Identity-based Data Research Articles

Campus climate assessment and action: disaggregating the social work experience in Canada

ABSTRACT Climate surveys hold the potential to advance equity in organizations, serving to generate quantitative data on the depth and breadth of climate-related issues, with its forte being those related to belonging, inclusion, and relationships. When administered in a university, it holds the potential to signal the need for improvements, as climate has been associated with engagement, motivation, wellbeing, and retention. The Faculty of Social Work, where an MSW and PhD program are located (Kitchener, Canada), conducted a climate survey in 2020. This article reports on the survey’s content, key findings, action outcomes, and provides recommendations for others considering such an initiative. The survey was a wake-up call for the department, with five concrete outcomes including establishing student caucus groups, a faculty capacity-development initiative to improve teaching, trainings to address microaggressions, improved integration of EDI into hirings, and campaigns to collect identity-based data for faculty and students. We also share two pending initiatives and two derailed initiatives. Recommendations emphasize the importance of disaggregating results to ensure that disparities are identified in the organization.

Identity-Based Data Auditing Scheme With Provable Security in the Standard Model Suitable for Cloud Storage

Identity-Based Data Auditing Scheme With Provable Security in the Standard Model Suitable for Cloud Storage

A Brief Systematics Review and Visualization of Smart Cities based on Fog and Big Data Analysis Technology

The fog computing is based on IoT, and same as clouds are on the edge of a network between a device and the cloud, which can provide very close service to the device in real time. cloud computing frameworks also extend support to emerging application paradigms such as IoT, Fog computing, Edge, and Big Data through service and infrastructure. the ubiquitous deployment of sensors in smart cities requires a high-performance computing paradigm to support big data analysis with smart technologies and communications in IoT, providing location-awareness and latency-sensitive computing near the data sources (i.e., at the edge of the network). Cloud Computing paradigms widely used in enterprises to address the emerging challenges of big data analysis because of its scalable and distributed data management scheme. However, data centers in the Cloud faces great challenges on the burden of exploding amount of big data and the additional requirements of location awareness and low latency at the edge of network necessary for smart cites. the widely distributed sensor networks generate massive volume of data, which leads to a “Big Data “analysis challenge. The machine-to-machine(M2M) communication among massive numbers of sensors will dominate future communication network traffic, namely Internet of Things, instead of traditional Internet of Contents (IoC) in human-to-human and human-to-machine communication. In this review system where we took the research article around 33 from the different database and also taken 1987 datasets form the PubMed database from 1959 to 2024 (02 June 2024). In addition, depending on the different requirement which is partially processed the data. Then the gathered data is stored at the ledger unit through the smart cities based on the fog computing and big data technology. The hashing identity-based data encryption is a public key encryption which uses a digital signature to encrypt the data to prevent the information from the third party.

Privacy-Preserving Identity-Based Data Rights Governance for Blockchain-Empowered Human-Centric Metaverse Communications

Privacy-Preserving Identity-Based Data Rights Governance for Blockchain-Empowered Human-Centric Metaverse Communications

Efficient Identity-Based Data Integrity Auditing With Key-Exposure Resistance for Cloud Storage

The key exposure is a serious threat for the security of data integrity auditing. Once the user's private key for auditing is exposed, most of the existing data integrity auditing schemes would inevitably become unable to work. To deal with this problem, we construct a novel and efficient identity-based data integrity auditing scheme with key-exposure resilience for cloud storage. This is achieved by designing a novel key update technique, which is fully compatible with BLS signature used in identity-based data integrity auditing. In our design, the Third Party Auditor (TPA) is responsible for generating update information. The user can update his private key based on the private key in one previous time period and the update information from the TPA. Furthermore, the proposed scheme supports real lazy update, which greatly improves the efficiency and the feasibility of key update. Meanwhile, the proposed scheme relies on identity-based cryptography, which makes certificate management easy. The security proof and the performance analysis demonstrate that the proposed scheme achieves desirable security and efficiency.

An efficient and secure identity-based integrity auditing scheme for sensitive data with anti-replacement attack on multi-cloud storage

The rapid growth of cloud storage brings forth significant difficulties in ensuring the integrity of data owners' sensitive data. Multi-cloud storage systems, which motive to enhance trustworthiness, are vulnerable to rigorous replacement attacks. These insidious attacks involve malicious actors substituting legitimate data with counterfeit versions, leading to compromised integrity and fraudulent audit outcomes. We propose a novel identity-based data integrity auditing protocol tailored for multi-cloud storage environments to tackle this challenge. Our protocol leverages a Third-Party Auditor (TPA) to delegate data authenticity and auditing responsibilities, employing identity-based blind signatures with a robust data recovery scheme. By eliminating the need for cumbersome public key certificate management, our solution effectively protects data owners' sensitive data while ensuring confidentiality across multiple cloud providers, thereby mitigating the risk of replacement attacks. A thorough security examination shows the proposed system resists forging, replacement attacks, and data confidentiality violations. A rigorous performance experiment also reveals outstanding computational and communication efficiency that outperforms current methods in tag production, proof generation, and verification. Our protocol offers an extraordinary balance of security and efficiency, making it particularly useful for auditing patent-sensitive data in multi-cloud storage. Our proposal provides a timely and effective way to protect sensitive data and prevent attackers in multi-cloud storage settings at a time when replacement attacks pose a serious concern.

Efficient identity-based traceable cloud data broadcasting with outsider anonymity and simultaneous individual transmission

In recent years, cloud data broadcasting system has attracted intensive attention due to its universal applicability in various Internet-of-Things enabled real-life scenarios. Cloud data broadcasting with simultaneous individual transmission is an exciting data broadcasting variant that empowers any data broadcaster to distribute encrypted broadcast data to a subscribed consumer group and the personalized transmission to each group member simultaneously. Recently [IEEE Transactions on Broadcasting (2020)], a certificate-based data broadcasting with simultaneous individual transmission scheme (Chen et al., 2020) is proposed with the aim to solve both key-escrow problem and certificate management problem, and it is claimed to provide subscriber’s outsider anonymity under the nonstandard q-type security assumption with the existence of random oracles. Unfortunately, we can show that this most recent work of Chen et al. (2020) is not secure against insider attacks, meaning that their protocol cannot trace the system’s traitor consumers who can resell the sensitive information for their own profit without valid authorization. Besides, the design of Chen et al. (2020) has significantly high communication bandwidth that is approvingly inconvenient for the Internet-of-Things facilitated low-powerful multimedia devices to reduce unnecessary burden on the encryption costs. We design a provably secure adaptive identity-based data broadcasting technique having simultaneous individual transmission with unbounded number of consumers that can concatenate two mutually orthogonal functionalities, namely consumer’s outsider anonymity and traitor consumer traceability, in a cost-efficient way. Our framework exploits the most secure and advanced asymmetric Type-3 bilinear maps to defend against fault attacks and realizes security in the standard provable security model without the existence of any random oracle. On a positive note, our construction eliminates the q-type security assumption that is so far a plausible achievement compared to all the existing schemes in this area.

Ldasip: A Lightweight Dynamic Audit Approach for Sensitive Information Protection in Cloud Storage

How to audit the integrity of data stored on the cloud with incomplete trust is an important problem that restricts the development of cloud storage. Although there are several data integrity audit schemes in cloud storage, the increased need to protect sensitive information and support large-scale data storage and dynamic update will result in a significant increase in audit cost, which seriously affects the efficiency of existing cloud audit systems. To solve this problem, we propose Ldasip, a lightweight dynamic auditing method that supports sensitive information protection in cloud storage. Exploiting identity-based data integrity audit, a data masking technology is introduced into to protect user’s sensitive information. At the same time, an improved multibranch tree structure is proposed to realize dynamic audit and reduce communication overhead in the verification process. Theoretical analysis and comprehensive experiments have been conducted, which demonstrate the effectiveness of Ldasip. The results show that Ldasip can ensure the correctness of the audit, protect the sensitive information in the user's stored content, and support the dynamic update of data with less audit time and communication overhead.

Identity-based secure data aggregation in big data wireless sensor networks

Identity-based secure data aggregation in big data wireless sensor networks

An Identity-Based Data Integrity Auditing Scheme for Cloud-Based Maritime Transportation Systems

With the development of Internet of Things (IoT)-enabled Maritime Transportation Systems (MTS), massive data generated in the system not only requires to be stored reliably and cheaply, but also needs to be analyzed timely. The Cloud-based Maritime Transportation Systems (CMTS) allow users to upload the data without worrying about the price, capacity, location and so on. However, CMTS also brings some security issues, where the integrity protection of outsourced data is one of the most important issues since it is crucial for the safety, reliability and efficiency of sea lanes. To solve this problem, we propose an identity-based dynamic data integrity auditing scheme for CMTS. Our scheme decreases the burden of key management and improves the auditing efficiency by batch auditing. Besides, our scheme also supports dynamic operations on the outsourced data for CMTS. The security analysis shows that our scheme can ensure the feature of storage correctness and resist common attacks. In addition, the performance comparison results with other related schemes show that our scheme not only has the lowest computational cost on all entities, but also greatly reduces the communication overhead of the auditing phase. Therefore, our scheme is very suitable for data integrity verification in CMTS.

DOPIV: Post-Quantum Secure Identity-Based Data Outsourcing with Public Integrity Verification in Cloud Storage

Public verification enables cloud users to employ a third party auditor (TPA) to check the data integrity. However, recent breakthrough results on quantum computers indicate that applying quantum computers in clouds would be realized. A majority of existing public verification schemes are based on conventional hardness assumptions, which are vulnerable to adversaries equipped with quantum computers in the near future. Moreover, new security issues need to be solved when an original data owner is restricted or cannot access the remote cloud server flexibly. In this paper, we propose an efficient identity-based data outsourcing with public integrity verification scheme (DOPIV) in cloud storage. DOPIV is designed on lattice-based cryptography, which achieves post-quantum security. DOPIV enables an original data owner to delegate a proxy to generate the signatures of data and outsource them to the cloud server. Any TPA can perform data integrity verification efficiently on behalf of the original data owner, without retrieving the entire data set. Additionally, DOPIV possesses the advantages of being identity-based systems, avoiding complex certificate management procedures. We provide security proofs of DOPIV in the random oracle model, and conduct a comprehensive performance evaluation to show that DOPIV is more practical in post-quantum secure cloud storage systems.

CB-DA: Lightweight and Escrow-Free Certificate-Based Data Aggregation for Smart Grid

Recent development of smart cities includes advanced and necessary use of modern smart grid (SG), than the traditional power grid. The paradigm of SG has also transformed houses into a home area networks (HAN). In HAN, several smart devices and appliances are connected to the electricity control centers (ECC). Appliances share their load and consumption related information to ECC through smart meters. The consumption data may be used for supply-demand management, for example, by ramping production up or down as needed. However, security and privacy of the consumers data are greatly important, since fine-grained smart meter data may reveal an users presence/absence in his/her house. To address this issue, several public-key-based or identity-based data aggregation schemes have been proposed in the literature. However, most of such schemes either suffer from the complexity of certificate management or key escrow problem. To eliminate these issues, in this paper we propose an efficient certificate-based data aggregation (CB-DA) scheme. In the proposed CB-DA scheme, the owner selects a secret key and then use the secret key along with certificates as decryption/signing keys.

Identity-Based Dynamic Data Auditing for Big Data Storage

Identity-based remote data auditing schemes can verify data integrity and provide a simple identity authentication and management for multiple users. However, prior works on identity-based remote data auditing lack the support of dynamic operations. In these schemes, tag generation is linked to the index of data block, which is related to update operations such as modification, insertion and deletion. If users perform dynamic operations on a data block, the tags of all subsequent blocks need to be modified. It means that if users want to update data on a big data platform, they have to download the whole file, update the file and send the updated file to the big data platform. Such pattern will bring huge communication overhead. In this paper, we propose an identity-based dynamic data auditing scheme which supports dynamic data operations, including modification, insertion and deletion. As far as we know, there is still no other identity-based data auditing scheme that supports dynamic operations. In particular, to achieve efficient dynamic operations, we use the data structure of Merkle hash tree for block tag authentication, which helps update data with integrity assurance. Analyses of security and performance show that the proposed scheme is efficient and secure.

Identity-based Provable Data Possession for Multicloud Storage with Parallel Key-Insulation

Identity-based Provable Data Possession for Multicloud Storage with Parallel Key-Insulation

Secure Data Group Sharing and Dissemination with Attribute and Time Conditions in Public Cloud

Cloud computing has become increasingly popular among users and businesses around the world. Although cryptographic techniques can provide data protection for users in public cloud, several issues also remain problematic, such as secure data group dissemination and fine-grained access control of time-sensitive data. In this paper, we propose an identity-based data group sharing and dissemination scheme in public cloud, in which data owner could broadcast encrypted data to a group of receivers at one time by specifying these receivers' identities in a convenient and secure way. In order to achieve secure and flexible data group dissemination, we adopt attribute-based and timed-release conditional proxy re-encryption to guarantee that only data disseminators whose attributes satisfy the access policy of encrypted data can disseminate it to other groups after the releasing time by delegating a re-encryption key to cloud server. The re-encryption conditions are associated with attributes and releasing time, which allows data owner to enforce fine-grained and timed-release access control over disseminated ciphertexts. The theoretical analysis and experimental results show our proposed scheme makes a tradeoff between computational overhead and expressive dissemination conditions.

Identity-based Data Possession Verification Scheme for Multi-Replica Storage in Cloud

In the cloud storage environment, how to efficiently and dynamically complete the integrity verification of multi-user and multi-replica data is a challenging problem. Based on the bilinear mapping signature mechanism and the multi-branch authentication tree, we propose an identity-based integrity verification scheme of multi-replica data for cloud, which solves the problem of large public key storage and management overhead in signature algorithm based on traditional public key cryptosystems. The proof shows that our scheme satisfies the robustness and has the function of protecting privacy. The results of analysis indicate that, compared with the existing similar schemes, our scheme has higher communication efficiency and computing performance.

Identity-Based Verifiable Aggregator Oblivious Encryption and Its Applications in Smart Grids

Verifiable aggregator oblivious encryption is a useful notion that not only allows an untrusted aggregator to compute aggregated data without learning any other information but also requires the aggregator to generate a proof of the aggregated data so that anyone can verify the accuracy. Since the aggregator does not learn data that may reveal users' private information and also cannot forge the aggregated data, verifiable aggregator oblivious encryption is suitable for privacy-preserving smart metering. However, NIST has recommended not using public-key-based cryptography in the smart grid because public-key cryptography cannot provide sufficient scalability. Thus, we propose a notion of identity-based verifiable aggregator oblivious encryption and design concrete schemes in this paper. We prove the aggregator oblivious security and aggregator unforgeability of our schemes via the smooth projective hash function and computational Diffie-Hellman assumption. Furthermore, based on our identity-based verifiable aggregator oblivious encryption scheme, we propose an identity-based data aggregation protocol for the smart grid and provide a security analysis in the context of seven typical attacks on smart grids. The implementation of our protocol via the Intel Edison platform shows that it is sufficiently lightweight for resource-constrained smart meters.

A Lightweight Identity-Based Remote Data Auditing Scheme for Cloud Storage

Cloud storage enables data owners to use any device to store and access data anytime, anywhere. In a data auditing scheme, the data owner can entrust a third party auditor (TPA) to verify that the outsourced data remains unchanged. A secure data auditing scheme not only detects whether cloud service providers (CSP) maintain data integrity, but also prevents TPA from stealing data. In this paper, a new identity-based data auditing (IBDA) scheme for cloud storage systems is proposed. In the scheme, the data owner generates the tags using its private key and data blocks, and then uploads the data blocks along with the tags to CSP. In the challenge-proof phase, before returning the proof information, CSP performs the addition operation between the hash function value and the data block to hide the data, thereby preventing TPA from stealing the data. This scheme is proved to be secure in the random oracle model. Analysis of efficiency shows that it is more efficient than other schemes.

Data for queer lives: How LGBTQ gender and sexuality identities challenge norms of demographics

In this article, we argue that dominant norms of demographic data are insufficient for accounting for the complexities that characterize many lesbian, gay, bisexual, transgender, and queer (LGBTQ, or broadly “queer”) lives. Here, we draw from the responses of 178 people who identified as non-heterosexual or non-cisgender to demographic questions we developed regarding gender and sexual orientation. Demographic data commonly imagines identity as fixed, singular, and discrete. However, our findings suggest that, for LGBTQ people, gender and sexual identities are often multiple and in flux. An overwhelming majority of our respondents reported shifting in their understandings of their sexual identities over time. In addition, for many of our respondents, gender identity was made up of overlapping factors, including the relationship between gender and transgender identities. These findings challenge researchers to reconsider how identity is understood as and through data. Drawing from critical data studies, feminist and queer digital media studies, and social justice initiatives like Data for Black Lives, we call for a reimagining of identity-based data as “queer data” or “data for queer lives.” We offer also recommendations for researchers to develop more inclusive survey questions. At the same time, we address the ways that queer perspectives destabilize the underlying logics of data by resisting classification and “capture.” For marginalized people, the stakes of this work extend beyond academia, especially in the era of algorithms and big data when the issue of who is or is not “counted” profoundly affects visibility, access, and power in the digital realm.

A Priority Based Efficient Secure Framework for WBANs

In this article, the authors propose a system to gather patient information continuously, perform proper non-intrusive checking, and propose restorative or potentially way of life engagements, at whatever point required and proper. The structure, which depends on administration arranged service as application(SOAs) and the Cloud, permits a consistent combination of various innovations, applications, also, administrations. It additionally integrates mobile advances to easily gather, convey imperative information from a patient's wearable biosensors while considering a cell phones' restricted abilities and control seepage, notwithstanding discontinuous system detachments. At that point, information is put away in the Cloud and made accessible by means of SOA to permit access by doctors, paramedics, or other approved authorities. A contextual investigation has been created to assess the convenience of the structure, and the preparatory outcomes that have been broken down are demonstrating exceptionally encouraging outcomes. To secure the data transmission, they have applied identity-based data encryption scheme. It enhances the security in the authors' framework.