The development of wireless communication in the information technological era, collecting data, and transfering it from unmanned systems or devices could be monitored by any application while it is online. Direct and aliveness of countless wireless devices in a cluster of the medium could legitimate unwanted users to interrupt easily in an information flow. It would lead to data loss and security breach. Many traditional algorithms are effectively contributed to the support of cryptography-based encryption to ensure the user's data security. IoT devices with limited transmission power constraints have to communicate with the base station, and the data collected from the zones would need optimal transmission power. There is a need for a machine learning-based algorithm or optimization algorithm to maximize data transfer in a secure and safe transmission.

Blockchain-Enabled Decentralized Reliable Smart Industrial Internet of Things (BCIIoT)

Mã kiểm tra lỗi là một khối chức năng quan trọng giúp đảm bảo độ tin cậy trong các hệ thống thông tin liên lạc. Đặc biệt, mã hóa CRC (Cyclic Redundancy Check) được sử dụng rộng rãi trong nhiều lĩnh vực như truyền thông dân dụng và truyền thông công nghiệp. Mô hình mã CRC là một trong những mô hình mã kiểm tra lỗi hiệu quả giúp khắc phục dữ liệu bị ảnh hưởng của nhiễu trong quá trình truyền dữ liệu qua kênh truyền. Ưu điểm chính của mã CRC là đơn giản nhưng đạt được hiệu quả cao trong việc phát hiện lỗi và lưu trữ dữ liệu số. Trong bài báo này, chúng tôi trình bày chi tiết thiết kế và thi công bộ mã hóa và bộ giải mã mã CRC-16 dựa trên công nghệ FPGA bằng ngôn ngữ mô tả phần cứng Verilog. Các kết quả đánh giá được thực hiện trên cả phần mềm mô phỏng và kit FPGA để so sánh độ chính xác và tính hiệu quả của thiết kế so với lý thuyết.

Thiết Kế Và Thi Công Bộ Mã Hóa Và Giải Mã CRC-16 Dựa Trên Công Nghệ FPGA

Cyber-physical production network quality of service

The industrial internet of things (IIoT) encompasses smart devices, manufacturing systems, humans, and networks for automated productive outcomes. The placement of devices and networks is vulnerable to distributed denial of service (DDOS) attacks that degrade the productivity and efficiency of IIoT. In this article, we propose a checkpoint-intrigued adversary mitigation scheme (CIAMS) for improving the security features and recommendations of the detection systems. Features that use the recommendation to provide relevant information maintain their security level. A DDoS attack is dealt with at the outset, resulting in increased productivity. The IIoT's smart devices are less productive and efficient because of this DDoS attack. This CIAMS method is designed to address vulnerability and the ability to survive the features checkpoints. The proposed scheme substantiates the security breach and lag in the checkpoint systems against DDOS attacks. The checkpoints' vulnerability level and surviving features are assessed using a classified learning approach. In this assessment, the degrading features are reimbursed by improving the security functions, control, and access methods. Periodic checkpoint replacement and mutual security measures are used for mitigating the prolonging DDOS impact in the network. The proposed scheme's performance is verified using false positives, service distribution, lag, an efficiency score. Improvements have been made to the industrial environment's service delivery and efficiency. By reducing false positives by 10.35%, the proposed scheme improves service distribution ratio and efficiency score by 11.68% and 12.55% for different devices. 

CIAMS
 —
 Checkpoint‐intrigued
 adversary mitigation scheme for industrial internet of things

Abstract The error detection method is a system that determines errors in the data transmission process. One of the algorithms used to calculate this process is cyclic redundancy by sending binary data using mathematical analysis. The result of error detection found that a success rate of 65% and an error of 35%, it can be stated that the wireless communication process using module nRF24L01 has a high connection rate. Furthermore, connection loss can cause packet loss to the recipient during the communication process. This research was applied to assist disabled people with leg disabilities. These systems were equipped with nRF24L01 as transmitter and nRF24L01 as receiver. Both are installed Arduino Nano and Arduino Mega 2560. A controller smart glove tools are installed on an electric wheelchair as a support device with nRF24L01 module communication. This research was successfully implemented on the electric wheelchair.

Wengui Hu

Papers

Error detection and control of IIoT network based on CRC algorithm