Blockchain Papers

Akash Shinde, K. S. Radha, Eesh Pratap Singh, Amresh Kushwaha

Event ticketing systems have long faced challenges such as counterfeiting, scalping, and lack of transparency in resale markets. To address these issues, this research presents the design and development of a blockchain-based ticketing platform that leverages Non-Fungible Tokens (NFTs) to ensure secure, transparent, and verifiable ticket distribution. The primary aim of the study is to explore how blockchain technology can enhance trust, eliminate fraud, and provide users with full ownership of their tickets. The proposed system employs smart contracts to automate ticket creation, distribution, and resale, thereby minimizing the need for intermediaries. Each ticket is represented as a unique NFT, guaranteeing authenticity and enabling traceability throughout its lifecycle. The methodology involves implementing a decentralized application where event organizers can mint NFT tickets, and users can securely purchase, transfer, or resell them using blockchain infrastructure. The results demonstrate that NFT-based tickets effectively prevent duplication and unauthorized sales while providing an immutable record of ownership. Additionally, organizers gain better control over pricing policies, while buyers benefit from secure transfers and enhanced transparency. In conclusion, this platform contributes to solving long-standing issues in the ticketing industry by combining blockchain’s immutability with NFTs’ uniqueness. The study highlights the potential of decentralized technologies to revolutionize digital ticketing, improve user trust, and create a more efficient event management ecosystem.

Hakam Dzakwan Diash, Vannesa Nathania, Mohammad Idhom, Trimono Trimono

The volatile and dynamic Ethereum (ETH) market demands an accurate predictive model to support investment decision making. The complexity of ETH time series data and the influence of various external factors make price prediction a challenge in itself. This study aims to develop an ETH price prediction model using a combined architecture of Convolutional Neural Network (CNN) and also Bidirectional Long Short-Term Memory (BiLSTM). CNN is used to extract local features from historical ETH closing price data, while BiLSTM models bidirectional temporal patterns. The dataset used includes ETH daily price from January 2020 to January 2025, which are obtained from Yahoo Finance and have gone through a normalization process and transformation into sequential form. The model is trained for 100 epochs with an early stopping mechanism to prevent overfitting and evaluated using the MAPE and coefficient of determination (R²) metrics. The evaluation results show that the CNN-BiLSTM model is able to predict ETH prices with a MAPE value of 2.8546% and an R² of 0.9415, indicating high performance in capturing actual data trends. This study shows that the hybrid CNN-BiLSTM approach is effective for Ethereum price prediction.

Hinata Nishino, Kazumasa Omote, Keita Emura

Nominative signatures allow us to indicate who can verify a signature, and they can be employed to construct a non-transferable signature verification system that prevents the signature verification by a third party in unexpected situations. For example, this system can prevent IOU/loan certificate verification in unexpected situations. However, nominative signatures themselves do not allow the verifier to check whether the funds will be transferred in the future or have been transferred.It would be desirable to verify the fact simultaneously when the system involves a certain money transfer such as cryptocurrencies/cryptoassets. In this paper, we propose a smart contract-based non-transferable signature verification system using nominative signatures. We pay attention to the fact that the invisibility, which is a security requirement to be held for nominative signatures, allows us to publish nominative signatures on the blockchain. Our system can verify whether a money transfer actually will take place, in addition to indicating who can verify a signature. We transform the Hanaoka-Schuldt nominative signature scheme (ACNS 2011, IEICE Trans. 2016) which is constructed over a symmetric pairing to a scheme constructed over an asymmetric pairing, and evaluate the gas cost when a smart contract runs the verification algorithm of the modified Hanaoka-Schuldt nominative signature scheme.

R R J Putra, Muhamad Nursalman, Fawwaz Kautsar

A diploma is a document or certificate given to someone who has completed formal education. Diplomas are generally used as a benchmark for someone to get a job and identity in the eyes of the social environment. Many people think that a diploma is something meaningful or essential, so diplomas are often faked which violates legal norms and violates someone's Intellectual Property Rights (IPR). To anticipate counterfeiting, in Indonesia, there is currently a National Diploma Numbering (PIN) system and an Online Diploma Verification System (SIVIL), but unfortunately, the diploma database storage is still centralized which still allows illegal hacking to occur. On this basis, this research was created to able to provide a safer and more reliable diploma recording system solution, by utilizing Blockchain technology it is possible that every diploma issued can also be turned into a digital asset in the form of an NFT diploma, which is easy to track without having to face traditional bureaucratic obstacles. The NFT diploma functions as a representation of ownership, academic credentials, or identity as a sign of a student's educational history. This research aims to determine the performance of the Blockchain storage system on the Polygon network using smart contracts and IPFS. Apart from that, this research will compare the performance with previous research that used Polygon's layer-1, namely Ethereum. In smart contract cost testing, it was found that each Polygon transaction fee only requires 2.26% of the Ethereum transaction fee. Meanwhile, Quality of Service testing resulted in a throughput of 48.6-49.6 Kbps, packet loss of 0%, and latency of 42.07-44.13 m/s. The results show the potential for better cost efficiency and performance on the Polygon network compared to Ethereum.

Yiran Peng, Chenheng Deng, Jiaqi Li, KinTak U

Abstract The image protection of non‐fungible tokens based on zero‐watermark methods has received widespread attention. However, on the one hand, existing zero‐watermark methods are often limited to complex texture changes in the host image, and the features for constructing the zero‐watermark are vulnerable to geometric attacks. On the other hand, a single watermark image cannot adapt to the diverse usage scenarios of non‐fungible tokens. This paper proposes a robust personalized zero‐watermark scheme to address the challenges above. Firstly, the image regions suitable for constructing zero‐watermarks are highlighted by the non‐uniform weighted reconstruction, and the U‐Net is introduced for feature extraction against the geometric attacks. At the same time, the watermark images generated by generative models that are suitable for the usage scenario have achieved zero‐watermark addition and protection for non‐fungible token image content. The proposed method has been experimentally verified to have a certain degree of robustness in geometric and non‐geometric attacks.

Xiaoqing Wen, Quanbi Feng, Hanzheng Lyu, Jianyu Niu · 6 authors

Rollups have emerged as a promising approach to improving blockchains' scalability by offloading transactions execution off-chain. Existing rollup solutions either leverage complex zero-knowledge proofs or optimistically assume execution correctness unless challenged. However, these solutions suffer from high gas costs and significant withdrawal delays, hindering their adoption in decentralized applications. This paper introduces TEERollup, an efficient rollup protocol that leverages Trusted Execution Environments (TEEs) to achieve both low gas costs and short withdrawal delays. Sequencers (system participants) execute transactions within TEEs and upload signed execution results to the blockchain with confidential keys of TEEs. Unlike most TEE-assisted blockchain designs, TEERollup adopts a practical threat model where the integrity and availability of TEEs may be compromised. To address these issues, we first introduce a distributed system of sequencers with heterogeneous TEEs, ensuring system security even if a certain proportion of TEEs are compromised. Second, we propose a challenge mechanism to solve the redeemability issue caused by TEE unavailability. Furthermore, TEERollup incorporates Data Availability Providers (DAPs) to reduce on-chain storage overhead and uses a laziness penalty mechanism to regulate DAP behavior. We implement a prototype of TEERollup in Golang, using the Ethereum test network, Sepolia. Our experimental results indicate that TEERollup outperforms zero-knowledge rollups (ZK-rollups), reducing on-chain verification costs by approximately 86% and withdrawal delays to a few minutes.

Authors unavailable

Blockchain is a distributed digital ledger that stores any data and can record data about the transaction of cryptocurrency and Non-Fungible Token (NFT) ownership.Recently, cryptocurrency has become the most commonly used blockchain, it provides the potential to help a large wide range of applications.People prefer online transactions for speed, convenience, and the ability to generate financial activities from anywhere while also benefiting from features such as increased security measures and digital record-keeping.In the blockchain, hashing generates the network for transactions.However, due to unexpected conditions or external attacks, transaction failures can occur and require high security.This research proposes the Edwards-curve Digital Signature Algorithm (EdDSA) based on the Proof of Work (PoW) consensus algorithm for mobile payment transfer to provide effective transaction and security.In the verification phase, the receivers utilize the sender's public key and the received signature to verify the message using the PoW approach.When compared to existing approaches like Robust Payment Routing with an Approximation Guarantee (RobustPay+) and Multiple Charges Payment Channel Network based on Routing Protocol (MPCN-RP), EdDSA-PoW achieves a better success ratio of 1.2 in 50 nodes and success ratio and fee of 0.96 and 0.10 in 200 nodes.The proposed method achieves better values of 1.5 in Average maximum fee and 39 in Average accepted payment in 50 nodes compared to existing methods like e-commerce payment, RobustPay+, and Cryptocurrency Transactionbased Graph Convolutional Network (CTGAN).

Vinisha Gladys Belshi J, G. Ramya, M Yuvarani

Digital art is becoming increasingly popular, and there is a growing demand for online platforms where art can be bought and sold. The purpose of this project is to develop a website that provides such a platform, where art listers can list their digital art pieces for sale, and users can bid on them. Non-fungible tokens (NFTs) provide a new way for artists and photographers to sell their work online. NFT photos and NFT pictures (digital art) can sell for millions of dollars – and there are a growing number of platforms that allow you to buy and sell these items. But what if there is a platform where you can build digital art as well as bid it without any pain. In this project we are building an Auction Application and with help of Python Flask with a feature called neural style transfer where we can build digital arts.

Praneetha Surapaneni, Sriramulu Bojjagani, Anup Kumar Maurya

The advancements in telecommunications are significantly benefiting the Internet of Vehicles (IoV) in various ways. Minimal latency, faster data transfer, and reduced costs are transforming the landscape of IoV. While these advantages accompany the latest improvements, they also expand cyberspace, leading to security and privacy concerns. Vehicles rely on trusted authorities for registration and authentication processes, resulting in bottleneck issues and communication delays. Moreover, the central trusted authority and intermediate nodes raise doubts regarding transparency, traceability, and anonymity. This paper proposes a novel vehicle authentication handover framework leveraging blockchain, IPFS, and hybrid computing. The framework uses a Proof of Reputation (PoR) consensus mechanism to improve transparency and traceability and the Elliptic Curve Cryptography (ECC) cryptosystem to reduce computational delays. The suggested system assures data availability, secrecy, and integrity while maintaining minimal latency throughout the vehicle re-authentication. Performance evaluations show the system’s scalability, with creating keys, encoding, decoding, and registration operations done rapidly. Simulation is performed using SUMO to handle vehicle mobility in an IoV environment. The findings demonstrate the practicality of the proposed framework in vehicular networks, providing a reliable and trustworthy approach for IoV communication.

Mohamed Hasan Omar, Islam Taj-Eddin, Nagwa M. Omar, Hosny Ibrahim

Traffic road violations are increasing continuously in crowded and big cities, which requires an automatic system for monitoring and detecting. This system should be accurate and secure against poisoning attacks that intend to delete some or all traffic violations. Accordingly, this study proposes a secure road traffic management system using the Internet of Things (IoT) and blockchain technology. The system uses a network of sensors, traffic signals, and cameras to track violating vehicles and record their violations in the blockchain. In the proposed system, we used deep learning models to recognize the vehicle identification number and type of traffic violations, and we stored the traffic violation data on the Ethereum test network. The proposed system consists of three steps: (1) vehicle information detection. (2) Type of violation detection. (3) Violation storage in the blockchain. The proposed secure road traffic management system uses blockchain, IoT, encryption, and authentication to increase violation detection and recording, processing speed, and communication delay, ultimately improving service quality and customer experience. The experimental results show that the proposed system is more accurate and secure than the other systems that have been proposed in recent research.

Sankalp Bhoyar, Sagar Chakraborty, Pahuni Choudhary, Kisor Ray · 5 authors

Decentralized finance is a revolutionary change in the financial system, using blockchain technology to build a diverse and open network of financial services. By cutting out middlemen, DeFi promotes financial equality and reaches out to more people. Smart contracts can complete transactions without the need for traditional banks to lower costs and improve efficiency in lending, borrowing, trading, and yield farming activities. The proposed research compares four leading DeFi lending protocols: AAVE, MAKERDAO, COMPOUND, and VENUS Finance. We have used Long Short-Term Memory (LSTM) neural networks to analyze historical data and measure key parameters, such as lending and borrowing rates, Total Value Locked (TVL), Market Capitalization, and token price dynamics. We found that AAVE and COMPOUND exhibit similar mean rates but AAVE offers more precise predictions. MAKER provides potentially higher returns but with a higher degree of unpredictability. VENUS, despite its precise predictions, yields the lowest returns due to its lower mean lending rate. Overall, the approach enhances the understanding of the dynamics within the DeFi ecosystem, helping stakeholders to make informed decisions. Index Terms—Decentralized, Blockchain, LSTM, Time Series Analysis.

Maha Ayub, Waiz Khan, Muhammad Umar Janjua

Abstract With the addition of multiple blockchain platforms in the ecosystem, the Dapp owners need to migrate their smart contracts from one platform to another to remain competitive , cost-effective, and secure. A smart contract is a piece of code that contain logic and data. To migrate a smart contract, whether it’s on the same blockchain platform or a different one, we need both its source code that represents the logic and data which indicate the state of the contract. The source code can be easily set up, but to complete the migration, we have to extract the current state of the contract. In this paper, we have developed an advanced state extraction technique that uses static analysis to analyze the smart contract’s call graph and events, and extracts the entire storage state from the storage trie, along with the proper associations across function calls, enabling users to visualize, manage, and transform the state as desired for migration. The soundness of the extracted state was confirmed using the method of abstract interpretation. Further, the migration adapter is designed that transform extracted state into slot-value pair and migrated it to the target blockchain. Our new approach has allowed us to analyze 14% more smart contracts with the extraction of 15% more data from 67,993 contracts, and migrate some of them to the Polygon test-net.

Abdulrahman AlMeasam, Fatma AlQubaisi, Shoug Ahmed, Ahmed Alsuwaidi · 5 authors

Nowadays with the rising number of personal vehicles, finding a parking space has become an issue for many residents.Advancements in technologies like Internet of Things (IoT) have helped to maximize the productivity and reliability of urban infrastructure.In this paper, we propose an online parking rent system to reserve a parking space for the residents and other users, via a blockchain on the Ethereum platform which uses a non-fungible token as currency and a barcode for ease of use.A barcode will be provided while reserving the parking space, and is used when unlocking the bollards.This will help residents to save time by knowing their parking spot.

Fares Alharbi, Mohammed Zakariah, Reem Alshahrani, Ashwag Albakri · 6 authors

License Plate Recognition (LPR) is essential for the Internet of Vehicles (IoV) since license plates are a necessary characteristic for distinguishing vehicles for traffic management. As the number of vehicles on the road continues to grow, managing and controlling traffic has become increasingly complex. Large cities in particular face significant challenges, including concerns around privacy and the consumption of resources. To address these issues, the development of automatic LPR technology within the IoV has emerged as a critical area of research. By detecting and recognizing license plates on roadways, LPR can significantly enhance management and control of the transportation system. However, implementing LPR within automated transportation systems requires careful consideration of privacy and trust issues, particularly in relation to the collection and use of sensitive data. This study recommends a blockchain-based approach for IoV privacy security that makes use of LPR. A system handles the registration of a user's license plate directly on the blockchain, avoiding the gateway. The database controller may crash as the number of vehicles in the system rises. This paper proposes a privacy protection system for the IoV using license plate recognition based on blockchain. When a license plate is captured by the LPR system, the captured image is sent to the gateway responsible for managing all communications. When the user requires the license plate, the registration is done by a system connected directly to the blockchain, without going through the gateway. Moreover, in the traditional IoV system, the central authority has full authority to manage the binding of vehicle identity and public key. As the number of vehicles increases in the system, it may cause the central server to crash. Key revocation is the process in which the blockchain system analyses the behaviour of vehicles to judge malicious users and revoke their public keys.

Ohm Patel

The current Layer 1 blockchain, such as Ethereum and Bitcoin, has several problems related to scalability and cost.Layer 1 blockchain networks have always been a struggle for Ethereum over scalability.Many of these factors can be attributed to the network's nature of linear processing of transactions.During high traffic, these networks get crowded, slow the transaction time, and charge high fees.For many industries, these have made blockchains unusable, even though previously, I described them as getting from bad to worse in terms of functionality.To tackle these issues, developers have a singular aim in mindto craft blockchain scaling solutions that improve efficiency, expand capacity, and bring down costs of transactions so that blockchains can deliver the high performance demanded of them to match today's digital world.Rollups have become one of the most promising innovations in satisfying the stated need.Rollups can be described as a particular class of blockchains whose primary function is to increase the transactional capacity.Rollups, in the case of blockchain, are 'layer 2' scaling solutions that improve the transaction rate of the blockchain network.Thus, "Rollups" accurately name what they dothey combine several transactions into batches outside the mainstream network before performing these operations as one transaction in the mainnet.

T. Haritha, A. Anitha

In crowded cities, searching for the availability of parking lots is a herculean task as it results in the wastage of drivers’ time, increases air pollution, and traffic congestion. Smart parking systems facilitate the drivers to determine the information about the parking lot in real time and book them depending on the requirement. But the existing smart parking systems necessitate the drivers to reveal their sensitive information that includes their mobile number, personal identity, and desired destination. This disclosure of sensitive information makes the existing centralized smart parking systems more vulnerable to service providers’ security breaches, single points of failure, and bottlenecks. In this paper, an Improved Asymmetric Consortium Blockchain and Homomorphically Computing Univariate Polynomial-based private information retrieval (IACB-HCUPPIR) scheme is proposed to ensure parking lots’ availability with transparency security in a privacy-preserving smart parking system. In specific, an improved Asymmetric Consortium Blockchain is used for achieving secure transactions between different parties interacting in the smart parking environment. It further adopted the method of Homomorphically Computing Univariate Polynomial-based private information retrieval (HCUPPIR) scheme for preserving the location privacy of drivers. The results of IACB-HCUPPIR confirmed better results in terms of minimized computation and communication overload with throughput, latency, and response time with maximized drivers’ privacy preservation. Moreover, the proposed fully homomorphic algorithm (FHE) was compared against partial-homomorphic encryption (PHE) and technique without encryption and found that the proposed model has quick communication in allocating the parking slots starting with 24.3 s, whereas PHE starts allocating from 24.7 s and the technique without encryption starts at 27.4 s. Thus, we ensure the proposed model performs well in allocating parking slots with less time and high security with privacy preservation.

T. Shanthi, M. Ramprasath, A. Kavitha, T. Muruganantham

The latest 6G improvements secured autonomous driving's realism in Intelligent Autonomous Transport Systems (IATS). Despite the IATS's benefits, security remains a significant challenge. Blockchain technology has grown in popularity as a means of implementing safe, dependable, and decentralised independent IATS systems, allowing for more utilisation of legacy IATS infrastructures and resources, which is especially advantageous for crowdsourcing technologies. Blockchain technology can be used to address security concerns in the IATS and to aid in logistics development. In light of the inadequacy of reliance and inattention to rights created by centralised and conventional logistics systems, this paper discusses the creation of a blockchain-based IATS powered by deep learning for secure cargo and vehicle matching (BDL-IATS). The BDL-IATS approach utilises Ethereum as the primary blockchain for storing private data such as order and shipment details. Additionally, the deep belief network (DBN) model is used to select suitable vehicles and goods for transportation. Additionally, the chaotic krill herd technique is used to tune the DBN model’s hyperparameters. The performance of the BDL-IATS technique is validated, and the findings are inspected under a variety of conditions. The simulation findings indicated that the BDL-IATS strategy outperformed recent state-of-the-art approaches.

Zichi Wang, Xin Feng, Xinpeng ZHANG

The images with non-fungible token (NFT) are employed as the digital artistic works in metaverse for creation, transaction, sharing, and collection.Being different from natural images, the content of NFT images is defined by user and distributed in the digital space widely.It is convenient for the hidden of secret data.In this case, covert communication with NFT images is a new branch of image steganography.Then, a steganographic method for NFT images was proposed accordingly.Given a NFT image, the regions of its profile and the components with high frequency were enhanced firstly to enrich the details which were beneficial to hide the modification trace of steganography.In this way, the enhanced image was used as cover since it is more suitable for steganography.Then, the tendency modification direction of each pixel was determined by the differences between the enhanced image and the given image.The differences were also used to determine the cost value of modification amplitude.Thus, the undetectability of steganography can be increased further.Secret data was embedded into the cover image using the popular steganographic coding schemes.Experimental results showed that the proposed method had imporoved undetectability on NFT images compared with existing digital steganographic schemes.Compared with HILL, MiPOD, and DEFI, the proposed method can increase the detection error P_E of steganalysis by 8.7%, 9.2% and 6.2%, respectively (the average value for the cases of different payload and steganalytic features).Therefore, the proposed method is suitable for NFT images and it provides targeted steganographic method for the third kind of images, i.e., NFT images, except of natural images and generated images.For further study, the deep learning-based steganographic method can be designed for NFT images using the strong fitting and learning ability of neural networks.

Riya Kakkar, Jafar A. Alzubi, Amit Dua, Smita Agrawal · 9 authors

In most countries, traffic congestion has reached a level where managing traffic is tedious for regulatory bodies. The traffic management faced many issues such as route routing based on congestion, delivery of messages/emails to end-users, and real-time allocation of parking slots. There have been many works on predicting parking prices for traffic management, but most favor users or owners and are not secure. To address these issues, a blockchain and Interplanetary File System (IPFS)-based parking price prediction scheme (PADaaV) is proposed to facilitate the users to reserve a parking slot securely and efficiently. It mainly focuses on ensuring security, privacy, and transparency for parking slot owners and users. Furthermore, we employ a second price auction model to optimize the parking price for users, and parking slot owners can also get benefit from it. The performance of the PADaaV has been simulated for 100 users with 40 parking slots based on different auction models. The various performance parameters considered are profit for users, profit for parking slot owners, overall revenue of the system, scalability, computation time, and data storage cost. The performance results show that the PADaaV is secure and beneficial for users and parking slot owners.

Iago Sestrem Ochôa, Valderi Reis Quietinho Leithardt, Leonardo Calbusch, Juan F. De Paz · 7 authors

Since the early 2000s, life in cities has changed significantly due to the Internet of Things (IoT). This concept enables developers to integrate different devices collecting, storing, and processing a large amount of data, enabling new services to improve various professional and personal activities. However, privacy issues arise with a large amount of data generated, and solutions based on blockchain technology and smart contract have been developed to address these issues. Nevertheless, several issues must still be taken into account when developing blockchain architectures aimed at the IoT scenario because security flaws still exist in smart contracts, mainly due to the lack of ease when building the code. This article presents a blockchain storage architecture focused on license plate recognition (LPR) systems for smart cities focusing on privacy, performance, and security. The proposed architecture relies on the Ethereum platform. Each smart contract matches the privacy preferences of a license plate to be anonymized through public encryption. The storage of data captured by the LPR system can only be done if the smart contract enables it. However, in the case of motivation foreseen by the legislation, a competent user can change the smart contract and enable the storage of the data captured by the LPR system. Experimental results show that the performance of the proposed architecture is satisfactory, regarding the scalability of the built private network. Furthermore, tests on our smart contract using security and structure analysis tools on the developed script demonstrate that our solution is fraud-proof. The results obtained in all experiments bring evidence that our architecture is feasible to be used in real scenarios.

Mohamed Salb, Ali Elsadai, Miodrag Živković, Nebojša Bačanin Džakula

Predicting the market behaviour is a crucial task for cryptocurrency investors. Based on the prediction, they make decisions that will either bring profit or loss. The prediction is typically involves the historical data that is used to forecast the future behaviour of the prices on the market. Prediction is based on the machine learning approach. The nature-inspired algorithms have been successfully applied in optimization of numerous machine learning models in the recent years. Swarm intelligence metaheuristics, a family of nature-inspired algorithms, have proven to be excellent optimizers not only in the machine learning domain, but in various other practical domains as well. This paper proposes one such approach, more precisely the enhanced version of the sine cosine algorithm to optimize the support vector machine, and use it to predict the cryptocurrency prices. The basic SCA was improved with a simple exploration mechanism, and then compared to other approaches executed on the same datasets. The results obtained from the performed experimental simulations indicate that the proposed method achieved better performances than other approaches included in the research.

Mustufa Haider Abidi

The development in stock market prediction is represented as a significant role and it received immense interest as predicting stock prices effectively which cause striking profits by creating appropriate decisions. Stock market prediction is the most important confronts on account of non-stationary, blaring, and chaotic data. Hence, prediction turns out to be demanding between investors to invest the money in order to make earnings. At first, to blockchain Network Bridge the blockchain network is subjected from that bitcoin data is obtained which is pursued with the prediction of bitcoin. The developed Raindrop optimization method based on Deep LSTM is used for the prediction of Bitcoin. Initially, based on the Rate of Change Rate (ROCR), Average True Range (ATR), Double Exponential Moving Average (DEMA), Simple Moving Average (SMA), and Moving Average Convergence Divergence (MACD) flow strength indicators are extracted from the blockchain data. On the basis of the extracted features, the prediction is performed exploiting Raindrop optimization algorithm-based Deep LSTM, which is a combination of Raindrop optimization algorithm with Deep LSTM. Subsequently, the Raindrop optimization algorithm is used to determine the optimal weights in Deep LSTM. The simulation of the developed algorithm is done from the explicitly accessible dataset. The examination of technique regarding MAE and RMSE shows that the developed method attained a minimal Mean Absolute Error (MAE) and the minimal Root Mean Squared Error (RMSE) correspondingly.

Rishikesh Kale

Every kind of business depends on the evolving technologies that tend to take advantages of new opportunities. With every new technology, different set of challenges appear. In recent years, numerous blockchain-based applications have been proposed to solve problems in different areas. In this paper, an adaptive strategy is proposed to eliminate driving license frauds using blockchain technology. With second generation of blockchain technologies, smart contracts have helped to develop trust and automated transactions between large numbers of users. Smart Contracts are programs that run on the blockchain to take action on the records. This paper proposes a driving license registration and verification smart contract using Ethereum blockchain. The smart contract mechanism allows for registration of the officers/agents by a higher authority. It can dynamically restrict unregistered officer/fraud agents from generating fake driving license. Also, the smart contract facilitates verification of a registered driving license which includes checking its validity and authorization. It provides special rights to the traffic regulator officer to add remarks to the driving license if the driving license holder is found violating the traffic rules. Since the blockchain is an immutable ledger, this remark cannot be tampered and the apprehended person would be liable to pay the fines. This would result in reduction of traffic accidents and violation of traffic rules. This smart contract opens up doors for more innovations in this field and improves traffic regulation and management.

Dipti Pawade, Avani Sakhapara, Raj shah, Siby Thampi · 5 authors

There are large numbers of vehicles in the populated country like India. It's a very common scenario that traffic police came across some vehicle random vehicle and had some doubt in mind but do not have in hand information about that vehicle and end up leaving that thought. Sometimes this may result in some disaster. With the advent of technology, there are mobile applications and web based systems are available to ease up the process by which traffic police can fine the vehicle owner or people can pay the fine online. But yet there is no system is available through which traffic police can get all the details about the particular vehicle. This motivated us to design and developed an application thorough which traffic police can get all the information right from owner of the vehicle to its RC book and insurance status on just one click. Looking at the chances of data tampering, we have also played an attention to the data security and used blockchain for creating distributed, robust and tempered proof system. In this paper we have discussed traffic police assistance system, which can scan the vehicle number plate, identify the number and provide the all the information and documents stored against that vehicle number. To address the issue of data security and alteration of sensitive data blockchain is used so that any alteration can be monitored. As the complete information process is dependent on how correctly the vehicle number is identified, so the number plate recognition module is tested thoroughly under various conditions. Finally user feedback is taken and analyzed to evaluate the feasibility and usability of the proposed application.