COVlD-19 vaccine Distribution: Preparing for the Unexpected

In December 2020, two shipments of the vaccine experienced temperature excursions in which product was actually kept at overly cold temperatures (3). Urgent need to protect data One problem that vaccine developers and regulatory agencies need to address is the urgent need to protect data, says Nigel Thorpe, technology director with Secure Age, which specializes in enterprise data encryption using a public key infrastructure platform. For operators on the plant floor, the efforts required are fraught with potential error, especially during shift changes, says Jim Evans, director of Verista, Inc.'s vision, connectivity, and automation division. Raw materials The speed with which vaccines have been developed and are being distributed pose important questions centred around variability. If we're having a raw materials shortage when the vaccines haven't even been scaled up, what will happen when they get full approval?" he asks.

A survey of automatic contact tracing approaches using bluetooth low energy

To combat the ongoing Covid-19 pandemic, many new ways have been proposed on how to automate the process of finding infected people, also called contact tracing. A special focus was put on preserving the privacy of users. Bluetooth Low Energy as base technology has the most promising properties, so this survey focuses on automated contact tracing techniques using Bluetooth Low Energy. We define multiple classes of methods and identify two major groups: systems that rely on a server for finding new infections and systems that distribute this process. Existing approaches are systematically classified regarding security and privacy criteria.Copyright © 2021 ACM.

A secure remote health monitoring model for early disease diagnosis in cloud-based IoT environment.

Internet of Things (IoT) and smart medical devices have improved the healthcare systems by enabling remote monitoring and screening of the patients' health conditions anywhere and anytime. Due to an unexpected and huge increasing in number of patients during coronavirus (novel COVID-19) pandemic, it is considerably indispensable to monitor patients' health condition continuously before any serious disorder or infection occur. According to transferring the huge volume of produced sensitive health data of patients who do not want their private medical information to be revealed, dealing with security issues of IoT data as a major concern and a challenging problem has remained yet. Encountering this challenge, in this paper, a remote health monitoring model that applies a lightweight block encryption method for provisioning security for health and medical data in cloud-based IoT environment is presented. In this model, the patients' health statuses are determined via predicting critical situations through data mining methods for analyzing their biological data sensed by smart medical IoT devices in which a lightweight secure block encryption technique is used to ensure the patients' sensitive data become protected. Lightweight block encryption methods have a crucial effective influence on this sort of systems due to the restricted resources in IoT platforms. Experimental outcomes show that K-star classification method achieves the best results among RF, MLP, SVM, and J48 classifiers, with accuracy of 95%, precision of 94.5%, recall of 93.5%, and f-score of 93.99%. Therefore, regarding the attained outcomes, the suggested model is successful in achieving an effective remote health monitoring model assisted by secure IoT data in cloud-based IoT platforms.

Privacy-Preserving Social Media with a Disclosure

Social Media are an important communication tool in today's society. In recent years, many events have been held online due to COVID-19, making Social Media an even more important communication tool. However, it is difficult to explicitly imagine the recipients of messages when posting on Social Media and there is a tendency to provide information easily, leading to the existence of inappropriate postings that the user does not intend. Furthermore, it is difficult to disclose information for anonymous posting on Twitter. This cause the link problem between the posts. In our proposal, we realize a way to solve these problems by realizing a Social Media that allows both unlinkable posting and disclose posting. Specifically, unlinkable posts can be changed to named posts, and when the name is changed, it is guaranteed that the person who posted the anonymous post was really the anonymous writer and that the anonymous writer cannot be identified from the anonymous post. We introduced randomized pseudonyms to prevent the viewer from checking a post text based only on the posting name without checking the contents of the posting. We also show how to prevent the attack on our proposed scheme by using hiding property and binding property of the commitment scheme. In addition, we implement the proposed scheme and describe the changes between our proposed scheme and regular post in posting time, publication time, and verification time.

Privacy, Security and Usability Comparison of Online Learning Platforms in Developing Countries: A Study on Bangladeshi Universities

As the number of MS Teams, Zoom, and Google Meet users increases with online education, so do the privacy and security vulnerabilities. This study aims to investigate the privacy, security, and usability aspects of few tools that are frequently used for educational purposes by Bangladeshi universities. Consumer security, privacy, and usability are also concerns when it comes to online-based software. This study assesses the most commonly used tools that are used for online education based on three important factors: privacy, security, and usability. Assessment factors concerning the privacy, security, and usability aspects are initially identified. Afterwards, each of the applications was assessed and ranked by comparing their characteristics, functionalities, and terms and conditions (T&C) in contradiction of those factors. In addition, for the purpose of additional validation, a survey was carried out with 57 university students who were enrolled at one of several private universities in Bangladesh. Microsoft Teams, Zoom, and Google Meet have been ranked based on an evaluation of their security, privacy, and usability features, which was accomplished through the use of a knowledge base and a user survey. © 2022 IEEE.

Analysis of Ransomware Using Reverse Engineering Techniques to Develop Effective Countermeasures

Ransomware is the most severe threat to companies and organizations, snowballing daily. Ransomware comes in various types that are difficult for non-specialists to distinguish and evolve and change encryption techniques to avoid detection. Ransomware has become a worldwide incidence during the Corona pandemic and remote work, accountable for millions of dollars of losses annually;This malware threatens victims to lose sensitive data unless they pay a ransom, usually by encrypting the victims' hard drive contents until the ransom is paid. The study focused on literature reviews and publications issued by international organizations interested in ransomware analysis to build a strong background in this field. Used static analysis and reverse engineering methodology to investigate ransomware to understand its purpose, functionality, and effective countermeasures against it. Finally, after Dearcry and Babuk ransomware were analyzed, written the Yara rule to detect and suggested countermeasures against them to help cybersecurity professionals better understand the inner workings of real ransomware and develop advanced countermeasures against similar attacks in the future. © 2023 by the authors.

Privacy Preserving based Personal Health Records Sharing Using Rail Fence Data Encryption (RFDE) for Secure Cloud Environment

The prevalence cloud security has privacy preserving problems that major challenges due to humanity's need protect the sensitive and non-sensitive data to decision-making and resolve data leakage problems. One of the most difficult aspects is the reuse and sharing of accurate and detailed clinical data about PHR collected via Personal Health Records (PHRs) cloud transition is difficult. PHRs are often privacy preserving patient-centric models for exchanging medical information outsourced to third parties, such as Cloud Service Providers (CSP). A unique PHR patient information to ensure security with encryption before storage in the cloud. But still, issues such as security issues, flexible access and a valid user privacy risk management, efficiency and remain an important challenge to achieve better data access sensitive and non-sensitive imposition of control in cloud storage. To achieve high efficiency of PHR and modular data access control, Rail Fence Data Encryption (RFDE) algorithm provided to encrypt the PHR file to make high privacy standards. RFDE is also a form of transposition cipher called zigzag encryption, and the unauthorized user can't access the information. The proposed algorithm encrypts the PHR information it generates the secret key. The receiver decrypts the PHR information using the private key. The proposed algorithm provide efficient performance compared with previous algorithm. © 2023 IEEE.

Secure NIfTI Image Authentication Scheme for Modern Healthcare System

Advances in digital neuroimaging technologies, i.e., MRI and CT scan technology, have radically changed illness diagnosis in the global healthcare system. Digital imaging technologies produce NIfTI images after scanning the patient's body. COVID-19 spared on a worldwide effort to detect the lung infection. CT scans have been performed on billions of COVID-19 patients in recent years, resulting in a massive amount of NIfTI images being produced and communicated over the internet for diagnosis. The dissemination of these medical photographs over the internet has resulted in a significant problem for the healthcare system to maintain its integrity, protect its intellectual property rights, and address other ethical considerations. Another significant issue is how radiologists recognize tempered medical images, sometimes leading to the wrong diagnosis. Thus, the healthcare system requires a robust and reliable watermarking method for these images. Several image watermarking approaches for .jpg, .dcm, .png, .bmp, and other image formats have been developed, but no substantial contribution to NIfTI images (.nii format) has been made. This research suggests a hybrid watermarking method for NIfTI images that employs Slantlet Transform (SLT), Lifting Wavelet Transform (LWT), and Arnold Cat Map. The suggested technique performed well against various attacks. Compared to earlier approaches, the results show that this method is more robust and invisible.

Blockchain-Based Trusted Federated Learning with Pre-Trained Models for COVID-19 Detection

COVID-19 is a serious epidemic that not only endangers human health, but also wreaks havoc on the development of society. Recently, there has been research on using artificial intelligence (AI) techniques for COVID-19 detection. As AI has entered the era of big models, deep learning methods based on pre-trained models (PTMs) have become a focus of industrial applications. Federated learning (FL) enables the union of geographically isolated data, which can address the demands of big data for PTMs. However, the incompleteness of the healthcare system and the untrusted distribution of medical data make FL participants unreliable, and medical data also has strong privacy protection requirements. Our research aims to improve training efficiency and global model accuracy using PTMs for training in FL, reducing computation and communication. Meanwhile, we provide a secure aggregation rule using differential privacy and fully homomorphic encryption to achieve a privacy-preserving Byzantine robust federal learning scheme. In addition, we use blockchain to record the training process and we integrate a Byzantine fault tolerance consensus to further improve robustness. Finally, we conduct experiments on a publicly available dataset, and the experimental results show that our scheme is effective with privacy-preserving and robustness. The final trained models achieve better performance on the positive prediction and severe prediction tasks, with an accuracy of 85.00% and 85.06%, respectively. Thus, this indicates that our study is able to provide reliable results for COVID-19 detection.

A survey of image encryption for healthcare applications.

Recently, medical image encryption has attracted many researchers because of security issues in the communication process. The recent COVID-19 has highlighted the fact that medical images are consistently created and disseminated online, leading to a need for protection from unauthorised utilisation. This paper intends to review the various medical image encryption approaches along with their merits and limitations. It includes a survey, a brief introduction, and the most utilised interesting applications of image encryption. Then, the contributions of reviewed approaches are summarised and compared regarding different technical perspectives. Lastly, we highlight the recent challenges along with several directions of potential research that could fill the gaps in these domains for researchers and developers.

Towards Secure and Privacy-Preserving Data Sharing for COVID-19 Medical Records: A Blockchain-Empowered Approach

COVID-19 is currently a major global public health challenge. In the battle against the outbreak of COVID-19, how to manage and share the COVID-19 Electric Medical Records (CEMRs) safely and effectively in the world, prevent malicious users from tampering with CEMRs, and protect the privacy of patients are very worthy of attention. In particular, the semi-trusted medical cloud platform has become the primary means of hospital medical data management and information services. Security and privacy issues in the medical cloud platform are more prominent and should be addressed with priority. To address these issues, on the basis of ciphertext policy attribute-based encryption, we propose a blockchain-empowered security and privacy protection scheme with traceable and direct revocation for COVID-19 medical records. In this scheme, we perform the blockchain for uniform identity authentication and all public keys, revocation lists, etc are stored on a blockchain. The system manager server is responsible for generating the system parameters and publishes the private keys for the COVID-19 medical practitioners and users. The cloud service provider (CSP) stores the CEMRs and generates the intermediate decryption parameters using policy matching. The user can calculate the decryption key if the user has private keys and intermediate decrypt parameters. Only when attributes are satisfied access policy and the user's identity is out of the revocation list, the user can get the intermediate parameters by CSP. The malicious users may track according to the tracking list and can be directly revoked. The security analysis demonstrates that the proposed scheme is indicated to be safe under the Decision Bilinear Diffie-Hellman (DBDH) assumption and can resist many attacks. The simulation experiment demonstrates that the communication and storage overhead is less than other schemes in the public-private key generation, CEMRs encryption, and decryption stages. Besides, we also verify that the proposed scheme works well in the blockchain in terms of both throughput and delay.

Enhancing Security of Medical Image Data in the Cloud Using Machine Learning Technique

To prevent medical data leakage to third parties, algorithm developers have enhanced and modified existing models and tightened the cloud security through complex processes. This research utilizes PlayFair and K-Means clustering algorithm as double-level encryption/ decryption technique with ArnoldCat maps towards securing the medical images in cloud. K-Means is used for segmenting images into pixels and auto-encoders to remove noise (de-noising);the Random Forest regressor, tree-method based ensemble model is used for classification. The study obtained CT scan-images as datasets from ‘Kaggle' and classifies the images into ‘Non-Covid' and ‘Covid' categories. The software utilized is Jupyter-Notebook, in Python. PSNR with MSE evaluation metrics is done using Python. Through testing-and-training datasets, lower MSE score (‘0') and higher PSNR score (60%) were obtained, stating that, the developed decryption/ encryption model is a good fit that enhances cloud security to preserve digital medical images.

An Encryption Key Sharing Method for Contact Tracing Application

The world has seen many pandemics in the past. COVID-19, SARS, and H1N1 are some of them. During the period of epidemic prevention and control, tracing the source becomes a challenge to control the disease, and contact tracing applications are developed by many countries to slow down the spread of pandemics. However, the privacy problem is becoming one of the important issues in contact tracing systems nowadays. To protect the private information for infected persons and their potential contacts in the scenario which described in our paper, the effective encryption key sharing method can be applied to contact tracing systems. In this paper, we propose a key sharing mechanism for contact tracing application, it is allows a confirmed patient to hide their sensitive information from others when send the notification messages. Our mechanism is used to achieve such a user's privacy functionality. We present the security analysis and prove the security of the mechanism. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

A Secure Blockchain-Assisted Access Control Scheme for Smart Healthcare System in Fog Computing

IoT-based smart healthcare system allows doctors to monitor and diagnose patients remotely, which can greatly ease overcrowding in the hospitals and disequilibrium of medical resources, especially during the rage of COVID-19. However, the smart healthcare system generates enormous data which contains sensitive personal information. To protect patients’privacy, we propose a secure blockchain-assisted access control scheme for smart healthcare system in fog computing. All the operations of users are recorded on the blockchain by smart contract in order to ensure transparency and reliability of the system. We present a blockchain-assisted Multi-Authority Attribute-Based Encryption (MA-ABE) scheme with keyword search to ensure the confidentiality of the data, avoid single point of failure and implement fine-grained access control of the system. IoT devices are limited in resources, therefore it is not practical to apply the blockchain-assisted MA-ABE scheme directly. To reduce the burdens of IoT devices, We outsource most of the computational tasks to fog nodes. Finally, the security and performance analysis demonstrate that the proposed system is reliable, practical, and efficient. IEEE

Attribute-based multi-user collaborative searchable encryption in COVID-19.

With the outbreak of COVID-19, the government has been forced to collect a large amount of detailed information about patients in order to effectively curb the epidemic of the disease, including private data of patients. Searchable encryption is an essential technology for ciphertext retrieval in cloud computing environments, and many searchable encryption schemes are based on attributes to control user's search permissions to protect their data privacy. The existing attribute-based searchable encryption (ABSE) scheme can only implement the situation where the search permission of one person meets the search policy and does not support users to obtain the search permission through collaboration. In this paper, we proposed a new attribute-based collaborative searchable encryption scheme in multi-user setting (ABCSE-MU), which takes the access tree as the access policy and introduces the translation nodes to implement collaborative search. The cooperation can only be reached on the translation node and the flexibility of search permission is achieved on the premise of data security. ABCSE-MU scheme solves the problem that a single user has insufficient search permissions but still needs to search, making the user's access policy more flexible. We use random blinding to ensure the confidentiality and security of the secret key, further prove that our scheme is secure under the Decisional Bilinear Diffie-Hellman (DBDH) assumption. Security analysis further shows that the scheme can ensure the confidentiality of data under chosen-keyword attacks and resist collusion attacks.

Statistical Analysis of Online Voting System Through Blockchain and ML Techniques: A Sustainable Approach for 21st Century Life Style and Smart Cities

A digital voting system is a process that allows people to vote while sitting at their homes and is based on their face recognition identification. The votes will be counted and saved in a blockchain-based structure which is secure and immutable, thus giving availability with security in a system. The traditional voting system does not allow people to vote sitting at their home. Considering the situation of covid, everything is going digital. Questions on EVM from losing parties regarding some malfunctioning. Copyright © 2022, IGI Global.

The Security Algorithm ES-BR22-001 Used to Secure the Health Data

The data age information is considerably more significant in open life, since individuals' well-being information just concluded regardless of whether COVID-19 impacted, and furthermore connected with all medical problems information. These information used to examine and anticipate the medical problems information by Machine Learning Algorithm, and afterward anticipated information need greater security. In this way, we applied the current strategy ChaCha technique and that strategy zeroed in as it were "encryption execution” so security is less. In this paper, to apply the new ES-BR22-001 strategy, this technique has 7 stages. The 1st stage is finding the K value. The 2nd stage is applying the K value in Eq. (1). The 3rd stage is finding the Sk values by using Eq. (1). The 4th stage is applying the Sk values in the sparse matrix. The 5th stage is sparse matrix values are converted into single line. The 6th stage is pairing all the values. The final stage is all paired values will be applied in the matrix. The new ES-BR22-001 method provides security and performance is good while compared to ChaCha method. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

FPGA Based Light Weight Encryption of Medical Data for IoMT Devices using ASCON Cipher

Internet of Things applications with various sensors in public network are vulnerable to cyber physical attacks. The technology of IoT in smart health monitoring systems popularly known as Internet of Medical Things (IoMT) devices. The rapid growth of remote telemedicine has witnessed in the post COVID era. Data collected over IoMT devices is sensitive and needs security, hence provided by enhancing a light weight encryption module on IoMT device. An authenticated Encryption with Associated Data is employed on the IoMT device to enhance the security to the medical wellness of patient. This paper presents FPGA-based implementation of ASCON-128, a light weight cipher for data encryption. A LUT6 based substitution box (SBOX) is implemented on FPGA as part of cipher permutation block. The proposed architecture takes 1330 number of LUTs, which is 35% less compared to the best existing design. Moreover, the proposed ASCON architecture has improved the throughput by 45% compared to the best existing design. This paper presents the results pertaining to encryption and decryption of medical data as well as normal images. © 2022 IEEE.

Privacy preserving via multi-key homomorphic encryption in cloud computing

As the world grapples with the COVID-19 and its variants, multi-user collaboration by means of cloud computing is ubiquitous. How to make better use of cloud resources while preventing user privacy leakage has become particularly important. Multi-key homomorphic encryption(MKHE) can effectively deal with the privacy disclosure issue during the multi-user collaboration in the cloud computing setting. Firstly, we improve the DGHV homomorphic scheme by modifying the selection of key and the coefficients in encryption, so as to eliminate the restriction on the parity of the ciphertext modulus in the public key. On this basis, we further propose a DGHV-type MKHE scheme based on the number theory. In our scheme, an extended key is introduced for ciphertext extension, and we prove that it is efficient in performance analysis. The semantic security of our schemes is proved under the assumption of error-free approximate greatest common divisor and the difficulty of large integer factorization. Furthermore, the simulation experiments show the availability and computational efficiency of our MKHE scheme. Therefore, our scheme is suitable for the multi-user scenario in cloud environment. © 2023 Elsevier Ltd

Rain Drop Service and Biometric Verification Based Blockchain Technology for Securing the Bank Transactions from Cyber Crimes Using Weighted Fair Blockchain (WFB) Algorithm

Cybercrime is an online crime committing fraud, stealing identities, violating privacy or hacking the personal information. A high level of information security in banking can be attained through striving to achieve an integrity, confidentiality, availability, assurance, and accountability. This Pandemic situation (COVID-19) paved the way for the customers to avoid traditional ways of banking and adapt to digital transactions. This banking digitalization increases in the utilization of cashless transactions like digital money (Cryptocurrency). Cyber security is imperative to preserve sensitive information, therefore, Blockchain technology has been adapted to provide security. Transactions done via Blockchain are tested through every block, which makes transactions secure and helps the banking system to work faster. The proposed algorithm WFB is used to estimate the average queue rate and avoid unwanted block generation. Then the trapezoidal fuzzy technique optimizes the allocation of blocks. An objective of this investigation is to enhance the security in banking systems from Cybercrimes by verifying Rain Drop Service (RDS) and Fingerprint Biometric without the need of any central authority. Once the service is completed, the service is a dropout and the following new service will be provided (Hence the name RDS). For the strong authentication scheme to fight against bank fraud, RSA encryption technique has been implemented successfully. Therefore, Blockchain technology increases the need for cyber security as a part of design architecture which intends to detect the stemming attacks in real time instead of repairing the damage. [ FROM AUTHOR] Copyright of Cybernetics & Systems is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)