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2020-09-21
Wang, Zan-Jun, Lin, Ching-Hua Vivian, Yuan, Yang-Hao, Huang, Ching-Chun Jim.  2019.  Decentralized Data Marketplace to Enable Trusted Machine Economy. 2019 IEEE Eurasia Conference on IOT, Communication and Engineering (ECICE). :246–250.
Transacting IoT data must be different in many from traditional approaches in order to build much-needed trust in data marketplaces, trust that will be the key to their sustainability. Data generated internally to an organization is usually not enough to remain competitive, enhance customer experiences, or improve strategic decision-making. In this paper, we propose a decentralized and trustless architecture through the posting of trade records while including the transaction process on distributed ledgers. This approach can efficiently enhance the degree of transparency, as all contract-oriented interactions will be written on-chain. Storage via an end-to-end encrypted message channel allows transmitting and accessing trusted data streams over distributed ledgers regardless of the size or cost of the device, while simultaneously making a verifiable Auth-compliant request to the platform. Furthermore, the platform will complete matching, trading and refunding processes with-out human intervention, and it also protects the rights of data providers and consumers through trading policies which apply revolutionary game theory to the machine economy.
2020-09-04
Ichsani, Yuditha, Deyani, Resisca Audia, Bahaweres, Rizal Broer.  2019.  The Cryptocurrency Simulation using Elliptic Curve Cryptography Algorithm in Mining Process from Normal, Failed, and Fake Bitcoin Transactions. 2019 7th International Conference on Cyber and IT Service Management (CITSM). 7:1—8.
On each cryptocurrency transaction, a high-level security is needed to protect user data as well as data on the transaction. At this stage, it takes the appropriate algorithm in securing transactions with more efficient processing time. The Elliptic Curve Cryptography (ECC) is one of the cryptography algorithms which has high-level security, and ECC is often compared with the Rivest, Shamir, and Adleman (RSA) algorithm because it has a security level that is almost the same but has some differences that make ECC is superior compared to the RSA algorithm, so that the ECC algorithm can optimize cryptocurrency security in the transaction process. The purpose of this study is to simulate the bitcoin transactions using cryptography algorithms. This study uses the ECC algorithm as the algorithm ECDH and ECDSA key exchange as the algorithm for signing and verifying. The comparison results of ECC and RSA processing time is 1:25, so the ECC is more efficient. The total processing time of ECC is 0,006 seconds and RSA is 0,152 seconds. The researcher succeeded to implement the ECC algorithm as securing algorithms in mining process of 3 scenarios, normal, failed, and fake bitcoin transactions.
2020-03-30
Ximenes, Agostinho Marques, Sukaridhoto, Sritrusta, Sudarsono, Amang, Ulil Albaab, Mochammad Rifki, Basri, Hasan, Hidayat Yani, Muhammad Aksa, Chang Choon, Chew, Islam, Ezharul.  2019.  Implementation QR Code Biometric Authentication for Online Payment. 2019 International Electronics Symposium (IES). :676–682.
Based on the Indonesian of Statistics the level of society people in 2019 is grow up. Based on data, the bank conducted a community to simple transaction payment in the market. Bank just used a debit card or credit card for the transaction, but the banks need more investment for infrastructure and very expensive. Based on that cause the bank needs another solution for low-cost infrastructure. Obtained from solutions that, the bank implementation QR Code Biometric authentication Payment Online is one solution that fulfills. This application used for payment in online merchant. The transaction permits in this study lie in the biometric encryption, or decryption transaction permission and QR Code Scan to improve communication security and transaction data. The test results of implementation Biometric Cloud Authentication Platform show that AES 256 agents can be implemented for face biometric encryption and decryption. Code Scan QR to carry out transaction permits with Face verification transaction permits gets the accuracy rate of 95% for 10 sample people and transaction process gets time speed of 53.21 seconds per transaction with a transaction sample of 100 times.