Welcome to IOTBC 2024

2nd International Conference IOT, Blockchain and Cryptography (IOTBC 2024)

March 09 ~ 10, 2024, Virtual Conference

Accepted Papers
Lottocoin: Increasing Velocity of Crytocurrencies

Kimaya Basu, Thomas H. Austin, and Justin Rietz, Cupertino, CA, USA, San José State University, San Jose, CA, USA


Since the introduction of Bitcoin, blockchain-based cryptocurrencies have exploded in popularity. Several blockchains have introduced various improvements over Bitcoin's design. However, many of these same blockchains struggle to generate interest from clients, who often want to participate in the more active blockchains. Even more so, those interested in running mining rigs or validators may be reluctant to invest their funds in a blockchain that does not show signs of activity. In this paper, we introduce LottoCoin, where new rewards are randomly generated for clients who participate in the blockchain. The chance of selection is based on the transaction fees given by the client, thus encouraging greater activity (velocity of money) with greater amounts of coins paid to the miners/validators. By encouraging activity on the blockchain, LottoCoin seeks to generate greater interest for investors providing the infrastructure. Through economic analysis and a simulation using the SpartanGold blockchain framework, we show that the addition of a gambling mechanism can be used to drive adoption of a new blockchain.

Cryptographic Protocols for Electronic Voting System

Ezekiel Ologunde, University of Baltimore, Baltimore, Maryland, USA


This paper explores the critical role of cryptographic protocols in strengthening the integrity of electronic voting systems, thereby preserving and reinforcing democratic ideals. It delves into advancements in homomorphic encryption, post-quantum cryptography, and zero-knowledge proofs, which are fundamental to ensuring the security and privacy of online voting systems. The study also investigates robust auditing processes, including using blockchain technology for transparency and risk-limiting audits. Furthermore, it advocates for stricter regulations for private companies involved in electronic voting and emphasizes the importance of user-friendly cryptographic interfaces and educational initiatives. The research integrates human factors research and addresses legal and ethical considerations of online voting cryptographic protocols. The findings underscore the need for a multi-faceted approach to realize secure, reliable, and user-friendly online voting systems.


Cryptographic protocol, Security,Online Voting.

Leveraging Nft’s for Secured Decentralized Lending ”a Defi Solution

Abhishek T, Chanadan M S, Darshan G A, Vyshnavi G, and Dr Vinodha K, PES UNIVERSITY, Bangalore, Karnataka, India


In the evolving world of technology and digital assets non fungible tokens (NFTs) have emerged as the latest advancement. These digital assets represent ownership of intangible items. Hold significant value. Unlike cryptocurrencies, like Ethereum or Bitcoin NFTs cannot be exchanged due to their nature. Each NFT has an indivisible value. NFTs not pave the way for financial services but also open up fresh opportunities for creators, buyers and artists.To revolutionize financing in the DeFi space this proposed approach utilizes NFTs generated from digital arts. By eliminating intermediaries this innovative method ensures trust and security in transactions. The idea entails automating borrower lender interactions through contracts while securely storing data using blockchain technology. Borrowers can obtain funding by leveraging assets such as estate, artwork and collectibles that’re often illiquid. The key component of this system is contracts that independently execute lending agreements and collateral transfers within predefined parameters. By leveraging the Ethereum blockchain this project aims to provide consumers with access, to a platform offering a wide range of financial services.The demonstration illustrates the process of managing NFT lending and borrowing through contracts providing a secure and trustworthy transaction environment.


NFTs , Decentralized lending,Smart contracts ,Decentralized Finance(DeFi), Collateral.

The Mathematics Behind Cryptocurrencies “a Statistical Analysis of Cryptocurrencies

Masoud Eshaghinasrabadi-California State University, Northridge, USA


This article undertakes an extensive statistical examination of significant cryptocurrencies, expanding on the groundwork in the previous report, "A Statistical Analysis of Cryptocurrencies." Our study delves into the dynamics of Bitcoin, Ethereum, Tether, Binance, Ripple, Cardano, Solana, and Dogecoin, utilizing trading prices from 2017 to 2022 and considering significant events like the COVID-19 pandemic. Employing correlation analysis, our investigation aims to unravel the intricate relationships between these leading cryptocurrencies. The findings underscore the necessity of achieving greater independence among candidate distributions to accurately model the return of all popular cryptos, suggesting an enhanced correlation among some. The generalized hyperbolic and generalized t distributions emerged as top-performing models despite limitations in overall fitness that varied across cryptocurrencies, with Tether exhibiting the least favorable fit. Using the fitted models, we forecasted average daily returns from January 1st to February 1st, 2023, demonstrating generally reliable predictive validity. These insights are pivotal in understanding cryptocurrency movements and mitigating the associated trading risks.


Cryptocurrency Dynamics, StatisticalExamination, GroundworkExpansion, CorrelationAnalysis, CandidateDistributions, Independence Modeling, Generalized Hyperbolic Distribution, Generalized t Distribution., Predictive Validity, Trading Risks, Bitcoin, Ethereum, Tether, Binance, Ripple, Cardano, Solana, Dogecoin, Trading Prices, COVID-19 Impa.

On the Construction of Perfect Keyword Secure Peks Scheme

Indranil Ghosh Ray


With the growing popularity of cloud computing, searchable encryption has become centre of attraction to enhance privacy and usability of the shared data. First searchable encryption scheme under the public key setting was proposed by Bonah et al. which is known as PEKS. In the PEKS scheme, one can easily link between cipher text and the trapdoor. In Information Sciences 2017 paper, Huang et al. proposed a public key SE scheme. In this scheme, encryption of a document or keyword requires the secret key of the data sender. The data sender generates ciphertexts, and upload them onto the cloud server. The data receiver generates trapdoors depending upon the public key of the sender and its own secret key. Thus, the PEKS scheme of Huang et al. circumvents the above attack by linking the ciphertext and the trapdoor to the key of the sender. However no work is available in the literature to stop attacks against linking user key and cipher text and server key and cipher text. In this paper we address these issues. We formalize the two new security notions, namely UKI-security and SKI-security. We have shown that our scheme is secure under these newly introduced security notions.

The Covid Shock, the Rise of Defi, and Bitcoin’s Increasing Market Risk

Bruce D. McNevin1 and Joan Nix2, 1Chief Data Scientist, Unlimited Funds, 2Associate Professor of Economics, Queens College (CUNY)


This paper aims to determine whether Bitcoin’s market risk increased in response to the COVID-19 shock. Our analysis employs familiar asset pricing models used by investment managers. Our main result is that Bitcoin’s market risk increased after the lockdown in March 2020. Wavelet analysis that captures both time and scale changes is introduced, and risk estimates that allow for both time and scale changes are provided, consistent with our main finding. From the standpoint of traditional investments, we find that the market risk of a Bitcoin investment after March 2020 is similar to that of a risky tech stock.


Blockchain, Bitcoin, DeFi, Ethereum, Wrapped Bitcoin, CAPM, Fama/French.

Efficient Storage of Heterogeneous Iot Data in a Blockchain Using an Indexing Method in Metric Space

K. Khettabi, B. Farou, Z. Kouahla, and H. Seridi, LabSTIC Laboratory, Department of Computer Science, 8 Mai 1945 University, Guelma 24000, Algeria


In this work, we proposed a IoT data indexing method to surpass some challenges encountered during the use of hashing in the storage of data in a blockchain. The indexing method was developed in metric space in which no dimensions are considered and only distance between objects is taken into account. The proposed method consisted on putting the index in the inner of a block. The index, called GHB-tree is based on space partitioning using hyperplane. The proposed approach was tested using two datasets of close size and different dimensions. The experimental results showed that the proposed method is efficient and competitive to other storing methods since the queries retrieve time is very reduced to be expressed by millisecond compared with that of other blockchains.


lockchains, IoT data indexing, Metric space, k-NN search method, Retrieve time.