scholarly journals FS-PEKS: Lattice-based Forward Secure Public-key Encryption with Keyword Search for Cloud-assisted Industrial Internet of Things

Author(s):  
Xiaojun Zhang ◽  
Chunxiang Xu ◽  
Huaxiong Wang ◽  
Yuan Zhang ◽  
Shixiong Wang
2021 ◽  
Vol 17 (3) ◽  
pp. 25-45
Author(s):  
Muthukumaran V. ◽  
Manimozhi I. ◽  
Praveen Sundar P. V. ◽  
Karthikeyan T. ◽  
Magesh Gopu

Organizations have moved from the conventional industries to smart industries by embracing the approach of industrial internet of things (IIoT), which has provided an avenue for the integration of smart devices and communication technologies. In this context, this work presents a public key encryption with equality test based on DLP with decomposition problems over near-ring. The proposed method is highly secure, and it solves the problem of quantum algorithm attacks in industrial internet of thing systems. Further, the proposed system is highly secure, and it prevents the chosen-ciphertext attack in type-I adversary and it is indistinguishable against the random oracle model for the type-II adversary. The proposed scheme is highly secure, and the security analysis measures are comparatively stronger than existing techniques.


Author(s):  
Ganesh Gopal Deverajan ◽  
V. Muthukumaran ◽  
Ching‐Hsien Hsu ◽  
Marimuthu Karuppiah ◽  
Yeh‐Ching Chung ◽  
...  

2019 ◽  
Vol 128 ◽  
pp. 11-20 ◽  
Author(s):  
Lingling Xu ◽  
Jin Li ◽  
Xiaofeng Chen ◽  
Wanhua Li ◽  
Shaohua Tang ◽  
...  

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Mimi Ma ◽  
Min Luo ◽  
Shuqin Fan ◽  
Dengguo Feng

The Industrial Internet of Things (IIoT), as a special form of Internet of Things (IoT), has great potential in realizing intelligent transformation and industrial resource utilization. However, there are security and privacy concerns about industrial data, which is shared on an open channel via sensor devices. To address these issues, many searchable encryption schemes have been presented to provide both data privacy-protection and data searchability. However, due to the use of expensive pairing operations, most previous schemes were inefficient. Recently, a certificateless searchable public-key encryption (CLSPE) scheme was designed by Lu et al. to remove the pairing operation. Unfortunately, we find that Lu et al.’s scheme is vulnerable to user impersonation attacks. To enhance the security, a new pairing-free dual-server CLSPE (DS-CLSPE) scheme for cloud-based IIoT deployment is designed in this paper. In addition, we provide security and efficiency analysis for DS-CLSPE. The analysis results show that DS-CLSPE can resist chosen keyword attacks (CKA) and has better efficiency than other related schemes.


IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 20849-20861 ◽  
Author(s):  
Yulei Zhang ◽  
Xiangzhen Liu ◽  
Xiaoli Lang ◽  
Yongjie Zhang ◽  
Caifen Wang

2020 ◽  
Author(s):  
Karthik Muthineni

The new industrial revolution Industry 4.0, connecting manufacturing process with digital technologies that can communicate, analyze, and use information for intelligent decision making includes Industrial Internet of Things (IIoT) to help manufactures and consumers for efficient controlling and monitoring. This work presents the design and implementation of an IIoT ecosystem for smart factories. The design is based on Siemens Simatic IoT2040, an intelligent industrial gateway that is connected to modbus sensors publishing data onto Network Platform for Internet of Everything (NETPIE). The design demonstrates the capabilities of Simatic IoT2040 by taking Python, Node-Red, and Mosca into account that works simultaneously on the device.


Author(s):  
С.Л. Добрынин ◽  
В.Л. Бурковский

Произведен обзор технологий в рамках концепции четвертой промышленной революции, рассмотрены примеры реализации новых моделей управления технологическими процессами на базе промышленного интернета вещей. Описано техническое устройство основных подсистем системы мониторинга и контроля, служащей для повышения осведомленности о фактическом состоянии производственных ресурсов в особенности станков и аддитивного оборудования в режиме реального времени. Архитектура предлагаемой системы состоит из устройства сбора данных (УСД), реализующего быстрый и эффективный сбор данных от станков и шлюза, передающего ликвидную часть информации в облачное хранилище для дальнейшей обработки и анализа. Передача данных выполняется на двух уровнях: локально в цехе, с использованием беспроводной сенсорной сети (WSN) на базе стека протоколов ZigBee от устройства сбора данных к шлюзам и от шлюзов в облако с использованием интернет-протоколов. Разработан алгоритм инициализации протоколов связи между устройством сбора данных и шлюзом, а также алгоритм выявления неисправностей в сети. Расчет фактического времени обработки станочных подсистем позволяет более эффективно планировать профилактическое обслуживание вместо того, чтобы выполнять задачи обслуживания в фиксированные интервалы без учета времени использования оборудования We carried out a review of technologies within the framework of the concept of the fourth industrial revolution; we considered examples of the implementation of new models of process control based on the industrial Internet of things. We described the technical structure of the main subsystems of the monitoring and control system to increase awareness of the actual state of production resources in particular machine tools and additive equipment in real time. The architecture of the proposed system consists of a data acquisition device (DAD) that implements fast and efficient data collection from machines and a gateway that transfers the liquid part of information to the cloud storage for further processing and analysis. We carried out the data transmission at two levels, locally in the workshop, using a wireless sensor network (WSN) based on ZigBee protocol stack from the data acquisition device to the gateways and from the gateways to the cloud using Internet protocols. An algorithm was developed for initializing communication protocols between a data acquisition device and a gateway, as well as an algorithm for detecting network malfunctions. Calculating the actual machining time of machine subsystems allows us to more efficiently scheduling preventive maintenance rather than performing maintenance tasks at fixed intervals without considering equipment usage


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