# Trustworthiness in Mobile Cyber-Physical Systems
## 2 Review of Issue Contents
Owing to the readiness with which a trusted platform such as SGX can be integrated with many current CPSs, this research also has implications for security enhancements in CPS environments. Event-based systems (EBSs) are prevalent in MCPS applications owing to their communication model, which uses implicit invocation and concurrency between components. However, the non-determinism of EBSs during event processing can introduce inherent security vulnerabilities into the system. Many types of attack can incapacitate and/or damage a target EBS by exploiting this event-based communication model. To minimize the security risks to EBSs, the security flaws of such systems, the relationships between these flaws, and feasible techniques for dealing with each flaw must be determined. However, existing security flaw taxonomies do not appropriately reflect the inherent security issues of EBSs. Therefore, [PERSON] et al. [7] introduced a new taxonomy that defines and classifies the inherent security flaws of EBSs, which can serve as a basis for resolving its specific security problems. Moreover, the authors correlated their taxonomy with security attacks designed to target specific flaws and identified existing solutions for the prevention of such attacks. In [8], [PERSON] et al. describe an energy minimization technique for mixed-criticality real-time scheduling on a single-core system. The main contribution of the proposed technique is that it allows the processor frequency to be controlled dynamically depending on the system criticality mode. Through a series of simulations, they demonstrated and analyzed the effects caused by both low-and high-criticality modes in power-aware mixed-criticality systems. As safety and power awareness are both issues for MCPSs, this study offers valuable insights for power-aware safety-critical CPSs. Safety and efficiency provide the focus in [9], in which [PERSON] et al. propose a system that dynamically controls the all-red signal length based on the driving characteristics of vehicles identified as red-light runners (RLRs) to improve the overall safety and efficiency of intersections in road networks. The proposed system uses a multi-channel deep convolutional neural network (MC-DCNN) to enable the online detection and classification of RLRs, which can be defined using clustering results acquired via dynamic time wrapping (DTW) and hierarchical clustering analysis (HCA). For dynamic all-red signal control, the proposed system uses a multi-level regression model to estimate the necessary all-red signal extension time more accurately, thereby improving the overall safety for intersection traffic as well as efficiency of the traffic flow. By contrast, the study conducted by [PERSON] et al. [10] concerns real-time data transmission to mobile equipment used by groups of workers, termed a mobile sink group (MSG), for which rapid and reliable data are vital to ensure the efficient operation of groups working on collaborative projects, which often involve multiple pieces of equipment where miscommunication could result in an industrial accident. The authors proposed a real-time data delivery mechanism based on a virtual grid structure to support MSGs. The main idea is to determine the farthest distance and calculate the minimum real-time data transmission speed required. First, the proposed scheme models the MSG as a single center point and radius, and defines the end-to-end distance based on the member sink located furthest from the source node. Thus, the source node can calculate the transmission speed, which is maintained during the data transmission. The data transmission process is divided into two main phases: the main forwarding phase, which passes through the center of the mobile sinks from the source node, and the branch forwarding phase at the branch point, which receives data via the main forwarding phase.