Encryption Algorithm Using Polygon Triangulation and Catalan Numbers

The present COVID pandemic has transformed a physical world to a digital world. Electronic communication has become a major part of the human life that leads to a threat to digital network. So, hiding and protecting the information against unintended persons are highly essential nowadays. This can be done by encryption process. Encryption techniques are derived from mathematical concepts like number theory, graph theory, and algebra. The present paper explains a symmetric packet cipher using polygon triangulation and Catalan number of applied number theory. Here, a natural number n is secret between the users. The Catalan number Cn and number of triangles of n-angle Tn have major role in encryption process with simple logical XOR operation. To protect the cipher against different active and passive attacks, to achieve avalanche effect, the present plaintext packet is concatenated with the previous cipher text packet. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

An efficient lightweight encryption model with re-encryption scheme to create robust blockchain architecture for COVID-19 data

Handling electronic health records from the Internet of Medical Things is one of the most challenging research areas as it consists of sensitive information, which targets attackers. Also, dealing with modern healthcare systems is highly complex and expensive, requiring much secured storage space. However, blockchain technology can mitigate these problems through improved health record management. The proposed work develops a scalable, lightweight framework based on blockchain technology to improve COVID-19 data security, scalability and patient privacy. Initially, the COVID-19 related data records are hashed using the enhanced Merkle tree data structure. The hashed values are encrypted by lattice based cryptography with a Homomorphic proxy re-encryption scheme in which the input data are secured. After completing the encryption process, the blockchain uses inter planetary file system to store secured information. Finally, the Proof of Work concept is utilized to validate the security of the input COVID based data records. The proposed work's experimental setup is performed using the Python tool. The performance metrics like encryption time, re-encryption time, decryption time, overall processing time, and latency prove the efficacy of the proposed schemes. © 2022 John Wiley & Sons Ltd.

A Blockchain-Based End-to-End Data Protection Model for Personal Health Records Sharing: A Fully Homomorphic Encryption Approach

Personal health records (PHR) represent health data managed by a specific individual. Traditional solutions rely on centralized architectures to store and distribute PHR, which are more vulnerable to security breaches. To address such problems, distributed network technologies, including blockchain and distributed hash tables (DHT) are used for processing, storing, and sharing health records. Furthermore, fully homomorphic encryption (FHE) is a set of techniques that allows the calculation of encrypted data, which can help to protect personal privacy in data sharing. In this context, we propose an architectural model that applies a DHT technique called the interplanetary protocol file system and blockchain networks to store and distribute data and metadata separately;two new elements, called data steward and shared data vault, are introduced in this regard. These new modules are responsible for segregating responsibilities from health institutions and promoting end-to-end encryption;therefore, a person can manage data encryption and requests for data sharing in addition to restricting access to data for a predefined period. In addition to supporting calculations on encrypted data, our contribution can be summarized as follows: (i) mitigation of risk to personal privacy by reducing the use of unencrypted data, and (ii) improvement of semantic interoperability among health institutions by using distributed networks for standardized PHR. We evaluated performance and storage occupation using a database with 1.3 million COVID-19 registries, which showed that combining FHE with distributed networks could redefine e-health paradigms. © 2022 by the authors.

A privacy-preserving blockchain-based tracing model for virus-infected people in cloud

The outbreak of COVID-19 has exposed the privacy of positive patients to the public, which will lead to violations of users' rights and even threaten their lives. A privacy-preserving scheme involving virus-infected positive patients is proposed by us. The traditional ciphertext policy attribute-based encryption (CP-ABE) has the features of enhanced plaintext security and fine-grained access control. However, the encryption process requires the high computational performance of the device, which puts a high strain on resource-limited devices. After semi-honest users successfully decrypt the data, they will get the real private data, which will cause serious privacy leakage problems. Traditional cloud-based data management architectures are extremely vulnerable in the face of various cyberattacks. To address the above challenges, a verifiable ABE scheme based on blockchain and local differential privacy is proposed, using LDP to perturb the original data locally to a certain extent to resist collusion attacks, outsourcing encryption and decryption to corresponding service providers to reduce the pressure on mobile terminals, and deploying smart contracts in combination with blockchain for fair execution by all parties to solve the problem of returning wrong search results in a semi-honest cloud server. Detailed security proofs are performed through the defined security goals, which shows that the proposed scheme is indeed privacy-protective. The experimental results show that the scheme is optimized in terms of data accuracy, computational overhead, storage performance, and fairness. In terms of efficiency, it greatly reduces the local load, enhances personal privacy protection, and has high practicality as well as reliability. As far as we know, it is the first case of applying the combination of LDP technology and blockchain to a tracing system, which not only mitigates poisoning attacks on user data, but also improves the accuracy of the data, thus making it easier to identify infected contacts and making a useful contribution to health prevention and control efforts. © 2022 Elsevier Ltd

UpAIsthiti: A Touchless Attendance System

Managing attendance is a vital task for every institution. Considering the COVID pandemic where many organizations have resorted to online mode of working, it has become imperative to maintain social distancing and digitize various processes. Thus, for maintaining attendance of the students of schools/colleges or employees of a company, a touchless attendance system is required that records the attendance by capturing faces and does not waste time. This one-of-a-kind application uses a client–server model and captures the faces of students/employees through video feeds from mobile phone cameras, and the images are sent to a server, where image processing is used to process the faces. Further, with the help of dlib and the face recognition library, it identifies the faces and records the attendance in the software itself. The processed image is again sent back to the client android application, and the user gets notified about their attendance. Additional functionalities for data analysis and updating data have also been added to the system. Thus, the whole attendance system is an effort to make the attendance activity easy and efficient. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Ciphertext-policy attribute-based encryption supporting policy-hiding and cloud auditing in smart health

Smart Health, with its flexibility and efficiency, has been widely deployed, especially during the COVID-19 pandemic. However, privacy protection mechanisms for Smart Health are not yet well established and still present a number of security issues. Ciphertext-Policy Attribute-Based Encryption (CP-ABE), is identified as the furthest potential approach for constructing privacy-preserving Smart Health. However, traditional CP-ABE is facing some new challenges. On the one hand, access policy is not encrypted, and the identity information of the user could be exposed. On the other hand, Smart Health Records (SHRs) are outsourced to the Cloud Service Providers (CSP) and may be at risk of being tampered with. In this article, we have built a CP-ABE solution (PHCA) that supports policy-hiding and cloud auditing to ensure privacy security for smart health, in which the decryption cost is constant. To ensure data integrity, we securely introduce an effective third-party auditor. In addition, we design and implement safe and effective outsourcing decryption algorithms, which significantly low the decryption costs for users. Performance comparisons and security analysis demonstrate that our solutions function effectively. • We propose a CP-ABE scheme (PHCA) that supports policy-hiding and cloud auditing. • Our scheme ensures data integrity and privacy. • Our scheme is proven secure under dual-system encryption technique. [ FROM AUTHOR]

Secure E-health Framework in Cloud-Based Environment

Since December 2019, the world still fighting to beat coronavirus (COVID-19). However, coronavirus is continuing its spread in many countries and claimed the lives people. It is not easy to differentiate between COVID-19 symptoms and simple flu symptoms, especially at the first stage of the infection. This is the main challenge where we have to run many tests as possible and isolate any suspicious people 14 days at least to make sure that they are not carrying the virus. This will increase the cost and people may lose their jobs. Therefore, the economy has to continue. Companies and organization start running their business using online tools, this will draw different future and employee need to gain special task to continue their work. In order go back to the normal life, we have track the virus and stay away from infected area or people. In this paper, we propose a secure cloud-based health framework to record patients' readings, give initial diagnose to identify infected areas and control the spread of the virus. The proposed framework will be running in a secure environment to protect patient's records. © 2022 IEEE.

Improved Gentry–Halevi's fully homomorphic encryption-based lightweight privacy preserving scheme for securing medical Internet of Things

Internet of Medical Things (IoMT) solutions have proliferated rapidly in the COVID-19 pandemic era. The smart medical sensors capture real-time data from remote patients and communicate it to medical servers in a secure and privacy-preserving manner. It is a herculean challenge to guarantee security and privacy in Medical IoT applications. Hence, an improved Gentry–Halevi's fully homomorphic encryption-based (IGHFHE) lightweight privacy preserving user authentication scheme is proposed in this work. The scheme is proposed with an integer matrix computation strategy for securing data computation with privacy protection. It adopts the translation process of Gentry–Halevi's fully homomorphic encryption process for performing homomorphic addition and multiplication, then encrypt an integer matrix modulo that represents a positive integer. Extensive informal investigation and simulation of the proposed IGHFHE scheme shows that it is more resistant to well-known attacks for preventing authentication breaches. Also, the proposed IGHFHE scheme reduced computational and storage overhead by 4.98% and 5.78% respectively on average in comparison to other prevailing schemes. © 2023 John Wiley & Sons Ltd.

Privacy-Preserving Mechanism to Secure IoT-Enabled Smart Healthcare System in the Wireless Body Area Network

The IoT has been a subclass of Industry 4.0 standards that is under research from the perspective of quality of service (QoS) & security. Due to the pandemic situations like novel coronavirus smart healthcare monitoring gained growing interest in detection. In IoT data is communicated from Intra WBAN (Wireless Body Area Network) to inter-WBAN and then beyond WBAN. While transferring data from one layer to the other end-to-end data privacy is the challenge to focus on. The privacy-preserving of patients' sensitive data is difficult due to their open nature and resource-constrained sensor nodes. The proposed research design based on routing protocols achieves the patient's sensitive data privacy preservation along with minimum computation efforts and energy consumption. The proposed model is Secure Communication-Elliptic Curve Cryptography (SCECC) WBAN-assisted networks in presence of attackers is evaluated using NS2. The proposed privacy preservation algorithm uses efficient cryptographic solutions using hash, digital signature, and the optimization of the network. © 2022 The Korean Society for Vascular Surgery.

RSA-based Encryption Algorithm for Digital Images

With the spread of Covid-19, secure transmission of data over the Internet has drawn prior attention. Therefore, protecting these data is a very important process. This objective can be achieved through encryption. In this study, a digital image encryption algorithm is suggested depending on the RSA cryptosystem, since the RSA is a strong and well-known asymmetric encryption system. The proposed algorithm divides the image into blocks of 2×2 size rather than encrypting one pixel at a time. This improves the encryption process and then converts each block into a single vector. The vector elements are converted to binary and then into to a single binary number. After that, the binary number is converted to decimal to be compatible with using RSA algorithm. The proposed algorithm is lossless;the original image is restored without losing any information or data. Finally, the suggested algorithm is executed in MATLAB environment and tested on various images. The results of the experiment reveal the suggested encryption algorithm is both reliable, secure and applicable to image protection. © 2022 IEEE.