With the gradually opening of energy markets and popularization of Electric Vehicles (EVs), EVs can transmit, dispatch and recharge energy in different markets and domains dynamically. However, in Vehicular Energy Network, EVs may randomly enter and leave a market, it imposes a difficult problem in that how to schedule and distribute energy effectively. Additionally, the location of EV owners usually includes sensitive information such as home addresses, company names, hospital traces, and so on, which may be collected by attackers and may result in the privacy leakage about EV owners. In this paper, we propose a decentralized blockchain-enabled energy trading scheme that can trade cross over various domains efficiently, which enables reliable transactions between EVs and energy nodes within short processing delay. It can also preserve the privacy of EV owners, by adopting the k-anonymity method in constructing a united request to hide the location information and creating a clocking area based on undirected graphs. Even though the server is maliciously attacked, the attacker cannot distinguish among EV owners, which breaks the linkage between real locations and identities to preserve EV owners' privacy. Finally, we conduct a comprehensive experimental evaluation to evaluate the trading performance and location privacy protection performance. The simulation results show that our proposed architecture outperforms over most state-ofthe-art schemes in terms of processing delay and location privacy awareness. INDEX TERMS Vehicular energy networks, Energy trading, K-anonymity, Location privacy, Blockchain Recently, blockchain technology has emerged as a promis
As a significant part of the Internet of things, wireless sensor networks (WSNs) is frequently implemented in our daily life. Data aggregation in WSNs can realize limited transmission and save energy. In the process of data aggregation, node data information is vulnerable to be eavesdropped and attacked. Therefore, it is of great significance to the research of data aggregation privacy protection in WSNs. We propose a secure and efficient privacy-preserving data aggregation algorithm (SECPDA) based on the original clustering privacy data aggregation algorithm. In this algorithm, we utilize SEP protocol to dynamically select cluster head nodes, introduce slicing idea for the private data slicing, and generate false information for interference. A comprehensive experimental evaluation is conducted to assess the data traffic and privacy protection performance. The results demonstrate that the proposed SECPDA algorithm can effectively reduce data traffic and further improve data privacy of nodes.
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