scholarly journals Data Integrity Time Optimization of a Blockchain IoT Smart Home Network Using Different Consensus and Hash Algorithms

2021 ◽  
Vol 2021 ◽  
pp. 1-23
Author(s):  
Ammar Riadh Kairaldeen ◽  
Nor Fadzilah Abdullah ◽  
Asma Abu-Samah ◽  
Rosdiadee Nordin
Keyword(s):  
Data Security ◽  
Execution Time ◽  
Smart Home ◽  
Data Integrity ◽  
Consensus Algorithm ◽  
Home Networks ◽  
Consensus Algorithms ◽  
Time Optimization ◽  
Merkle Hash Tree ◽  
Tools And Techniques

Data security is a major issue for smart home networks. Yet, different existing tools and techniques have not been proven highly effective for home networks’ data security. Blockchain is a promising technology because of the distributed computing infrastructure network that makes it difficult for hackers to intrude into the systems through the use of cryptographic signatures and smart contracts. In this paper, an architecture for smart home networks that could guarantee data integrity, robust security, and the ability to protect the validity of the blockchain transactions has been investigated. The system model is tested using various sizes of realistic datasets (30, 3 k, and 30 k to represent a small, medium, and large number of transactions, respectively). Four different consensus algorithms were considered, the conventional schemes concatenated hash transactions (CHT) and Merkle hash tree (MHT), as well as the newly proposed odd and even modified MHT (O&E MHT) and modified MHT (MMHT). Moreover, 15 hash functions were also examined and compared to understand the effects of each consensus algorithms on the data integrity verification check execution time and the time optimization provided by the proposed MMHT algorithm. The results show that even though the CHT algorithm gives the lowest execution time, it is impractical for a blockchain implementation due to the requirement to copy the entire blockchain ledger in real time. Meanwhile, the O&E MHT does not give any tangible benefit in the execution time. However, the proposed MMHT offers a minimum of 30% gain in time optimization than the conventional MHT algorithm typically used in blockchains. This work shows that the proposed MMHT consensus algorithm not only can identify malicious codes but has an improved data integrity check performance in smart homes, all while ensuring network stability.

scholarly journals Hardening Machine Learning Denial of Service (DoS) Defences Against Adversarial Attacks in IoT Smart Home Networks

2021 ◽  
pp. 102352
Author(s):  
Eirini Anthi ◽  
Lowri Williams ◽  
Amir Javed ◽  
Pete Burnap
Keyword(s):  
Machine Learning ◽  
Smart Home ◽  
Denial Of Service ◽  
Home Networks

scholarly journals Toward a Faster Fault Tolerant Consensus to Maintain Data Consistency in Collaborative Environments

2017 ◽  
Vol 26 (03) ◽  
pp. 1750002
Author(s):  
Fouad Hanna ◽  
Lionel Droz-Bartholet ◽  
Jean-Christophe Lapayre
Keyword(s):  
Network Model ◽  
Fault Tolerant ◽  
Data Consistency ◽  
Consensus Algorithm ◽  
Simulation Platform ◽  
Consensus Problem ◽  
Collaborative Environments ◽  
Consensus Algorithms ◽  
Shared Data ◽  
Simultaneous Process

The consensus problem has become a key issue in the field of collaborative telemedicine systems because of the need to guarantee the consistency of shared data. In this paper, we focus on the performance of consensus algorithms. First, we studied, in the literature, the most well-known algorithms in the domain. Experiments on these algorithms allowed us to propose a new algorithm that enhances the performance of consensus in different situations. During 2014, we presented our very first initial thoughts to enhance the performance of the consensus algorithms, but the proposed solution gave very moderate results. The goal of this paper is to present a new enhanced consensus algorithm, named Fouad, Lionel and J.-Christophe (FLC). This new algorithm was built on the architecture of the Mostefaoui-Raynal (MR) consensus algorithm and integrates new features and some known techniques in order to enhance the performance of consensus in situations where process crashes are present in the system. The results from our experiments running on the simulation platform Neko show that the FLC algorithm gives the best performance when using a multicast network model on different scenarios: in the first scenario, where there are no process crashes nor wrong suspicion, and even in the second one, where multiple simultaneous process crashes take place in the system.

Secure Data Transmission of Smart Home Networks Based on Information Hiding

2020 ◽  
pp. 264-275
Author(s):  
Haiyu Deng ◽  
Lina Yang ◽  
Xiaocui Dang ◽  
Yuan Yan Tang ◽  
Patrick Wang
Keyword(s):  
Data Transmission ◽  
Information Hiding ◽  
Smart Home ◽  
Home Networks ◽  
Secure Data ◽  
Secure Data Transmission

Development of integration platforms for interworking of smart home devices for heterogeneous data security

2017 ◽  
Vol 24 (3) ◽  
pp. 191
Author(s):  
Jeong Gi Lee ◽  
Sang Hyun Lee
Keyword(s):  
Data Security ◽  
Smart Home ◽  
Heterogeneous Data

scholarly journals Blockchain in manufacturing quality control: A computer simulation study

PLoS ONE ◽  
2021 ◽  
Vol 16 (3) ◽  
pp. e0247925
Author(s):  
Pooi-Mun Wong ◽  
Shreya R. K. Sinha ◽  
Chee-Kong Chui
Keyword(s):  
Quality Control ◽  
Data Security ◽  
Control Process ◽  
Production Quality ◽  
Consensus Algorithm ◽  
Defect Tolerance ◽  
Production Quality Control ◽  
Peer Supervision ◽  
Quality Control Process ◽  
Quality Controller

Blockchain has been applied to quality control in manufacturing, but the problems of false defect detections and lack of data transparency remain. This paper proposes a framework, Blockchain Quality Controller (BCQC), to overcome these limitations while fortifying data security. BCQC utilizes blockchain and Internet-of-Things to form a peer-to-peer supervision network. This paper also proposes a consensus algorithm, Quality Defect Tolerance (QDT), to adopt blockchain for during-production quality control. Simulation results show that BCQC enhances data security and improves defect detections. Although the time taken for the quality control process increases with the number of nodes in blockchain, the application of QDT allows multiple inspections on a workpiece to be consolidated at a faster pace, effectively speeding up the entire quality control process. The BCQC and QDT can improve the quality of parts produced for mass personalization manufacturing.

scholarly journals Log Replication in Raft vs Kafka

2020 ◽  
Vol 65 (2) ◽  
pp. 66
Author(s):  
M. Petrescu ◽  
R. Petrescu
Keyword(s):  
Distributed Systems ◽  
Fault Tolerant ◽  
Consensus Algorithm ◽  
Correct Operation ◽  
Consensus Algorithms ◽  
Fault Tolerant System ◽  
Multiple Algorithms

The implementation of a fault-tolerant system requires some type of consensus algorithm for correct operation. From Paxos to View-stamped Replication and Raft multiple algorithms have been developed to handle this problem. This paper presents and compares the Raft algorithm and Apache Kafka, a distributed messaging system which, although at a higher level, implements many concepts present in Raft (strong leadership, append-only log, log compaction, etc.).This shows that mechanisms conceived to handle one class of problems (consensus algorithms) are very useful to handle a larger category in the context of distributed systems.

scholarly journals Cloud Data Integrity Verification Algorithm for Sustainable Accounting Informatization

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Lin Yang
Keyword(s):  
Big Data ◽  
Execution Time ◽  
Cloud Storage ◽  
Computing Time ◽  
Data Integrity ◽  
Cloud Data ◽  
Integrity Verification ◽  
Verification Algorithm ◽  
Advantages And Disadvantages ◽  
Better Than

In recent years, people have paid more and more attention to cloud data. However, because users do not have absolute control over the data stored on the cloud server, it is necessary for the cloud storage server to provide evidence that the data are completely saved to maintain their control over the data. Give users all management rights, users can independently install operating systems and applications and can choose self-service platforms and various remote management tools to manage and control the host according to personal habits. This paper mainly introduces the cloud data integrity verification algorithm of sustainable computing accounting informatization and studies the advantages and disadvantages of the existing data integrity proof mechanism and the new requirements under the cloud storage environment. In this paper, an LBT-based big data integrity proof mechanism is proposed, which introduces a multibranch path tree as the data structure used in the data integrity proof mechanism and proposes a multibranch path structure with rank and data integrity detection algorithm. In this paper, the proposed data integrity verification algorithm and two other integrity verification algorithms are used for simulation experiments. The experimental results show that the proposed scheme is about 10% better than scheme 1 and about 5% better than scheme 2 in computing time of 500 data blocks; in the change of operation data block time, the execution time of scheme 1 and scheme 2 increases with the increase of data blocks. The execution time of the proposed scheme remains unchanged, and the computational cost of the proposed scheme is also better than that of scheme 1 and scheme 2. The scheme in this paper not only can verify the integrity of cloud storage data but also has certain verification advantages, which has a certain significance in the application of big data integrity verification.

Medical Data Security Tools and Techniques in E-Health Applications

2021 ◽  
pp. 1171-1178
Author(s):  
Anukul Pandey ◽  
Butta Singh ◽  
Barjinder Singh Saini ◽  
Neetu Sood
Keyword(s):  
Data Security ◽  
Privacy Preservation ◽  
Data Access ◽  
Primary Objective ◽  
Medical Data ◽  
Authorized User ◽  
Access Rights ◽  
Integrated Concept ◽  
Tools And Techniques ◽  
Health Applications

The primary objective of this chapter is to analyze the existing tools and techniques for medical data security. Typically, medical data includes either medical signals such as electrocardiogram, electroencephalogram, electromyography, or medical imaging like digital imaging and communications in medicine, joint photographic experts group format. The medical data are sensitive, subject to privacy preservation, and data access rights. Security in e-health field is an integrated concept which includes robust combination of confidentiality, integrity, and availability of medical data. Confidentiality ensures the data is inaccessible to unauthorized access. Integrity restricts the alteration in data by the unauthorized user. Whereas availability provides the readiness of the data when needed by the authorized user. Additionally, confidentiality, integrity and availability, accountability parameter records the back action list which answers the why, when, what, and whom data is accessed. The selected tools and techniques used in medical data security in e-health applications is discussed.

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