Multiple Objective Functions for Falsification of Cyber-Physical Systems

Cyber-physical systems are typically safety-critical, thus it is crucial to guarantee that they conform to given specifications, that are the properties that the system must fulfill. Optimization-based falsification is a model-based testing method to find counterexamples of the specifications. The main idea is to measure how far away a specification is from being broken, and to use an optimization procedure to guide the testing towards falsification. The efficiency of the falsification is affected by the objective function used to evaluate the test results; different objective functions are differently efficient for different types of problems. However, the efficiency of various objective functions is not easily determined beforehand. This paper evaluates the efficiency of using multiple objective functions in the falsification process. The hypothesis is that this will, in general, be more efficient, meaning that it falsifies a system in fewer iterations, than just applying a single objective function to a specific problem. Two objective functions are evaluated, Max, Additive, on a set of benchmark problems. The evaluation shows that using multiple objective functions can reduce the number of iterations necessary to falsify a property

Rampo: A CEGAR-based Integration of Binary Code Analysis and System Falsification for Cyber-Kinetic Vulnerability Detection

This paper presents a novel tool, named Rampo, that can perform binary code analysis to identify cyber kinetic vulnerabilities in CPS. The tool takes as input a Signal Temporal Logic (STL) formula that describes the kinetic effect, i.e., the behavior of the physical system, that one wants to avoid. The tool then searches the possible cyber trajectories in the binary code that may lead to such physical behavior. This search integrates binary code analysis tools and hybrid systems falsification tools using a Counter-Example Guided Abstraction Refinement (CEGAR) approach. Rampo starts by analyzing the binary code to extract symbolic constraints that represent the different paths in the code. These symbolic constraints are then passed to a Satisfiability Modulo Theories (SMT) solver to extract the range of control signals that can be produced by each path in the code. The next step is to search over possible physical trajectories using a hybrid systems falsification tool that adheres to the behavior of the cyber paths and yet leads to violations of the STL formula. Since the number of cyber paths that need to be explored increases exponentially with the length of physical trajectories, we iteratively perform refinement of the cyber path constraints based on the previous falsification result and traverse the abstract path tree obtained from the control program to explore the search space of the system. To illustrate the practical utility of binary code analysis in identifying cyber kinetic vulnerabilities, we present case studies from diverse CPS domains, showcasing how they can be discovered in their control programs. Our tool could compute the same number of vulnerabilities while leading to a speedup that ranges from 3x to 98x

Falsification of Signal-Based Specifications for Cyber-Physical Systems

In the development of software for modern Cyber-Physical Systems, testing is an integral part that is rightfully given a lot of attention. Testing is done on many different abstraction levels, and especially for large-scale industrial systems, it can be difficult to know when the testing should conclude and the software can be considered correct enough for making its way into production. This thesis proposes new methods for analyzing and generating test cases as a means of being more certain that proper testing has been performed for the system under test. For analysis, the proposed approach includes automatically finding how much a given test suite has executed the physical properties of the simulated system. For test case generation, an up-and-coming approach to find errors in Cyber-Physical Systems is simulation-based falsification. While falsification is suitable also for some large-scale industrial systems, sometimes there is a gap between what has been researched and what problems need to be solved to make the approach tractable in the industry. This thesis attempts to close this gap by applying falsification techniques to real-world models from Volvo Car Corporation, and adapting the falsification procedure where it has shortcomings for certain classes of systems. Specifically, the thesis includes a method for automatically transforming a signal-based specification into a formal specification in temporal logic, as well as a modification to the underlying optimization problem that makes falsification more viable in an industrial setting. The proposed methods have been evaluated for both academic benchmark examples and real-world industrial models. One of the main conclusions is that the proposed additions and changes to analysis and generation of tests can be useful, given that one has enough information about the system under test. It is difficult to provide a general solution that will always work best -- instead, the challenge lies in identifying which properties of the given system should be taken into account when trying to find potential errors in the system

Enhancing Temporal Logic Falsification of Cyber-Physical Systems using multiple objective functions and a new optimization method

Cyber-physical systems (CPSs) are engineering systems that bridge the cyber-world of communications and computing with the physical world. These systems are usually safety-critical and exhibit both discrete and continuous dynamics that may have complex behavior. Typically, these systems have to satisfy given specifications, i.e., properties that define the valid behavior. One commonly used approach to evaluate the correctness of CPSs is testing. The main aim of testing is to detect if there are situations that may falsify the specifications.\ua0For many industrial applications, it is only possible to simulate the system under test because mathematical models do not exist, thus formal verification is not a viable option. Falsification is a strategy that can be used for testing CPSs as long as the system can be simulated and formal specifications exist. Falsification attempts to find counterexamples, in the form of input signals and parameters, that violate the specifications of the system. Random search or optimization can be used for the falsification process. In the case of an optimization-based approach, a quantitative semantics is needed to associate a simulation with a measure of the distance to a specification being falsified. This measure is used to guide the search in a direction that is more likely to falsify a specification, if possible. \ua0The measure can be defined in different ways. In this thesis, we evaluate different quantitative semantics that can be used to define this measure. The efficiency of the falsification can be affected by both the quantitative semantics used and the choice of the optimization method. The presented work attempts to improve the efficiency of the falsification process by suggesting to use multiple quantitative semantics, as well as a new optimization method. The use of different quantitative semantics and the new optimization method have been evaluated on standard benchmark problems. We show that the proposed methods improve the efficiency of the falsification process

From Formal Requirement Analysis to Testing and Monitoring of Cyber-Physical Systems

abstract: Cyber-Physical Systems (CPS) are being used in many safety-critical applications. Due to the important role in virtually every aspect of human life, it is crucial to make sure that a CPS works properly before its deployment. However, formal verification of CPS is a computationally hard problem. Therefore, lightweight verification methods such as testing and monitoring of the CPS are considered in the industry. The formal representation of the CPS requirements is a challenging task. In addition, checking the system outputs with respect to requirements is a computationally complex problem. In this dissertation, these problems for the verification of CPS are addressed. The first method provides a formal requirement analysis framework which can find logical issues in the requirements and help engineers to correct the requirements. Also, a method is provided to detect tests which vacuously satisfy the requirement because of the requirement structure. This method is used to improve the test generation framework for CPS. Finally, two runtime verification algorithms are developed for off-line/on-line monitoring with respect to real-time requirements. These monitoring algorithms are computationally efficient, and they can be used in practical applications for monitoring CPS with low runtime overhead.Dissertation/ThesisDoctoral Dissertation Computer Science 201

On Optimization-Based Falsification of Cyber-Physical Systems

In what is commonly referred to as cyber-physical systems (CPSs), computational and physical resources are closely interconnected. An example is the closed-loop behavior of perception, planning, and control algorithms, executing on a computer and interacting with a physical environment. Many CPSs are safety-critical, and it is thus important to guarantee that they behave according to given specifications that define the correct behavior. CPS models typically include differential equations, state machines, and code written in general-purpose programming languages. This heterogeneity makes it generally not feasible to use analytical methods to evaluate the system’s correctness. Instead, model-based testing of a simulation of the system is more viable. Optimization-based falsification is an approach to, using a simulation model, automatically check for the existence of input signals that make the CPS violate given specifications. Quantitative semantics estimate how far the specification is from being violated for a given scenario. The decision variables in the optimization problems are parameters that determine the type and shape of generated input signals. This thesis contributes to the increased efficiency of optimization-based falsification in four ways. (i) A method for using multiple quantitative semantics during optimization-based falsification. (ii) A direct search approach, called line-search falsification that prioritizes extreme values, which are known to often falsify specifications, and has a good balance between exploration and exploitation of the parameter space. (iii) An adaptation of Bayesian optimization that allows for injecting prior knowledge and uses a special acquisition function for finding falsifying points rather than the global minima. (iv) An investigation of different input signal parameterizations and their coverability of the space and time and frequency domains. The proposed methods have been implemented and evaluated on standard falsification benchmark problems. Based on these empirical studies, we show the efficiency of the proposed methods. Taken together, the proposed methods are important contributions to the falsification of CPSs and in enabling a more efficient falsification process

On Falsification of Large-Scale Cyber-Physical Systems

In the development of modern Cyber-Physical Systems, Model-Based Testingof the closed-loop system is an approach for finding potential faults andincreasing quality of developed products. Testing is done on many differentabstraction levels, and for large-scale industrial systems, there are severalchallenges. Executing tests on the systems can be time-consuming and largenumbers of complex specifications need to be thoroughly tested, while manyof the popular academic benchmarks do not necessarily reflect on this complexity.This thesis proposes new methods for analyzing and generating test casesas a means for being more certain that proper testing has been performed onthe system under test. For analysis, the proposed approach can automaticallyfind out how much of the physical parts of the system that the test suite hasexecuted.For test case generation, an approach to find errors is optimization-basedfalsification. This thesis attempts to close the gap between academia and industryby applying falsification techniques to real-world models from VolvoCar Corporation and adapting the falsification procedure where it has shortcomingsfor certain classes of systems. Specifically, the main contributionsof this thesis are (i) a method for automatically transforming a signal-basedspecification into a formal specification allowing an optimization-based falsificationapproach, (ii) a new collection of specifications inspired by large-scalespecifications from industry, (iii) an algorithm to perform optimization-basedfalsification for such a large set of specifications, and (iv) a new type of coveragecriterion for Cyber-Physical Systems that can help to assess when testingcan be concluded.The proposed methods have been evaluated for both academic benchmarkexamples and real-world industrial models. One of the main conclusions isthat the proposed additions and changes to the analysis and generation oftests can be useful, given that one has enough information about the systemunder test. The methods presented in this thesis have been applied to realworldmodels in a way that allows for higher-quality products by finding morefaults in early phases of development