Maximum likelihood estimation of exponential distribution under type-ii censoring from imprecise data

Statistical analysis of lifetime distributions under Type-II censoring scheme is based on precise lifetime data. However, some collected lifetime data might be imprecise and are represented in the form of fuzzy numbers. This paper deals with the estimation of exponential mean parameter under Type-II censoring scheme when the lifetime observations are fuzzy and are assumed to be related to underlying crisp realization of a random sample. Maximum likelihood estimate of the unknown parameter is obtained by using EM algorithm. In addition, a new numerical method for parameter estimation is provided. Using the parametric bootstrap method, the construction of confidence intervals for the mean parameter is discussed. Monte Carlo simulations are performed to investigate performance of the different methods. Finally, an illustrative example is also included.Keywords: Type-II censoring, Imprecise lifetime, Exponential distribution, Maximumlikelihood estimation, Bootstrap confidence interva

Blockchain for IoT: The challenges and a way forward

Copyright © 2018 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved Bitcoin has revolutionized the decentralized payment system by excluding the need for a trusted third party, reducing the transaction (TX) fee and time involved in TX confirmation as compared to a conventional banking system. The underlying technology of Bitcoin is Blockchain, which was initially designed for financial TXs only. However, due to its decentralized architecture, fault tolerance and cryptographic security benefits such as user anonymity, data integrity and authentication, researchers and security analysts around the world are focusing on the Blockchain to resolve security and privacy issues of IoT. But at the same time, default limitations of Blockchain, such as latency in transaction confirmation, scalability concerning Blockchain size and network expansion, lack of IoT-centric transaction validation rules, the absence of IoT-focused consensus protocols and insecure device integration are required to be addressed before it can be used securely and efficiently in an IoT environment. Therefore, in this paper we analyze some of the existing consensus protocols used in various Blockchain-based applications, with a focus on investigating significant limitations in TX (Transaction) validation and consensus mechanism that make them inappropriate to be implemented in Blockchain-based IoT systems. We also propose a way forward to address these issues

PrivySharing: A Blockchain-based framework for integrity and privacy-preserving data sharing in Smart Cities

Copyright © 2019 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved The ubiquitous use of Internet of Things (IoT) ranges from industrial control systems to e-Health, e-commerce, smart cities, supply chain management, smart cars, cyber-physical systems and a lot more. However, the data collected and processed by IoT systems especially the ones with centralized control are vulnerable to availability, integrity, and privacy threats. Hence, we present “PrivySharing,” a blockchain-based innovative framework for integrity and privacy-preserving IoT data sharing in a smart city environment. The proposed scheme is distinct from existing technologies on many aspects. The data privacy is preserved by dividing the blockchain network into various channels, where every channel processes a specific type of data such as health, smart car, smart energy or financial data. Moreover, access to user data within a channel is controlled by embedding access control rules in the smart contracts. In addition, users' data within a channel is further isolated and secured by using private data collection. Likewise, the REST API that enables clients to interact with the blockchain network has dual security in the form of an API Key and OAuth 2.0. The proposed solution also conforms to some of the significant requirements outlined in the European Union General Data Protection Regulation. Lastly, we present a system of reward in the form of a digital token “PrivyCoin” for the users for sharing their data with the stakeholders/third parties

Blockchain's adoption in IoT: The challenges, and a way forward

© 2018 Elsevier Ltd The underlying technology of Bitcoin is blockchain, which was initially designed for financial value transfer only. Nonetheless, due to its decentralized architecture, fault tolerance and cryptographic security benefits such as pseudonymous identities, data integrity and authentication, researchers and security analysts around the world are focusing on the blockchain to resolve security and privacy issues of IoT. However, presently, not much work has been done to assess blockchain's viability for IoT and the associated challenges. Hence, to arrive at intelligible conclusions, this paper carries out a systematic study of the peculiarities of the IoT environment including its security and performance requirements and progression in blockchain technologies. We have identified the gaps by mapping the security and performance benefits inferred by the blockchain technologies and some of the blockchain-based IoT applications against the IoT requirements. We also discovered some practical issues involved in the integration of IoT devices with the blockchain. In the end, we propose a way forward to resolve some of the significant challenges to the blockchain's adoption in IoT

PLEDGE: An IoT-oriented Proof-of-Honesty based Blockchain Consensus Protocol

The existing lottery-based consensus algorithms, such as Proof-of-Work, and Proof-of-Stake, are mostly used for blockchain-based financial technology applications. Similarly, the Byzantine Fault Tolerance algorithms do provide consensus finality, yet they are either communications intensive, vulnerable to Denial-of-Service attacks, poorly scalable, or have a low faulty node tolerance level. Moreover, these algorithms are not designed for the Internet of Things systems that require near-real-time transaction confirmation, maximum fault tolerance, and appropriate transaction validation rules. Hence, we propose "Pledge, "a unique Proof-of-Honesty based consensus protocol to reduce the possibility of malicious behavior during blockchain consensus. Pledge also introduces the Internet of Things centric transaction validation rules. Initial experimentation shows that Pledge is economical and secure with low communications complexity and low latency in transaction confirmation

PrivySharing: A blockchain-based framework for privacy-preserving and secure data sharing in smart cities

© 2019 Elsevier Ltd The ubiquitous use of Internet of Things (IoT) ranges from industrial control systems to e-Health, e-commerce, smart cities, agriculture, supply chain management, smart cars, cyber-physical systems and a lot more. However, the data collected and processed by IoT systems especially the ones with centralized control are vulnerable to availability, integrity, and privacy threats. Hence, we present “PrivySharing,” a blockchain-based innovative framework for privacy-preserving and secure IoT data sharing in a smart city environment. The proposed scheme is distinct from existing strategies on many aspects. The data privacy is preserved by dividing the blockchain network into various channels, where every channel comprises a finite number of authorized organizations and processes a specific type of data such as health, smart car, smart energy or financial details. Moreover, access to users’ data within a channel is controlled by embedding access control rules in the smart contracts. In addition, data within a channel is further isolated and secured by using private data collection and encryption respectively. Likewise, the REST API that enables clients to interact with the blockchain network has dual security in the form of an API Key and OAuth 2.0. The proposed solution conforms to some of the significant requirements outlined in the European Union General Data Protection Regulation. We also present a system of reward in the form of a digital token named “PrivyCoin” for users sharing their data with stakeholders/third parties. Lastly, the experimental outcomes advocate that a multi-channel blockchain scales well as compared to a single-channel blockchain system

D2Gen: A Decentralized Device Genome Based Integrity Verification Mechanism for Collaborative Intrusion Detection Systems

Collaborative Intrusion Detection Systems are considered an effective defense mechanism for large, intricate, and multilayered Industrial Internet of Things against many cyberattacks. However, while a Collaborative Intrusion Detection System successfully detects and prevents various attacks, it is possible that an inside attacker performs a malicious act and compromises an Intrusion Detection System node. A compromised node can inflict considerable damage on the whole collaborative network. For instance, when a malicious node gives a false alert of an attack, the other nodes will unnecessarily increase their security and close all of their services, thus, degrading the system's performance. On the contrary, if the spurious node approves malicious traffic into the system, the other nodes would also be compromised. Therefore, to detect a compromised node in the network, this article introduces a device integrity check mechanism based on 'Digital Genome.' In medical science, a genome refers to a set that contains all of the information needed to build and maintain an organism. Based on the same concept, the digital genome is computed over a device's vital hardware, software, and other components. Hence, if an attacker makes any change in a node's hardware and software components, the digital genome will change, and the compromised node will be easily detected. It is envisaged that the proposed integrity attestation protocol can be used in diverse Internet of Things and other information technology applications to ensure the legitimate operation of end devices. This study also proffers a comprehensive security and performance analysis of the proposed framework

Internet of Things 2.0: Concepts, Applications, and Future Directions

Applications and technologies of the Internet of Things are in high demand with the increase of network devices. With the development of technologies such as 5G, machine learning, edge computing, and Industry 4.0, the Internet of Things has evolved. This survey article discusses the evolution of the Internet of Things and presents the vision for Internet of Things 2.0. The Internet of Things 2.0 development is discussed across seven major fields. These fields are machine learning intelligence, mission critical communication, scalability, energy harvesting-based energy sustainability, interoperability, user friendly IoT, and security. Other than these major fields, the architectural development of the Internet of Things and major types of applications are also reviewed. Finally, this article ends with the vision and current limitations of the Internet of Things in future network environments

Spread, circulation, and evolution of the Middle East respiratory syndrome coronavirus

The Middle East respiratory syndrome coronavirus (MERS-CoV) was first documented in the Kingdom of Saudi Arabia (KSA) in 2012 and, to date, has been identified in 180 cases with 43% mortality. In this study, we have determined the MERS-CoV evolutionary rate, documented genetic variants of the virus and their distribution throughout the Arabian peninsula, and identified the genome positions under positive selection, important features for monitoring adaptation of MERS-CoV to human transmission and for identifying the source of infections. Respiratory samples from confirmed KSA MERS cases from May to September 2013 were subjected to whole-genome deep sequencing, and 32 complete or partial sequences (20 were ≥99% complete, 7 were 50 to 94% complete, and 5 were 27 to 50% complete) were obtained, bringing the total available MERS-CoV genomic sequences to 65. An evolutionary rate of 1.12 × 10−3 substitutions per site per year (95% credible interval [95% CI], 8.76 × 10−4; 1.37 × 10−3) was estimated, bringing the time to most recent common ancestor to March 2012 (95% CI, December 2011; June 2012). Only one MERS-CoV codon, spike 1020, located in a domain required for cell entry, is under strong positive selection. Four KSA MERS-CoV phylogenetic clades were found, with 3 clades apparently no longer contributing to current cases. The size of the population infected with MERS-CoV showed a gradual increase to June 2013, followed by a decline, possibly due to increased surveillance and infection control measures combined with a basic reproduction number (R0) for the virus that is less than 1

Effect of the COVID-19 Vaccine on the Menstrual Cycle among Females in Saudi Arabia

BACKGROUND: The number of reports of menstrual changes after COVID-19 vaccination in the Saudi population is still unknown. Therefore, this study aimed to assess the effect of the COVID-19 vaccine(Pfizer, AstraZeneca, and Moderna) on the menstrual cycle among females in Saudi Arabia. METHODS: This descriptive cross-sectional study was conducted in Saudi Arabia at Umm Al-Qura University (UQU) from August 2021 to February 2022. Data was collected through a previously validated online questionnaire. RESULTS: A total of 2338 participants who received the first dose of the COVID-19 vaccine participated in this study; 1606 (68.7%) of them received the second dose in addition to the first. The mean age of the study participants was 35.4±9.5 years. No significant associations were found between the type of COVID-19 vaccine and the impact on the menstrual cycle, either for the first or second dose (P-values > 0.05). A significant association was found only between the first dose vaccination day and the impact on the menstrual cycle in the second question of “After receiving the COVID-19 vaccine, your next period was” (P-value ≤ 0.05). Significant associations were found between the second dose vaccination day and the impact on the menstrual cycle in the first and second questions of “After receiving the COVID-19 vaccine, your next period was”, and “After receiving the first dose, your next period was," respectively (P-values ≤ 0.05). CONCLUSION: The study found a potential association between the COVID-19 vaccine and menstrual cycle irregularities, which could impact females' quality of life