Protect Data Confidentiality Research Articles

Secure Data Sharing With Flexible Cross-Domain Authorization in Autonomous Vehicle Systems

As an increasingly prevalent technology in intelligent autonomous transportation systems, autonomous vehicle platoon has been indicated the ability to significantly reduce fuel consumption as well as heighten highway safety and throughput. However, existing efforts rarely focus on protecting data confidentiality and authenticity in autonomous vehicle platoons. How to ensure secure and high-fidelity platoon-level communication is still in its infancy. This paper makes the first attempt for efficient and secure communication across autonomous vehicle platoons. Specifically, we present PDSM-FC, the first privacy-preserving data share mechanism with flexible cross-domain authorization over distinctive platoons. The key insight of PDSM-FC is the design of a new ciphertext conversion technique, which allows a ciphertext to be easily converted into another type of ciphertext, facilitating efficient access by all entities holding the legitimate authorization. As a result, PDSM-FC can achieve high-fidelity data communication between two unique platoons in ciphertext, so as to complete specific tasks including platoon integration. Rigorous security analysis shows that PDSM-FC is secure against various attacks such as collusion, forgery and chosen-plaintext attacks. Moreover, theoretical evaluation and extensive experiments demonstrate the practicability of PDSM-FC in terms of functionality, storage and computation overheads.

A Security Frame work for Data Storage in Cloud Computing by Using Cryptographic Approaches

Cloud computing has revolutionized the way data is stored, processed, and accessed. However, with the widespread adoption of cloud services, ensuring the security and privacy of data has become a paramount concern. This paper presents a comprehensive security framework for data storage in cloud computing, leveraging cryptographic approaches. The proposed framework aims to protect data confidentiality, integrity, and availability throughout its lifecycle in the cloud. It explores various cryptographic techniques, including encryption, access control mechanisms, and key management protocols. Additionally, the paper discusses the challenges and considerations associated with implementing cryptographic security measures in cloud storage and provides recommendations for a robust and efficient security framework.

Criminal for Leaking Administs Data of PDDIKTI and PSD-PTU According to Law Number 19 Year 2016 Concerning ITE

Protection for every citizen wherever they are is an obligation that must be fulfilled by a country. This is in accordance with the Preamble to the 1945 Constitution of the Republic of Indonesia in the 4th (fourth) paragraph. One form of recognition, guarantee, protection, and fair legal certainty as well as equal treatment before the law is the existence of adequate arrangements that are very close between the protection of confidential data from individual PDDikti admins and PSD-PTU a Lecturer, both at universities State Universities (PTN) and Private Universities (PTS). Private secrecy is very essential, especially related to the PDDikti and PSD-PTU data of a Lecturer, both at State Universities (PTN) and Private Universities (PTS), because that is where there are individual rights that must be protected by the State. The protection of personal data in the digital era has been regulated and stated in the form of Ministerial Regulation (Permen) No. 20 of 2016 concerning Personal Data Protection (PDP) stipulated November 7, 2016, promulgated and effective since December 1, 2016. The regulation states that Personal Data is data certain individuals who are kept, cared for, and the truth is protected and their confidentiality is protected because that is where there are individual rights that must be protected by the State which should be kept secret except for the interests of the State.

A zero trust and blockchain-based defense model for smart electric vehicle chargers

Electric vehicles (EVs) have rapidly developed over the last decade due to their environmental benefits. As a key component of EVs, electric vehicle chargers are becoming increasingly digital and intelligent. However, due to the vast attack surface and the lack of systematic study, EV chargers and charging management cloud platforms are facing cyber security problems. These problems include weak cryptographic mechanisms, insecure data communication, and malicious firmware attacks. Through specific vulnerabilities, attackers can tamper with the data communication or replay network requests between EV chargers and cloud platforms. It will cause threats such as user-level privacy leakage, power fluctuations in the smart grid, and damage to Electric vehicles, damaging public life and property safety. Given the above, this paper proposes a security protection scheme incorporating blockchain, zero trust, and ShangMi cryptographic (SM) algorithms. The scheme uses Hyperledger Fabric for key management and trust evaluation event storage to guarantee the authenticity, non-repudiation, and tamper-proof of keys and events. In addition, zero trust is applied to secure valuable resources and enforce identity and access management (IAM) for accessing entities. We adopt the dynamic trust evaluation method to assess the trustworthiness of accessing entities in real time to implement dynamic authorization. Furthermore, the SM algorithms SM2, SM3, and SM4 are used to protect data confidentiality, integrity, and authenticity. Experimental results demonstrate that our scheme can effectively resist replay and tampering attacks, securing data communication between EV chargers and cloud platforms. And the performance of the cryptographic algorithm, blockchain system, and Secure Sockets Layer (SSL) meets Chinese national and industry standards.

Masking Techniques for Confidential Data Protection in Privacy-Preserving Data Mining

Masking Techniques for Confidential Data Protection in Privacy-Preserving Data Mining

Blockchain Technology: Security Issues, Healthcare Applications, Challenges and Future Trends

Blockchain technology provides a data structure with inherent security properties that include cryptography, decentralization, and consensus, which ensure trust in transactions. It covers widely applicable usages, such as in intelligent manufacturing, finance, the Internet of things (IoT), medicine and health, and many different areas, especially in medical health data security and privacy protection areas. Its natural attributes, such as contracts and consensus mechanisms, have leading-edge advantages in protecting data confidentiality, integrity, and availability. The security issues are gradually revealed with in-depth research and vigorous development. Unlike traditional paper storage methods, modern medical records are stored electronically. Blockchain technology provided a decentralized solution to the trust-less issues between distrusting parties without third-party guarantees, but the “trust-less” security through technology was easily misunderstood and hindered the security differences between public and private blockchains appropriately. The mentioned advantages and disadvantages motivated us to provide an advancement and comprehensive study regarding the applicability of blockchain technology. This paper focuses on the healthcare security issues in blockchain and sorts out the security risks in six layers of blockchain technology by comparing and analyzing existing security measures. It also explores and defines the different security attacks and challenges when applying blockchain technology, which promotes theoretical research and robust security protocol development in the current and future distributed work environment.

Getting along with frenemies: enhancing multi-competitor coopetition governance through artificial intelligence and blockchain

ABSTRACT Collaborating with one competitor is difficult but collaborating with several competitors is a monumental challenge. However, multi-competitor coopetition, or cooperation between multiple competitors, is increasing. This study examines how recent advancements in artificial intelligence (AI) and blockchain can support multi-competitor coopetition by enhancing governance. Examining two coopetitive R&D consortia in pharmaceuticals and medical imaging, we find that a nascent form of AI called federated learning can address key coopetition concerns such proprietary and confidential data protection, knowledge leakage, data sovereignty and silos thereby maintaining organisational boundaries and autonomy. The use of federated learning and blockchain increases transparency and accountability, which reduces information asymmetries and power differential inequities. Together, these technologies decentralise governance and authority, reducing the tension between collective value creation and individual value appropriation inherent in coopetition, particularly those with multiple competitors. Finally, this study illustrates how emerging technologies challenge traditional assumptions about organisational boundaries, distributed innovation, and coopetition.

Securing Big Data Scientific Workflows via Trusted Heterogeneous Environments

Big data workflow management systems (BDWMS)s have recently emerged as popular data analytics platforms to conduct large-scale data analytics in the cloud. However, the protection of data confidentiality and secure execution of workflow applications remains an important and challenging problem. Although a few data analytics systems, such as VC3 and Opaque, were developed to address security problems, they are limited to specific domains such as Map-Reduce-style and SQL query workflows. A generic secure framework for BDWMSs is still missing. In this article, we propose SecDATAVIEW, a distributed BDWMS that employs heterogeneous workers, such as Intel SGX and AMD SEV, to protect both workflow and workflow data execution, addressing three major security challenges: (1) Reducing the TCB size of the big data workflow management system in the untrusted cloud by leveraging the hardware-assisted TEE and software attestation; (2) Supporting Java-written workflow tasks to overcome the limitation of SGX’s lack of support for Java programs; and (3) Reducing the adverse impact of SGX enclave memory paging overhead through a “Hybrid” workflow task scheduling system that selectively deploys sensitive tasks to a mix of SGX and SEV worker nodes. Our experimental results show that SecDATAVIEW imposes moderate overhead on the workflow execution time.

Reliable Policy Updating Under Efficient Policy Hidden Fine-Grained Access Control Framework for Cloud Data Sharing

Ciphertext-Policy Attribute-Based Encryption (CP-ABE) is one of the potent encryption paradigms in protecting data confidentiality in the cloud data sharing scenario. However, the access policy of the traditional CP-ABE is in plaintext form that reveals significant sensitive information of data owners and data visitors. To mitigate this problem, two approaches have been proposed in the literature. One is partially hidden, where the attributes in the access policy are divided into two parts: the plaintext attribute names and the hidden attribute values. The other approach fully hides the attributes in the access policy which, unfortunately, hinders efficient and correct decryption as well as dynamic policy-updating. In this article, we design a security-enhanced Attribute Cuckoo Filter (se-ACF) to hide the access policy and propose a new CP-ABE system, called Privacy-Preserving Policy Updating ABE (3PU-ABE), which effectively integrates policy hiding and policy updating. We conduct rigorous security analysis and performance evaluation of 3PU-ABE. The results indicate that 3PU-ABE completely hides the access policy without affecting the decryption, and entails better policy-updating efficiency than similar works.

Mechanisms and techniques to enhance the security of big data analytic framework with MongoDB and Linux Containers

The frequency and scale of unauthorized access cases and misuses of data access privileges are a growing concern of many organizations. The protection of confidential data, such as social security numbers, financial information, etc., of the customers and/or employees is among the key responsibilities of any organization, and damage to such sensitive data can easily pose a threat to the future of a business and the security of the customers. Therefore, this paper proposes and implements some security mechanisms and techniques, such as secure authentication, secure authorization, and encryption, to assure the overall security of a big data analytic framework with MongoDB free community edition. This paper presents the fourth phase of our continuous research where in the first phase we proposed a data analytic framework with MongoDB and Linux Containers (LXCs) with basic security requirements. Next, in the second phase we proposed a vulnerability analysis testbed to find vulnerabilities associated with the system. Finally, in the third phase we discussed in detail root causes and some prevention techniques of vulnerabilities found in the system. In addition, this paper introduces a new security mechanism for privacy preserving data handling with MongoDB to ensure the privacy of the data before being processed. Our results show, with our initial model of the analytic framework, how well our newly introduced security mechanisms work and how these security mechanisms and techniques can be used to assure the confidentiality, integrity, and availability (CIA) of any data science project conducted on our proposed analytic framework. In addition, these security mechanisms and techniques help us to strengthen the current system against zero-day attacks where attacks on vulnerabilities that have not been patched or made public yet. Therefore, our vulnerability analysis testbed which is proposed in the second phase of this research will not be able to finds vulnerabilities related to zero-day attacks.

Efficient Implementation of AES-CTR and AES-ECB on GPUs With Applications for High-Speed FrodoKEM and Exhaustive Key Search

The Advanced Encryption Standard (AES) is a standardized block cipher widely used to protect data confidentiality. Besides that, it can be used to generate pseudo-random numbers, which has many important applications. Recently, several works demonstrated the efficient implementations of AES electronics code book (ECB) and counter (CTR) mode on GPU platforms, achieving high throughput. In this brief, we set a speed record of AES implementation, which outperformed previous implementations. In particular, the proposed AES implementation achieved throughput 9&#x0025; (CTR) and 7&#x0025; (ECB) higher than the state-of-the-art, bit-sliced implementation. Moreover, the proposed technique does not require round keys to be embedded into the code during compilation, which is a serious limitation found in earlier work. The proposed technique also achieved up to 63&#x0025; higher throughput compared to another technique presented recently. Two use cases are presented here to verify the efficiency of the proposed AES implementation. Firstly, AES is used to generate random samples in a NIST post-quantum key encapsulation mechanism (KEM), achieving 3,350, 1,503 and 7,716 key exchanges per second on V100, T4, and RTX3080 GPUs respectively. This allows the proposed FrodoKEM implementation to be <inline-formula> <tex-math notation="LaTeX">$2.99\times $ </tex-math></inline-formula> faster than the state-of-the-art performance. The proposed AES implementation was also used in an exhaustive key search application, achieving 11,428, 3,969, and 9,998 <inline-formula> <tex-math notation="LaTeX">$\times 10^{6}$ </tex-math></inline-formula> encryptions per second on V100, T4, and RTX3080 GPUs, respectively.

An Expressive Fully Policy-Hidden Ciphertext Policy Attribute-Based Encryption Scheme With Credible Verification Based on Blockchain

As the public cloud becomes one of the leading ways in data-sharing nowadays, data confidentiality and user privacy are increasingly critical. Partially policy-hidden ciphertext policy attribute-based encryption (CP-ABE) can effectively protect data confidentiality while reducing privacy leakage by hiding part of the access structure. However, it cannot satisfy the need of data sharing in the public cloud with complex users and large amounts of data, both in terms of less expressive access structures and limited granularity of policy hiding. Moreover, the verification of access right to shared data and correctness of decryption are ignored or conducted by an untrusted third party, and the prime-order groups are seldom considered in the expressive policy-hidden schemes. This article proposes a fully policy-hidden CP-ABE scheme constructed on linear secret sharing scheme (LSSS) access structure and prime-order groups for public cloud data sharing. To help users decrypt, hidden vector encryption (HVE) with a “convert step” is applied, which is more compatible with CP-ABE. Meanwhile, decentralized credible verification of access right to shared data and correctness of decryption based on blockchain are also provided. We prove the security of our scheme rigorously and compare the scheme with others comprehensively. The results show that our scheme performs better.

Development of tools for information protection of optical text recognition systems

The subject of research. There has been studying a new universal method of information protection in optical text recognition systems when transmitting confidential data over open communication channels. This work develops the concept of creating a modern, simple and reliable method for protecting information during its transmission over communication channels, to determine the objective criteria for the quality of its work, to create a set of algorithms for implementing the proposed method and software for conducting experimental studies. The current work puts on the concept of creation of a simple and reliable current method for protecting information when passing it through communication channels, also to define the objective criteria for assessing the tool operation quality and to exercise the dedicated programs, which implement the proposed methods and developed algorithms. Based on the results of these studies, it must evaluate the practice effectiveness of the proposed method in terms of both the transmitted data coding/decoding reliability and the secrecy of the fact of special information transmission. Results. It is described the universal concept of producing and use of the contemporary methods of information protection in optical text recognition systems in a confidential data transmission over open communication channels. The main criteria for these systems performance quality are determined. A new combined method for encrypting transmitted messages using QR-codes with subsequent masking of the fact of data transmission by various methods of LSB-steganography is proposed. To conduct experimental studies, a text recognition program based on Tesseract OCR software version 4.0 was developed. The program in Python uses the recent resources of the OpenCV library. The dedicated software technique contributed to assessing the efficiency of the algorithms, which realized the transmitted data encryption and therefore communication links privacy. There are examples of the system operation and results of the software testing in modes of messages encoding for subsequent hidden transmission. Conclusion. The case studies acknowledge the high efficiency of the proposed method of confidential data protection when transmitting them via open networks. The technique can be taken as a basis for developing software aimed at protecting information in OCR systems offered by various manufacturers.

A Dynamic Four-Step Data Security Model for Data in Cloud Computing Based on Cryptography and Steganography.

Cloud computing is a rapidly expanding field. It allows users to access computer system resources as needed, particularly data storage and computational power, without managing them directly. This paper aims to create a data security model based on cryptography and steganography for data in cloud computing that seeks to reduce existing security and privacy concerns, such as data loss, data manipulation, and data theft. To identify the problem and determine its core cause, we studied various literature on existing cloud computing security models. This study utilizes design science research methodology. The design science research approach includes problem identification, requirements elicitation, artifact design and development, demonstration, and assessment. Design thinking and the Python programming language are used to build the artifact, and discussion about its working is represented using histograms, tables, and algorithms. This paper’s output is a four-step data security model based on Rivest–Shamir–Adleman, Advanced Encryption Standard, and identity-based encryption algorithms alongside Least Significant Bit steganography. The four steps are data protection and security through encryption algorithms, steganography, data backup and recovery, and data sharing. This proposed approach ensures more cloud data redundancy, flexibility, efficiency, and security by protecting data confidentiality, privacy, and integrity from attackers.

Based on SM - 9 Cloud Edge System Information Security Transmission

&lt;p&gt;In the past few years, cloud edge system from conception to gradually improve, develop to today has become a mature side of cloud model. Compared with simple cloud computing, cloud edge system has lower network latency and is suitable for application scenarios with higher real-time requirements. Although it can make up for some shortcomings of cloud computing, it also faces many problems in practical application, how to realize the safe transmission of information in the open network environment is one of the difficulties. Since the data transmission process between the edge and the cloud exists in the form of plaintext transmission, this allows attackers to easily disrupt normal data interactions. It is an important research point to ensure the stable operation of the cloud edge system while maximizing the security of communication. To this end, the following work has been done in the direction of secure data transmission in this paper：1. Analyzed the potential risks of the cloud edge system communication network from the per-spective of data source security and data transmission security. 2. Summarizes the requirements and limitations of secure communication, introduces a light-weight SM9 encryption algorithm with low implementation cost and low resource consumption. And compared with other encryption algorithms. 3. Provide algorithmic foundation for establish a framework for secure transmission of light-weight data and achieve data confidentiality protection. Provides a viable reference for secure data transmission in the cloud edge system.&lt;/p&gt; &lt;p&gt;&amp;nbsp;&lt;/p&gt;

A PRODUCTIVE IBPRE MODEL FOR SECURE DATA SHARING IN BLOCKCHAIN TECHNOLOGY BASED IOT

Intelligent tailored services are necessary to fulfill the expectations of users. In order to provide a highly dependable service, additional information about the user's surroundings is required. In order to capture a vast quantity of data, the Internet of Things (IoT), which links multiple gadgets over the Internet, has been created. Although cloud computing is frequently utilized to effectively manage data, it has the potential to delay the transmission of data as well. In this work, we suggest a proxy re-encryption strategy to secure data sharing in cloud contexts. Data owners may outsource their encrypted data to the cloud using identity-based encryption, while proxy re-encryption construction will enable genuine user’s access to the data. An edge device serves as a proxy server for computationally expensive tasks since IoT devices have limited resources. Using information-centric networking capabilities, we may effectively serve cached material in the proxy, hence enhancing service quality and efficiently using network traffic. We've also built our system on block chain, a revolutionary new technology that makes it possible to centralize the sharing of data. It reduces the load on centralized systems and allows for more precise management of data access. The security study and assessment of our scheme reveal the potential of our technique in protecting data confidentiality, integrity, and security

АЛГОРИТМ ОБЕСПЕЧЕНИЯ ЗАЩИТЫ КОНФИДЕНЦИАЛЬНЫХ ДАННЫХ ОБЛАЧНОЙ МЕДИЦИНСКОЙ ИНФОРМАЦИОННОЙ СИСТЕМЫ

The aim of the work is the development and implementation of the architecture of a cloudstorage system, systematization and processing of survey results (for example, EEG) and an algorithmfor ensuring the protection of confidential data based on a completely homomorphic cryptosystem.The object of the research is the technologies of storage, transmission, processing andprotection of confidential information in distributed medical information systems. The architectureof a cloud platform for distributed storage, processing, systematization and protection of confidentialdata (results of medical examinations) has been developed, which makes it possible to interactwith various medical information systems and diagnostic hardware in order to generate big data.An algorithm has been developed to ensure the safety of medical data stored in a cloud platform in electronic form, recorded during patient examinations in order to calculate the average value foreach of the brain activity rhythms (based on the results of a series of examinations over a longperiod of time) using a fully homomorphic encryption algorithm. Based on the test results (analysisof the execution time of such operations as: encryption, decryption, addition, multiplication,signal-to-noise ratio of ciphertext to plaintext), the optimal algorithm. According to the results ofthe work, it is shown that the fully homomorphic encryption scheme CKKS is the most effective,especially in the context of the criticality of the requirements for a high level of security of confidentialdata, which determines the choice of this scheme for the implementation of the algorithmproposed in this work.

Measuring Whistleblowing Perceptions among the Civil Service of the Republic of Kosovo

Abstract In 2018, the Parliament of the Republic of Kosovo approved the Law on the Protection of Whistleblowers, setting up the foundations of the whistleblower protection system for the public and private sectors in the country. In line with the international principles for drafting legislation for the protection of whistleblowers, the law provides three channels for reporting wrongdoing and grants protection against any form of retaliation for whistleblowers. Noting the absence of institutional data on whistleblowing in the public sector, for this research article, a survey was implemented with individual members of civil service in Kosovo (n=400), during the period from September to November 2019, to collect primary data related to factors incentivizing and / or discouraging the decision to whistleblow. Data were collected at the national and local levels of state administration, as per the scope of the definition of the civil service by Kosovo legislation. In this contribution, research results reveal that the protection against any form of retaliation guaranteed by the law is not sufficient for members of civil service in Kosovo to support the decision to whistleblow, as concerns arise for the security and physical integrity of their respective family members. Law does not provide financial incentives for civil servants to whistleblow. Data reveal that a satisfactory level of trust is missing on organizational indicators such as trust in the responsible officer, protection of data confidentiality and anonymity, across different levels of categories of civil service. In line with the concerns voiced by members of civil service and international standards for whistleblower protection, the following actionable recommendations are proposed to advance the whistleblowing system in Kosovo: 1) Improve the provision of training for members of civil service on whistleblowing legislation, organizational procedures, whistleblower protection, and rights; 2) Establish strategies to support employees for whistleblowing. Such strategies would include programs enabling whistleblowers access to professional services such as stress management, counseling, and legal services; 3) Enhance security measures for the physical integrity of whistleblowers and their respective family members; 4) Establish incentives to encourage whistleblowing, such as financial rewards.

Retraction Note: The abnormal precipitation in rainy season based on genetic algorithm and the security of big data in network

In this paper, cloudsim cloud simulation tool is studied, and its running environment is reasonably configured. Taking the platform as the background, the improved genetic algorithm proposed in this paper is used for simulation experiment that is to optimize the genetic algorithm through simulated annealing behavior. Through the simulation experiment of the improved genetic algorithm, it can be known that the genetic algorithm designed in this paper can satisfy multiple customers one by one and has a certain improvement effect on cloud service quality. In this paper, the problem of rainfall anomaly in city D is studied. The results show that the rainfall anomaly of city D is related to solar activity, 500hPa height field in winter and SST in the Central South Pacific from June to August of the previous year. It is found that there is almost no rainfall during the high solar activity years, while there is frequent rainfall near the low solar activity years. Finally, according to the homomorphic encryption mechanism, this paper studies the protection of data confidentiality in computer network security and the multistorage technology of big data. In this research scheme, by adding a certain number of virtual objects to two different computing information dummies, we successfully protect the data such as the number of items owned by the data owner, the content of the items owned, and the item objects called by the user. In addition, this paper uses bilinear mapping and RS coding technology to create related protocols to solve some problems, such as infinite verification of big data integrity, error data recovery, and protection of data owner’s computing resources. Through the design of solutions to the above problems, this paper successfully completed the protection of big data resources and network security based on cloud computing environment.

Post golden jubilee year of the software journal: New research trends and strengthening advisory editorial team

Continuing our journey after the golden jubilee year of Journal of Software: Practice and Experience (SPE), this January 2022 issue focuses on new trends in computer science and software engineering. There are several emerging trends in the computer science, and software development landscape is growing by venturing into and adapting new technologies. Blockchains are being used in different domains for ensuring data security and retaining data provenance. Machine learning is extensively being used in different domains for solving relevant problems; software innovation is no exception. Continuous integration is driving the software development process in the industry. The Internet of Things (IoT) and real-time applications are becoming ubiquitous and are going green. Quantum computing is catching significant attention and first simulators and experimental testbeds are being provided, for the community to venture into the domain. It is time that SPE also looks into the ongoing developments and brings forth the practice and experience of the research community. Going by the motto, this issue starts with a research paper that dealt with blockchains for protecting data confidentiality and traceability. The issue has several research papers related to software engineering such as acquiring cross-domain requirements, just-in-time defect prediction, and benchmarking garbage collection delays. The issue also has papers relevant to cloud computing and wireless sensor networks, with specific focus at energy efficiency. Several of these research works have applied machine learning for achieving relevant research goals. The issue also has a paper that summarizes the state-of-the-art in software effort estimation using machine learning techniques. The issue concludes with a systematic review of quantum computing along with discussion on future research directions. The new EAB members include both established and emerging researchers who have a good track record and are associated with SPE in several ways including publishing their own high-quality research papers and/or organizing special issues on emerging topics. They are drawn from all over the world recognizing growing submissions for SPE from all regions. We request EAB, authors, reviewers, and readers for their continued support in sustaining SPE as the premier forum for publishing new software research and innovation along with practice and experience focus. Your feedback and comments on further improving SPE are highly appreciated.