ELD: Adaptive Detection of Malicious Nodes under Mix-Energy-Depleting-Attacks Using Edge Learning in IoT Networks

2020 ◽  
pp. 255-273
Author(s):  
Zuchao Ma ◽  
Liang Liu ◽  
Weizhi Meng
Keyword(s):  
Adaptive Detection ◽  
Malicious Nodes

Security based on Received Signal Strength in Localization for Underwater Sensor Networks

2016 ◽  
Vol 1 (2) ◽  
pp. 1-7
Author(s):  
Karamjeet Kaur ◽  
Gianetan Singh Sekhon
Keyword(s):  
Sensor Networks ◽  
Threshold Value ◽  
Critical Issue ◽  
Sensor Nodes ◽  
Underwater Sensor Networks ◽  
Research Subjects ◽  
Malicious Nodes ◽  
Intermediate Node ◽  
End To End Delay ◽  
End To End

Underwater sensor networks are envisioned to enable a broad category of underwater applications such as pollution tracking, offshore exploration, and oil spilling. Such applications require precise location information as otherwise the sensed data might be meaningless. On the other hand, security critical issue as underwater sensor networks are typically deployed in harsh environments. Localization is one of the latest research subjects in UWSNs since many useful applying UWSNs, e.g., event detecting. Now day’s large number of localization methods arrived for UWSNs. However, few of them take place stability or security criteria. In purposed work taking up localization in underwater such that various wireless sensor nodes get localize to each other. RSS based localization technique used remove malicious nodes from the communication intermediate node list based on RSS threshold value. Purposed algorithm improves more throughput and less end to end delay without degrading energy dissipation at each node. The simulation is conducted in MATLAB and it suggests optimal result as comparison of end to end delay with and without malicious node.

Two-stage grasp strategy combining CNN-based classification and adaptive detection on a flexible hand

2020 ◽  
Vol 97 ◽  
pp. 106729
Author(s):  
Xiaoyan Chen ◽  
Yilin Sun ◽  
Qiuju Zhang ◽  
Fei Liu
Keyword(s):  
Adaptive Detection ◽  
Two Stage

scholarly journals Credible Peer-to-Peer Trading with Double-Layer Energy Blockchain Network in Distributed Electricity Markets

Electronics ◽  
2021 ◽  
Vol 10 (15) ◽  
pp. 1815
Author(s):  
Longze Wang ◽  
Yu Xie ◽  
Delong Zhang ◽  
Jinxin Liu ◽  
Siyu Jiang ◽  
...  
Keyword(s):  
Double Layer ◽  
Electricity Markets ◽  
Electricity Market ◽  
Peer To Peer ◽  
Malicious Nodes ◽  
Energy Trading ◽  
Contract Performance ◽  
Trading Model ◽  
Consensus Information ◽  
Available Information

Blockchain-based peer-to-peer (P2P) energy trading is one of the most viable solutions to incentivize prosumers in distributed electricity markets. However, P2P energy trading through an open-end blockchain network is not conducive to mutual credit and the privacy protection of stakeholders. Therefore, improving the credibility of P2P energy trading is an urgent problem for distributed electricity markets. In this paper, a novel double-layer energy blockchain network is proposed that stores private trading data separately from publicly available information. This blockchain network is based on optimized cross-chain interoperability technology and fully considers the special attributes of energy trading. Firstly, an optimized ring mapping encryption algorithm is designed to resist malicious nodes. Secondly, a consensus verification subgroup is built according to contract performance, consensus participation and trading enthusiasm. This subgroup verifies the consensus information through the credit-threshold digital signature. Thirdly, an energy trading model is embedded in the blockchain network, featuring dynamic bidding and credit incentives. Finally, the Erenhot distributed electricity market in China is utilized for example analysis, which demonstrates the proposed method could improve the credibility of P2P trading and realize effective supervision.

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