGG19 architecture and adjusting the Number of Convolutional Layers (NoCL), we obtained and compared the accuracy of various models to determine the most suitable architecture. Since data for multiple-users is not easy to obtain, in this paper, we trained the model first with single users, then extended it to multiple users with transfer learning. Finally, we propose an adaptive method to integrate the benefits of FAEM and FAMAM.