ABSTRACT The proliferation of smart contracts has significantly fueled the growth and advancement of decentralized industries. Nonetheless, flaws in smart contract design and the infancy of their applications have resulted in a persistent rise in contractual vulnerabilities. Tools aimed at detecting vulnerabilities within smart contracts are hampered by low accuracy, stemming from a scarcity of standardized training data. Additionally, smart contract datasets are plagued by a myriad of challenges, including outdated information, inaccuracy, and an absence of universal standards, which have hindered their broad acceptance. To address these challenges, this paper introduces a blockchain‐based solution for a smart contract data sharing community. It devises a novel consensus‐based incentive mechanism to curate a high‐quality smart contract dataset and integrates a suite of automated detection tools to create an efficient pre‐detection methodology for vulnerabilities. Subsequently, the paper implements a smart contract data sharing platform. The experimental results demonstrate that mainstream detection tools fail to identify all vulnerabilities. Notably, detection rates for reentrancy, illegal delegate call, integer overflow, and lock of balance vulnerabilities exceeded 50%, with reentrancy detection reaching 88.7%. Furthermore, our framework identified 681 previously unmarked vulnerabilities. These findings robustly validate the feasibility and effectiveness of the proposed incentive scheme in enhancing vulnerability detection accuracy and data quality.

Cyber-Physical Systems (CPS) are the next generation of intelligent systems that integrate information control devices with physical resources. With increasingly close connections between CPS components and frequent interactions, potential defects grow exponentially, rendering the operating environment of CPS unreliable. Therefore, research on methods and theories to ensure the correctness, safety and reliability of CPS is not only an important research topic but also an inevitable challenge. In this paper, we propose a CPS modeling and verification method based on Architecture Analysis & Design Language (AADL) and process algebra to address this challenge. Due to the continuous, time-constrained, stochastic, uncertain and concurrent characteristics of CPS, this paper considers both flexibility and rigor in the modeling process. We first extend the ability of AADL to describe the multiple characteristics of CPS and propose Hybrid Probability-AADL (HP-AADL). Second, this paper introduces conditional execution, conditional interruption and probability operators into Temporal Calculus of Communication Systems (TCCS) and designs a new formal modeling language Hybrid Probability-Temporal Calculus of Communication Systems (HP-TCCS). However, HP-AADL is a semi-formal modeling language that cannot be directly used for formal verification, it cannot strictly guarantee the quality of the established CPS models, including its functional correctness and safety. Therefore, this paper proposes transformation rules from HP-AADL to HP-TCCS, which enables model checking of CPS models described in HP-AADL within HP-TCCS. Additionally, this paper designs a new formal specification language HPAT-Spatial Temporal Logic (HPAT-STL) based on Probabilistic Computation Tree Logic (PCTL) and Spatial Logic, which characterizes the temporal, probabilistic and spatial properties of CPS model. To achieve formal verification of HP-TCCS model and HPAT-STL formulas, this paper proposes a model checking algorithm HPAT-Model Checking Algorithm (HPAT-MCA). Finally, we discuss a typical CPS example to demonstrate the effectiveness of our proposed method in ensuring correct, safe and reliable CPS.

Temporal Logics are a rich variety of logical systems designed for specifying properties over time, and about events and changes in the world over time. Traditional temporal logic, however, is limited to binary outcomes true or false and lacks the capacity to specify performance properties of a system such as the maximum, minimum, or average costs between states. Current languages do not accommodate the quantification of such performance properties, especially in scenarios involving infinite execution paths where performance property like cumulative sums may fail to converge. To this end, this paper introduces a novel formal language aimed at assessing system performance, which encapsulates not only temporal dynamics but also various performance-related properties. In this study, this paper utilizes reinforcement learning techniques to compute the values of performance property formulas. Finally, in the experimental part, a formal language representation of system performance properties was implemented, and the values of the performance property formulas were computed using reinforcement learning. The effectiveness and feasibility of the proposed method were validated.

With the rapid development of Internet of Things and communication technologies, the connected vehicle technology with vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication is seen as the most promising solution for reducing traffic accidents and alleviating traffic congestion. Roadside Units (RSUs) play a crucial role in enabling V2I communication, as they can gather and broadcast traffic event information in the road network. Implementing a well-thought-out RSU strategy can significantly improve the stability and efficiency of traffic event information transmission in the road network. However, there is a lack of effective strategies for RSU deployment in stochastic scenarios. The presence of unpredictable factors like equipment failures and network attacks may disrupt the normal functioning of the RSUs. To guide the deployment of roadside facilities, we analyze the transmission time of traffic events in the road network and construct a multi-objective RSU deployment model considering the possibility of RSU failures. This model aims to maximize the number of connected vehicles served and minimize the expected transmission time of events. Through fuzzy programming theory and different decision preferences, we transform the two objectives into a single objective function. A random-key genetic algorithm (RKGA) is designed to solve the transformed model. Moreover, several simulation examples are presented to verify the feasibility and effectiveness of the proposed model and algorithm. The results indicate that decentralized deployment is preferred for low RSU failure probabilities, while centralized deployment is preferred for high failure probabilities.

The roadside unit (RSU), which enables vehicle-to-infrastructure communication, is essential for improving the communication performance of vehicular ad hoc networks. However, optimizing the deployment of RSUs while considering their deployment at both fixed locations and on mobile vehicles remains a challenging issue. To bridge this gap, we develop two spatio-temporal networks derived from vehicle trajectories. Subsequently, the joint deployment challenge of static and mobile RSUs is articulated as a mixed-integer programming model. After linearization, the model can be directly solved by CPLEX. Additionally, the integrated optimization problem can also be formulated as a route-based model. Due to the exponential growth of route numbers, a branch-and-price (BAP) algorithm is designed to solve the route-based model. Within the framework of the BAP, we develop a heuristic technique for generating effective initial solutions. Based on the characteristics of the spatio-temporal network, a directed acyclic graph shortest path algorithm is utilized to accelerate the solution of column generation pricing problem at each node. Simulation examples are presented to demonstrate the proposed algorithm. The results indicate that the BAP can generate verifiable high-quality solutions and has a significant speed advantage over CPLEX for large-scale problems. Furthermore, a series of sensitivity analyses are conducted to assess the system’s responses to various influencing factors.

Path generation means generating a path or a set of paths so that the generated path meets specified properties or constraints. To our knowledge, generating a path with the performance evaluation value of the path within a given value interval has received scant attention. This paper subtly formulates the path generation problem as an optimization problem by designing a reasonable fitness function, adapts the Markov decision process with reward model into a weighted digraph by eliminating multiple edges and non-goal dead nodes, constructs the path by using a priority-based indirect coding scheme, and finally modifies the bat algorithm with heuristic to solve the optimization problem. Simulation experiments were carried out for different objective functions, population size, number of nodes, and interval ranges. Experimental results demonstrate the effectiveness and superiority of the proposed algorithm.

This paper proposes a novel contact force sensing and control method for the inserting operation during precise assembly process, which is based on a micromanipulator integrated with force sensors. At first, theoretical analysis is carried out to calculate the admissible contact force between the gripped holes and the pegs. The contact force thresholds which are smaller than the admissible contact forces are adopted in the control algorithm to avoid the rotating of the gripped holes during assembly process. The force sensors are calibrated using an ATI force sensor and the conversing coefficients are calculated. The admissible contact forces are tested when different contact distance and preload force are adopted. The performance of the proposed contact force sensing and control method is verified by carrying out the task of applying contact force on the surface of the gripped holes with different contacting speeds. The results indicate that the contact force can be adjusted to be smaller than the threshold 1 and the peg-in-hole assembly can be completed successfully.Note to Practitioners—This paper proposes a novel contact force sensing method during the inserting operation. Compared with the traditional contact force sensing method, this paper adopts the force sensor integrated into the micromanipulator instead of commercial force sensor to detect the contact force between two parts. To ensure the assembling precision, the theoretical analysis is conducted to calculated the admissible contact force to avoid the sliding and rotating of the gripped micro part during assembling. This work efficiently simplifies the contact force sensing and control process, where complex calibration process needn’t to be carried out to eliminate the influence of the mass of the micromanipulator on the testing results. In addition, the assembling costs are reduced by replacing commercial force sensors with strain gauges.

Probabilistic behavior is omnipresent in computer-controlled systems, in particular, so-called safety-critical hybrid systems, due to various reasons, like uncertain environments or fundamental properties of nature. In this paper, we extend the existing hybrid process algebra ACP[Formula: see text] with probability without sacrificing the nondeterministic choice operator. The existing approximate probabilistic bisimulation relation is fragile and not robust in the sense of being dependent on the deviation range of the transition probability. To overcome this defect, a novel approximate probabilistic bisimulation is proposed which is inspired by the idea of Probably Approximately Correct (PAC) by relaxing the constraints of transition probability deviation range. Traditional temporal logics, even probabilistic temporal logics, are expressive enough, but they are limited to producing only true or false responses, as they are still logics and not suitable for performance evaluation. To settle this problem, we present a new performance evaluation language that expands quantitative analysis from the value range of [Formula: see text] to real number to reason over probabilistic systems. After that, the corresponding algorithms for performance evaluation are given. Finally, an industrial example is given to demonstrate the effectiveness of our method.