Autonomous vehicles are expected to become a new means of transportation, potentially replacing existing public transit systems. These vehicles equip range sensors such as LiDAR to perceive their surroundings. However, several distance spoofing attacks targeting LiDAR have been identified. While detection methods for individual attacks have been proposed, evaluating the impact of combined attack—combinations of multiple attack types—is also essential for improving the safety of autonomous driving systems. This study organizes the key aspects necessary for designing combined attack scenarios and proposes an improved simulation environment capable of reproducing diverse combined attack. The feasibility of the proposed simulation environment is also demonstrated.

While the introduction of cyber physical systems (CPS) into society is progressing toward the realization of Society 5.0, the threat of cyberattacks on IoT devices(IoT actuators) that have actuator functions to bring about physical changes in the real world among the IoT devices that constitute the CPS is increasing. In order to prepare for unauthorized control of IoT actuators caused by cyberattacks that are evolving daily, such as zero-day attacks that exploit unknown vulnerabilities in programs, it is an urgent issue to strengthen the CPS, which will become the social infrastructure of the future. In this paper, I explain, in particular, the security requirements for IoT actuators that exert physical action as feedback from cyberspace to the physical space, and a security framework for control that changes the real world, based on changes in cyberspace, where attackers are persistently present. And, I propose a security scheme for IoT actuators that integrates a new concept of security known as Zero Trust, as the Zero Trust IoT Security Framework (ZeTiots-FW).

These days, cyber attacks against cyber-physical systems (CPS) such as power plants are constantly growing, and therefore the countermeasures are essential. Whitelisting cyber attack detection, that detects anomalous activity as deviation from normal network communication, is especially attracting attention as one of the countermeasures because the traffic patterns are predictable in CPS. However, attackers can execute illegal operations within the normal network communication defined as the whitelisting detection rules because such operations tend to cause unstable control depending on operational states. In this work, we propose a new whitelisting cyber attack detection method that estimates the operational state of CPS and monitors the CPS network with the whitelisting detection rules according to the estimated state. The proposed method can define the more limited normal network communication to generate the whitelisting detection rules in each operational state. We experimented and evaluated the method on a plant simulator, and confirmed the effectiveness of the method: state estimation with support vector machine and attack detection with divided whitelisting detection rules.

Programmable Blobs is an attempt of actuated shape display using fluid material. We have developed an environment where we can program the shape of gel geometrically and topologically using our unique magnetic fluid called pBlob. This enables us to experience organic shape changes in real space, like a metaball in the CG world. The control hardware is composed of electromagnets arranged in the honeycomb structure and their control circuits. On/off control and PWM control vary the blob shapes and realize animations. We describe the method of blob creation, details of the mechanism and the language for transformation control, and propose some applications we are developing at present.