The Internet of Things (IoT) is a technology that enables various devices and sensors to connect to the internet and communicate with one another, which provides new value to users. Various fields are utilizing IoT, such as smart agriculture and manufacturing, to improve work efficiency and product quality. Although various universities and vocational schools are working on IoT education, there are few examples of IoT education for elementary school children and high school students, despite the need for skills required in the future society.

Thus, the current study developed an educational IoT device that enables elementary and high school students to learn about IoT. The features of this device include its ability to cover a wide range of ages with only one device and ease of use in experiencing IoT through experimental formats using various sensors and actuators without electrical wiring. This paper presents the configuration and experimental contents of the developed IoT device.

In order to realize a sustainable society that integrates cyber and physical space (Society 5.0), it is important to construct secure Cyber-Physical System (CPS). Devices in industrial systems must be energy efficient for environmental protection and low latency for production efficiency. On the other hand, CPS has issues such as huge energy consumption of the entire system and delays caused by communication processing due to frequent network connections of many devices. Lightweight block ciphers are one of the key technologies to solve these problems and improve the confidentiality of highly secret communication data. PRINCE with low latency and Midori128 with low energy operation are both computationally secure. Furthermore, they have been reported to have tamper-resistant circuits with improved security against the threat of power analysis attacks, which use the power consumption of cryptographic operations to guess secret keys. However, deep learning power analysis attacks have been proposed in recent years, focusing on deep learning, which has dramatically improved performance. Therefore, it is very important to evaluate the tamper resistance of PRINCE and Midori128. Against this background, this study examines the threat of deep learning power analysis attack methods against several implementations of PRINCE and Midori128. The proposed method achieves efficient analysis by generating deep learning training data oriented to implementation types and target ciphers. Evaluation experiments using actual equipment showed that the proposed method is able to analyze all partial keys of tamper-resistant circuits, which were difficult to analyze with conventional attack methods.

Intelligent-PID (i-PID) control proposed by Fliess is a simple control algorithm. The controller is designed based on ultra-local model, and consisted of PID type controller and derivatives of reference signal and controlled variables. Authors have considered discrete i-PID controller and its properties, and one of the result was that PD controller was sufficient in discrete time domain. In discrete i-PID controller, PD type controller is still required to ensure convergence of controlled error to zero, and PD type parameters affects convergence property, fast-response property and stability. In this paper, predictive functional control (PFC) based on an ultra-local model is proposed. By introducing of PFC, controlled variable converge to reference value without PD type controller. User-specified parameters of the proposed controller is smaller than the conventional i-PID controller. Characteristics of the proposed controller are compared with discrete i-PID controller by numerical examples.

In this paper, we propose a self-tuning algorithm by which we can achieve autonomous engineering including model identification and control parameter tuning on the edge-type MPC (Model Predictive Control). In the model identification algorithm, offset estimation is introduced in order to replace step response tests. We compare the control performance of the self-tuning edge-type MPC with those of PID control and offline-tuned edge-type MPC for a MIMO stir process model. As a result, the proposed self-tuning edge-type MPC achieves faster tracking performance without any pre-tuning.

For operability improvement, this paper proposes a frequency modification method using fast Fourier transform (FFT) in a bilateral control. A bilateral control is one of the remote control methods with tactile sensation. The bilateral control system consists of the leader and follower systems. By using FFT, the position response and estimated force in the leader and follower systems are converted from the time domain to the frequency domain. In the frequency domain, frequency modification is conducted. After the frequency modification, the frequency domain data is reconverted to the time domain by using inverse FFT. Therefore, the proposed method enables frequency modification that is easy for the operator to manipuate in the bilateral control. For the confirmation of the validity of the proposed method, the experiments that imitate drilling tasks were conducted.

Risk analysis based on attack scenarios is useful for security measures in ICS (Industrial Control System). However, the generation of attack scenarios requires a lot of time and effort from ICS and security experts. To make this generation efficient, a systematic method for generating attack scenarios is needed. Therefore, the purpose of this study is to establish a method that simplifies the construction of attack models and enables the comprehensive generation of scenarios that are concrete and useful for risk analysis. In this study, we proposed a model that assigns security countermeasure attributes to devices and networks in ICS modelling, and attack techniques analysis and attack path generation algorithms using these models. The proposed method can achieve efficient risk analysis in an ICS environment without making other security countermeasure processes inefficient.