Blockchain-based Framework for Reducing Fake or Vicious News Spread on Social Media/Messaging Platforms

With social media becoming the most frequently used mode of modern-day communications, the propagation of fake or vicious news through such modes of communication has emerged as a serious problem. The scope of the problem of fake or vicious news may range from rumour-mongering, with intent to defame someone, to manufacturing false opinions/trends impacting elections and stock exchanges to much more alarming and mala fide repercussions of inciting violence by bad actors, especially in sensitive law-and-order situations. Therefore, curbing fake or vicious news and identifying the source of such news to ensure strict accountability is the need of the hour. Researchers have been working in the area of using text analysis, labelling, artificial intelligence, and machine learning techniques for detecting fake news, but identifying the source or originator of such news for accountability is still a big challenge for which no concrete approach exists as of today. Also, there is another common problematic trend on social media whereby targeted vicious content goes viral to mobilize or instigate people with malicious intent to destabilize normalcy in society. In the proposed solution, we treat both problems of fake news and vicious news together. We propose a blockchain and keyed watermarking-based framework for social media/messaging platforms that will allow the integrity of the posted content as well as ensure accountability on the owner/user of the post. Intrinsic properties of blockchain-like transparency and immutability are advantageous for curbing fake or vicious news. After identification of fake or vicious news, its spread will be immediately curbed through backtracking as well as forward tracking. Also, observing transactions on the blockchain, the density and rate of forwarding of a particular original message going beyond a threshold can easily be checked, which could be identified as a possible malicious attempt to spread objectionable content. If the content is deemed dangerous or inappropriate, its spread will be curbed immediately. The use of the Raft consensus algorithm and bloXroute servers is proposed to enhance throughput and network scalability, respectively. Thus, the framework offers a proactive as well as reactive, practically feasible, and effective solution for curtailment of fake or vicious news on social media/messaging platforms. The proposed work is a framework for solving fake or vicious news spread problems on social media; the complete design specifications are beyond scope of the current work and will be addressed in the future.

Coordinated Control of Voltage Balancers for the Regulation of Unbalanced Voltage in a Multi-Node Bipolar DC Distribution Network

In a bipolar DC distribution network, the unbalanced load resistance, line resistance and renewable energy source will cause an unbalanced current for each node of the neutral line and lead to its unbalanced voltage. This is a unique power quality problem of bipolar DC distribution networks, which will increase the power loss in the network and lead to overcurrent protection of the neutral line in serious cases. A voltage balancer can be adopted to suppress the unbalanced voltage and current. However, the existing literature does not consider the consistent application of multiple voltage balancers in a multi-node bipolar DC distribution network. This paper creatively proposes a consensus control topology combining primary control and secondary control in a radial multi-node bipolar DC distribution network with voltage balancers. In this paper, the formulas for the positive and negative current and duty cycle of a bipolar DC distribution network with voltage balancers are derived, and improved voltage balancer modeling based on a consensus algorithm is built. The radial multi-node bipolar DC distribution network is established in MATLAB/Simulink. The simulation results compare the consensus control with the traditional droop control and verify the effectiveness of the new control structure with voltage balancers.

A Blockchain-Based Efficient, Secure and Anonymous Conditional Privacy-Preserving and Authentication Scheme for the Internet of Vehicles

The rapid advancement in the area of the Internet of Vehicles (IoV) has provided numerous comforts to users due to its capability to support vehicles with wireless data communication. The exchange of information among vehicle nodes is critical due to the rapid and changing topologies, high mobility of nodes, and unpredictable network conditions. Finding a single trusted entity to store and distribute messages among vehicle nodes is also a challenging task. IoV is exposed to various security and privacy threats such as hijacking and unauthorized location tracking of smart vehicles. Traceability is an increasingly important aspect of vehicular communication to detect and penalize malicious nodes. Moreover, achieving both privacy and traceability can also be a challenging task. To address these challenges, this paper presents a blockchain-based efficient, secure, and anonymous conditional privacy-preserving and authentication mechanism for IoV networks. This solution is based on blockchain to allow vehicle nodes with mechanisms to become anonymous and take control of their data during the data communication and voting process. The proposed secure scheme provides conditional privacy to the users and the vehicles. To ensure anonymity, traceability, and unlinkability of data sharing among vehicles, we utilize Hyperledger Fabric to establish the blockchain. The proposed scheme fulfills the requirement to analyze different algorithms and schemes which are adopted for blockchain technology for a decentralized, secure, efficient, private, and traceable system. The proposed scheme examines and evaluates different consensus algorithms used in the blockchain and anonymization techniques to preserve privacy. This study also proposes a reputation-based voting system for Hyperledger Fabric to ensure a secure and reliable leader selection process in its consensus algorithm. The proposed scheme is evaluated with the existing state-of-the-art schemes and achieves better results.

Optimization of Consensus Mechanism for IoT Blockchain

The essence of blockchain is a decentralized distributed ledger system; the IoT is formed by accessing and interconnecting a large number of heterogeneous terminals and has a natural distributed feature. Therefore, the combination of the two IoT blockchains is widely optimistic. At the same time, due to the heterogeneity of IoT sensing terminals, limited computing storage, and data transmission capabilities, the IoT blockchain is facing greater challenges, among which cryptographic consensus technology has become a key issue. In this chapter, based on the summary of the current blockchain consensus algorithm, applicability to the IoT-blockchain has been analyzed, the application status of several major IoT-blockchain platforms and consensus mechanisms have been introduced, and also the IoT-blockchain research progress on optimization of consensus mechanism has been expounded. Looking forward to the optimization techniques of the IoT blockchain, potential research directions have been summarized.

Blockchain Primer

Blockchain technology has the potential to revolutionize several industries including finance, supply chain and logistics, healthcare, and more. This primer introduces readers to basic development skills to blockchain foundations including blockchain cryptography, the consensus algorithm, and smart contracts. Further, this primer explains stepwise how to implement and deploy basic data stores using blockchain with Python. The primer serves as a succinct introductory guide to blockchain foundations by relying on a case study illustrated with visuals together with instructions on implementation. This primer is intended for educators, students, and technology enthusiasts with foundational computer science and Python development skills.

Automotive Vulnerability Analysis for Deep Learning Blockchain Consensus Algorithm

In this study, future cars are attempting self-driving around the world. However, hacking, such as ECUs in automobiles, creates problems that are directly connected to human life. Therefore, this study wrote a paper that detects anomalies in such cars by field. As a related study, the study investigated the vulnerabilities of the automobile security committee and automobile security standards and investigated the detection of abnormalities in the hacking of geo-train cars using artificial intelligence’s LSTM and blockchain consensus algorithm. In addition, in automobile security, an algorithm was studied to predict normal and abnormal values using LSTM-based anomaly detection techniques on the premise that automobile communication networks are largely divided into internal and external networks. In the methodology, LSTM’s pure propagation malicious code detection technique was used, and it worked with an artificial intelligence consensus algorithm to increase security. In addition, Unity ML conducted an experiment by constructing a virtual environment using the Beta version. The LSTM blockchain consensus node network was composed of 50,000 processes to compare performance. For the first time, 100 Grouped Tx, 500 Channels were tested for performance. For the first time, the malicious code detection rate of the existing system was verified. Accelerator, Multichannel, Sharding, Raiden, Plasma, and Trubit values were verified, and values of approximately 15,000 to 50,000 were obtained. In this paper, we studied to become a paper of great significance on hacking that threatens human life with the development of self-driving cars in the future.

Development and Simulation of Motion Control System for Small Satellites Formation

In the paper, the problem of forming and maintaining the small satellites formation in the near-earth projected circular orbits is considered. The satellite formation reconfiguration and formation-keeping control laws are proposed by employing the passivity-based output feedback control. For the complete nonlinear and time-dependent dynamics of the relative motion of a pair of satellites in elliptical orbits, new combined control algorithms, including a consensus protocol, are proposed and analyzed. A comparison of the control modes using the passivity-based output feedback control and the proportional-differential controller with and without the consensus algorithm is given. On the basis of the passification method, the algorithm is obtained ensuring the stable motion of the slave satellite relative to the orbit of the master satellite. To improve the accuracy of the satellites’ positioning, a consensus protocol based on measurements of the relative positions of the satellites is proposed and studied. Computer simulations of the proposed algorithms for options to construct formations are provided for two projected circular orbits of 8 satellites, demonstrating the efficiency of the proposed control schemes. It is shown that the resulting passivity-based output feedback control provides better accuracy than the PD controller. It is also shown that the use of the consensus protocol further increases the positioning accuracy of the satellite constellation.