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Small-pixel is one of the development directions of InSb infrared focal plane devices, but it will have a greater impact on the photocurrent response and crosstalk of the device. Therefore, the mesa junction device model, the planar junction device model and the epitaxial device model of the small-pixel InSb infrared focal plane array device are established using Sentaurus TCAD software. The back-incident three-pixel InSb array devices are used to simulate the photocurrent response and crosstalk of the three device models. The results show that the photocurrent response can be increased and the crosstalk can be reduced for the mesa junction device and the planar junction device by reducing device thickness and increasing junction depth, and the photocurrent response and crosstalk can be improved for the epitaxial InSb device by increasing the thickness of absorption layer and selecting an appropriate doping concentration. Considering the influence of process difficulty, it is re-commended to adopt a deep ion implanted planar junction structure or an epitaxial structure with controllable thickness and doping concentration prepared by molecular beam epitaxy.

In order to solve diverse quality and privacy leakage of perceived data in fog-cloud integrated internet of things (IoT), a streaming encryption-based privacy-preserving truth discovery mechanism for IoT was proposed. Firstly, by utilizing shuffling and streaming encryption algorithms, the ground truths and the weights were anonymously updated on the cloud server and fog server, respectively, so that the collusion attacks between malicious attackers and cloud or fog servers could be resisted to defend against privacy leakage of IoT devices. Secondly, by adopting the Softmax function, the device weights were calculated on fog server, which reduces the error rate for calculating the ground truths. Finally, the theoretical analysis proved that the mechanism could protect privacy of the devices. And, the experimental results demonstrate that the proposed mechanism is an effective privacy-preserving trust discovery mechanism for large-scale IoT devices, which can outperform existing ones in computing efficiency. [ABSTRACT FROM AUTHOR]