Biblio

In the past few years, the blockchain emerged as peer-to-peer distributed ledger technology for recording transactions, maintained by many peers without any central trusted regulatory authority through distributed public-key cryptography and consensus mechanism. It has not only given the birth of cryptocurrencies, but it also resolved various security, privacy and transparency issues of decentralized systems. This article discussed the blockchain basics overview, architecture, and blockchain security components such as hash function, Merkle tree, digital signature, and Elliptic curve cryptography (ECC). In addition to the core idea of blockchain, we focus on ECC's significance in the blockchain. We also discussed why RSA and other key generation mechanisms are not suitable for blockchain-based IoT applications. We also analyze many possible blockchain-based applications where ECC algorithm is better than other algorithms concerning security and privacy assurance. At the end of the article, we will explain the comparative analysis of ECC and RSA.

The Bitcoin blockchain is managed by an underlying peer-to-peer network. This network is responsible for the propagation of transactions carried out by users via the blocks (which contain the validated transactions), and to ensure consensus between the different nodes. The quality and safety of this network are therefore particularly essential. In this work, we present an open dataset on the peers composing the Bitcoin P2P Network that was made following a well defined and reproducible methodology. We also provide a first analysis of the dataset on three criteria: the number of public nodes and their client version and geographical distribution.

Blockchain is opening up new avenues for the development of new sorts of digital services. In this article, we'll employ the transparent Blockchain method to propose a system for collecting data from many sources and databases for use in local and national elections. The Blockchain-based system will be safe, trustworthy, and private. It will assist to know the overall count of the candidates who participated and it functions in the same way as people's faith in their governments does. Blockchain technology is the one that handles the actual vote. We use the secure hash algorithm for resolving this problem and tried to bring a solution through the usage of this booming technology. A centralized database in a blockchain system keeps track of the secure electronic interactions of users in a peer-to-peer network.

Due to the computing capability limitation of the Internet of things devices in the perception layer, the traditional security solutions are difficult to be used directly. How to design a new lightweight, secure and reliable protocol suitable for the Internet of Things application environment, and realize the secure transmission of information among many sensing checkpoints is an urgent problem to be solved. In this paper, we propose a decentralized lightweight authentication key protocol based on the combination of public key and trusted computing technology, which is used to establish secure communication between nodes in the perception layer. The various attacks that the protocol may suffer are analyzed, and the formal analysis method is used to verify the security of the protocol. To verify the validity of the protocol, the computation and communication cost of the protocol are compared with the existing key protocols. And the results show that the protocol achieved the promised performance.

An electronic medical record (EMR) is the digital medical data of a patient, and they are healthcare system's most valuable asset. In this paper, we introduce a decentralized network using blockchain technology and smart contracts as a solution to manage and secure medical records storing, and transactions between medical healthcare providers. Ethereum blockchain is employed to build the blockchain. Solidity object-oriented language was utilized to implement smart contracts to digitally facilitate and verify transactions across the network (creating records, access requests, permitting access, revoking access, rejecting access). This will mitigate prevailing issues of current systems and enhance their performance, since current EMRs are stored on a centralized database, which cannot guarantee data integrity and security, consequently making them susceptible to malicious attacks. Our proposed system approach is of vital importance considering that healthcare providers depend on various tests in making a decision about a patient's diagnosis, and the respective plan of treatment they will go through. These tests are not shared with other providers, while data is scattered on various systems, as a consequence of these ensuing scenarios, patients suffer of the resulting care provided. Moreover, blockchain can meliorate the motley serious challenges caused by future use of IoT devices that provide real-time data from patients. Therefore, integrating the two technologies will produce decentralized IoT based healthcare systems.

While the need for content distribution proliferates - becoming more mammoth and complex on the Internet - the P2P network perseveres as one of the best avenues to service the demand for content distribution. It enjoys a wide range of clients that transport data in bits securely, making it susceptible to moving dubious contents, hence becoming exposed to varying security threats that require credible digital investigation to address. The tools and techniques used in performing digital investigations are still mostly lagging, successfully slowing down law enforcement agencies in general. The acquisition of digital evidence over the Internet is still elusive in the battle against cybercrime. This paper considers a new technique for detecting passive peers that participate in a P2P network. As part of our study, we crawled the µTorrent P2P client over 10 days while logging all participating peers. We then employed digital forensic techniques to analyze the popular users and generate evidence within them with high accuracy. Finally, we evaluated our proposed approach against the standard Analysis, Design, Development, Implementation, and Evaluation, or ADDIE model for digital investigation to arrive at the credible digital evidence presented in this paper.

With the tremendous growth of IoT application, providing security to IoT systems has become more critical. In this paper, a technique is presented to ensure the safety of Internet of Things (IoT) devices. This technique ensures hardware and software security of IoT devices. Blockchain technology is used for software security and hardware logics are used for hardware security. For enabling a Blockchain, Ethereum Network is used for secure peer-to-peer transmission. A prototype model is also used using two IoT nodes to demonstrate the security logic.

We present a novel approach for the collaborative training of neural network models in decentralized federated environments. In the iterative process a group of autonomous peers run multiple training rounds to train a common model. Thereby, participants perform all model training steps locally, such as stochastic gradient descent optimization, using their private, e.g. mission-critical, training datasets. Based on locally updated models, participants can jointly determine a common model by averaging all associated model weights without sharing the actual weight values. For this purpose we introduce a simple n-out-of-n secret sharing schema and an algorithm to calculate average values in a peer-to-peer manner. Our experimental results with deep neural networks on well-known sample datasets prove the generic applicability of the approach, with regard to model quality parameters. Since there is no need to involve a central service provider in model training, the approach can help establish trustworthy collaboration platforms for businesses with high security and data protection requirements.

Protecting privacy of the user location in Internet of Things (IoT) applications is a complex problem. Peer-to-peer (P2P) approach is one of the most popular techniques used to protect privacy in IoT applications, especially that use the location service. The P2P approach requires trust among peers in addition to serious cooperation. These requirements are still an open problem for this approach and its methods. In this paper, we propose an effective solution to this issue by creating a manager for the peers' reputation called R-TTP. Each peer has a new query. He has to evaluate the cooperated peer. Depending on the received result of that evaluation, the main peer will send multiple copies of the same query to multiple peers and then compare results. Moreover, we proposed another scenario to the manager of reputation by depending on Fog computing to enhance both performance and privacy. Relying on this work, a user can determine the most suitable of many available cooperating peers, while avoiding the problems of putting up with an inappropriate cooperating or uncommitted peer. The proposed method would significantly contribute to developing most of the privacy techniques in the location-based services. We implemented the main functions of the proposed method to confirm its effectiveness, applicability, and ease of application.

As a result of the importance of privacy at present, especially with the modern applications and technologies that have spread in the last decade, many techniques and methods have appeared to preserve privacy and protect users' data from tracking, profiling, or identification. The most popular of these technologies are those which rely on peer-to-peer or third-party cooperation. But, by reviewing a significant portion of existing research articles related to privacy, we find considerable confusion amongst several concepts and ways of protection, such as the concept of cloak area, Anonymizer, cooperation, and Third Party Peers (TTP). In this research, we revisit and review these approaches, which contain an overlap between them to distinguish each one clearly with the help of graphs and to remove their ambiguity. In this way, we shall be able provide a ready-reckoner to those interested in this field to easily differentiate between them and thus work to develop them and provide new methods. In other words, this research seeks to enhance the privacy and security in smart applications and technologies in the IoT and smart city environments.

Resource discovery in unstructured peer-to-peer networks causes a search query to be flooded throughout the network via random nodes, leading to security and privacy issues. The owner of the search query does not have control over the transmission of its query through the network. Although algorithms have been proposed for policy-compliant query or data routing in a network, these algorithms mainly deal with authentic route computation and do not provide mechanisms to actually verify the network paths taken by the query. In this work, we propose an approach to deal with the problem of verifying network paths taken by a search query during resource discovery, and detection of malicious forwarding of search query. Our approach aims at being secure and yet very scalable, even in the presence of huge number of nodes in the network.