Internet of Things (IoT)-based devices, especially those used for home automation, consist of their own sensors and generate many logs during a process. Enterprises producing IoT devices convert these log data into more useful data through secondary processing; thus, they require data from the device users. Recently, a platform for data sharing has been developed because the demand for IoT data increases. Several IoT data marketplaces are based on peer-to-peer (P2P) networks, and in this type of marketplace, it is difficult for an enterprise to trust a data owner or the data they want to trade. Therefore, in this study, we propose a review system that can confirm the reputation of a data owner or the data traded in the P2P data marketplace. The traditional server-client review systems have many drawbacks, such as security vulnerability or server administrator’s malicious behavior. However, the review system developed in this study is based on Ethereum smart contracts; thus, this system is running on the P2P network and is more flexible for the network problem. Moreover, the integrity and immutability of the registered reviews are assured because of the blockchain public ledger. In addition, a certain amount of gas is essential for all functions to be processed by Ethereum transactions. Accordingly, we tested and analyzed the performance of our proposed model in terms of gas required.

No abstract

This paper describes the efficient selective encryption scheme for H.264/SVC. The proposed scheme encrypts with three domains in hierarchical layers using different keys: the intra prediction modes, the motion vector difference values and the sign bits of the texture data. The features of the proposed scheme are as follow. The proposed scheme offers 1) the computational efficiency by encrypting domains selectively according to each layer type, 2) the time efficiency through the light-weight encryption, 3) the security through the use of mutually different keys, and 4) the format compliance by utilizing the H.264/SVC structure and method. Fourth International Conference on Networked Computing and Advanced Information Management 978-0-7695-3322-3/08 $25.00

No abstract

No abstract