Zhe Hou

Griffith University · School of Information and Communication Technology (ICT)

This paper introduces a new high-performance machine learning tool named Silas, which is built to provide a more transparent, dependable and efficient data analytics service. We discuss the machine learning aspects of Silas and demonstrate the advantage of Silas in its predictive and computational performance. We show that several customised algori...

The future of multi-blockchain architecture depends on the emergence of new protocols that enable consensus between trustless cross-blockchain participants. However, interoperability between blockchains remains a research challenge. The existing interoperability approaches provide integration through solutions using a middleware system, making it d...

Nowadays there are a wealth of devices and cameras at sports venues and facilities that collect different forms of data. Mining useful insights from such data are crucial for improving the performance of professional athletes. In this paper, we introduce a new interactive tennis analytics framework that can realistically simulate tennis matches usi...

Neural networks have been widely applied in security applications such as spam and phishing detection, intrusion prevention, and malware detection. This black-box method, however, often has uncertainty and poor explainability in applications. Furthermore, neural networks themselves are often vulnerable to adversarial attacks. For those reasons, the...

Boolean satisfiability (SAT) solving is a fundamental problem in computer science. Finding efficient algorithms for SAT solving has broad implications in many areas of computer science and beyond. Quantum SAT solvers have been proposed in the literature based on Grover's algorithm. Although existing quantum SAT solvers can consider all possible inp...

Large Language Models (LLMs) have emerged as a transformative AI paradigm, profoundly influencing daily life through their exceptional language understanding and contextual generation capabilities. Despite their remarkable performance, LLMs face a critical challenge: the propensity to produce unreliable outputs due to the inherent limitations of th...

This is a special issue of Formal Aspects of Computing for the 28th IEEE Pacific Rim International Symposium on Dependable Computing (PRDC 2023).

Foundational verification considers the functional correctness of programming languages with formalized semantics and uses proof assistants (e.g., Coq, Isabelle) to certify proofs. The need for verifying complex programs compels it to involve expressive Separation Logics (SLs) that exceed the scopes of well-studied automated proof theories, e.g., s...

In the field of automated programming, large language models (LLMs) have demonstrated foundational generative capabilities when given detailed task descriptions. However, their current functionalities are primarily limited to function-level development, restricting their effectiveness in complex project environments and specific application scenari...

With the widespread adoption of medical informatics, a wealth of valuable personal health records (PHR) has been generated. Concurrently, blockchain technology has enhanced the security of medical institutions. However, these institutions often function as isolated data silos, limiting the potential value of PHRs. As the demand for data sharing bet...

Blockchain technology has evolved beyond its initial role in supporting cryptocurrencies like Bitcoin, with Ethereum introducing smart contracts for decentralised applications in various domains. However, ensuring the safety and security of smart contracts remains a critical challenge, particularly concerning concurrency issues. This is of paramoun...

The chapter introduces probabilistic CSP# (PCSP#) as a formal language for modeling probabilistic systems, emphasizing its foundational role in concurrent and parallel computation. PCSP# is an extension of communicating sequential programs (CSP#) that enables the modeling of probabilistic behaviors and uncertainties in system designs. We provide th...

Program refinement involves correctness-preserving transformations from formal high-level specification statements into executable programs. Traditional verification tool support for program refinement is highly interactive and lacks automation. On the other hand, the emergence of large language models (LLMs) enables automatic code generations from...

In the quantum computing era, the imperative role of post-quantum cryptography in securing digital communications has led to the development of computer-aided cryptography verification tools. These tools simplify the verification of post-quantum cryptography primitives and protocols, alleviating the challenges associated with manual proofs. This pa...

Boolean satisfiability (SAT) solving is a fundamental problem in computer science. Finding efficient algorithms for SAT solving has broad implications in many areas of computer science and beyond. Quantum SAT solvers have been proposed in the literature based on Grover’s algorithm. Although existing quantum SAT solvers can consider all possible inp...

This article examines the integration of blockchain, eXplainable Artificial Intelligence (XAI), especially in the context of federated learning, for credit scoring in financial sectors to improve the credit assessment process. Research shows that integration of these cutting-edge technologies is in its infancy, specifically in the areas of embracin...

Non-fungible tokens (NFTs) are unique tokens with various domains, e.g. real estate, metaverse, gaming and public auctions. However, when minted on public blockchains, the underlying blockchain transaction data can be publicly accessible. This instigated transaction data analysis for various purposes, including cryptocurrency price prediction and N...

The adoption of blockchain technology within various critical infrastructures is on the rise. Concurrently, there has been a corresponding increase in its misuse, primarily through the exploitation of its pseudo-anonymous characteristic. Encouraging blockchain adoption and improving security in the decentralised environment require techniques to de...

Blockchain technology has been integrated into a wide range of applications in various sectors, such as finance, supply chain, health, and governance. However, the participation of a few actors with malicious intentions challenges law enforcement authorities, regulators and other users. These challenges revolve around dealing with an array of illeg...

Safeguarding individuals and valuable resources from cyber threats stands as a paramount concern in the digital landscape, encompassing realms like cyber-physical systems and IoT systems. The safeguarding of cyber-physical systems (CPS) is particularly challenging given their intricate infrastructure, necessitating ongoing real-time analysis and sw...

This paper introduces an abstract blockchain model that employs the Burn-to-Claim cross-blockchain protocol [1]. This multi-level simulator models a virtual environment of nodes running on the Ethereum Virtual Machine (EVM). Developed using the \(CSP\#\) language [2], it has undergone formal verification with the model checker PAT. Focusing on inte...

Encryption protects internet users' data security and privacy but makes network traffic classification a much harder problem. Network traffic classification is essential for identifying and predicting user behavior which is important for the overall task of network management. Deep learning methods used to tackle this problem have produced promisin...

Encryption protects internet users’ data security and privacy but makes network traffic classification a much harder problem. Network traffic classification is essential for identifying and predicting user behaviour which is important for the overall task of network management. Deep learning methods used to tackle this problem have produced promisi...

A satellite communication system, as a typical example of the Internet of things, is a smart critical infrastructure and has become an essential component used in various services such as finances, communications, ground and air-borne navigation, utilities, power grid distribution, emergency services, agriculture, banking, and many other critical i...

The engineering behind the technology that powers Bitcoin, known as Blockchain, has gained attention as a potential software solution for various industrial applications. The capability of revolutionising digital transactions brought significant interest in this technology and evolved greatly in the past decade. However, the development of applicat...

p>This paper proposes a novel graph-based visualisation approach to incorporating automated graph modelling and generalised graph algorithms from blockchain transactions. Our approach enables users to interact directly with the blockchain data using graph queries and provides exploration capabilities through graph patterns. Four case studies are pr...

p>This paper proposes a novel graph-based visualisation approach to incorporating automated graph modelling and generalised graph algorithms from blockchain transactions. Our approach enables users to interact directly with the blockchain data using graph queries and provides exploration capabilities through graph patterns. Four case studies are pr...

p>The study analysed the importance of blockchain transaction features to identify suspicious activities. The feature engineering process involves exploiting domain knowledge, applying intuition, and performing a time-consuming series of trial-and-error extractions. Manually overseeing this process significantly impacts the performance of model gen...

p>The study analysed the importance of blockchain transaction features to identify suspicious activities. The feature engineering process involves exploiting domain knowledge, applying intuition, and performing a time-consuming series of trial-and-error extractions. Manually overseeing this process significantly impacts the performance of model gen...

Ensemble trees are a popular machine learning model which often yields high prediction performance when analysing structured data. Although individual small decision trees are deemed explainable by nature, an ensemble of large trees is often difficult to understand. In this work, we propose an approach called optimised explanation (OptExplain) that...

Neural networks have been widely applied in security applications such as spam and phishing detection, intrusion prevention, and malware detection. This black-box method, however, often has uncertainty and poor explainability in applications. Furthermore, neural networks themselves are often vulnerable to adversarial attacks. For those reasons, the...

Formal methods for verification of programs are extended to testing of programs. Their combination is intended to lead to benefits in reliable program development, testing, and evolution. Our geometric theory of testing is intended to serve as the specification of a testing environment, included as the last stage of a toolchain that assists profess...

Automated model repair techniques enable machines to synthesise patches that ensure models meet given requirements. B-repair, which is an existing model repair approach, assists users in repairing erroneous models in the B formal method, but repairing large models is inefficient due to successive applications of repair. In this work, we improve the...

The Level of Conceptual Interoparbilty Model (LCIM) is a widely used framework that represents interrelationship among integratability, interoperability, and compos-ability of different information systems. Although this model has been successfully applied to various domains such as cybernetics and informatics, there are many challenges in directly...

Interoperability is identified as one of the major design constraints for blockchain technology. Cross-blockchain technology is fast evolving as the demand for value transfer among different blockchain systems is growing. A generic cross-blockchain design methodology for interoperability requires a set of suitable components to facilitate the integ...

This paper presents the conceptualisation of a framework that combines digital twins with runtime verification and applies the techniques in the context of security monitoring and verification for satellites. We focus on special considerations needed for space missions and satellites, and we discuss how digital twins in such applications can be dev...

The broad adoption of Machine Learning (ML) in security-critical fields demands the explainability of the approach. However, the research on understanding ML models, such as Random Forest (RF), is still in its infant stage. In this work, we leverage formal methods and logical reasoning to develop a novel model-specific method for explaining the pre...

The internet is responsible for global connectivity and ensuring its safety is a paramount task for governments and organisations. Cybersecurity concerns led to the encryption of over 87% of internet traffic. Encryption ensures security by improving privacy between sender and receiver but creates a problem of inaccurate traffic classification. Prev...

In the hardware design process, hardware components are usually described in a hardware description language. Most of the hardware description languages, such as Verilog and VHDL, do not have mathematical foundation and hence are not fit for formal reasoning about the design. To enable formal reasoning in one of the most commonly used description l...

This chapter begins with Turing’s model of computable functions, called Turing Machines, and presents them as upgraded pushdown automata. We give informal arguments that Turing machines can perform any computation that a modern computer can compute. We then discuss two different computational models: partial recursive functions and \(\lambda \)-cal...

In this chapter, we discuss three flavours of non-classical logics. Intuitionistic logic is a weakened classical logic, whereas linear logic is stronger than classical logic. Linear temporal logic can express the future of paths one can take. We focus on the propositional fragment of these logics as we have seen the difficulty that comes with quant...

We first introduce the syntax and semantics of FOL, then we look at its proof theory. We extend the natural deduction calculus for propositional logic to that for FOL. We then proceed with a similar treatment for sequent calculus for FOL. Furthermore, this time we will consider how to improve a proof calculus, which leads to several variants of LK....

This chapter is focused on two classes of automata: finite automata and pushdown automata. They accept two classes of languages, respectively: regular languages and context-free languages. Those languages are generated by two classes of grammars: right-linear grammars and context-free grammars. We will discuss simple algorithms for converting betwe...

This chapter draws examples from Wadler’s paper [1] to demonstrate the correspondence between natural deduction for intuitionistic logic and simply-typed \(\lambda \)-calculus—both concepts are built upon previously discussed topics. We also give examples in a programming language to help the reader relate logic to program code.

This chapter focuses on a simple logic: propositional logic, which has an incredibly wide range of applications such as digital circuits and programming. We discuss its syntax, semantics, and similarity with Boolean algebra, from which we introduce the first proof method of this book: truth tables. We then move on to discuss more sophisticated proo...

Simulink has been widely used in model-based design and development. While we witness a growing demand on testing and verification for safety-critical systems, it remains a challenge to verify Simulink models, due largely to a lack of standardized formal semantics for Simulink. In this paper, we propose a comprehensive framework that allows us to a...

With the development of artificial intelligence, machine learning algorithms are currently being used in more and more fields, such as autonomous driving, medical diagnosis, etc. In recent years, much research focuses on property verification of machine learning models. As one of the machine learning models, the tree ensemble model's structure is a...

The SPARC instruction set architecture (ISA) has been used in various processors in workstations, embedded systems, and in mission-critical industries such as aviation and space engineering. Hence, it is important to provide formal frameworks that facilitate the verification of hardware and software that run on or interface with these processors. I...

Ensemble trees are a popular machine learning model which often yields high prediction performance when analysing structured data. Although individual small decision trees are deemed explainable by nature, an ensemble of large trees is often difficult to understand. In this work, we propose an approach called optimised explanation (OptExplain) that...

The future of multi-blockchain architecture depends on the emergence of new protocols that achieve communication between trustless cross-chain participants. However, interoper-ability between blockchains remains an open problem. Existing approaches provide integration through solutions using a middle-ware system, which makes it harder to gain confi...

This work follow the verification as planning paradigm and propose to use model-checking techniques to solve planning and goal reasoning problems for autonomous systems with high-degree of assurance. It presents a novel modelling framework — Goal Task Network (GTN) that encompass both goal reasoning and planning under a unified formal description t...

This book constitutes the refereed proceedings of the 19th International Symposium on Automated Technology for Verification and Analysis, ATVA 2021, held in Gold Coast, Australia in October 2021. The symposium is dedicated to promoting research in theoretical and practical aspects of automated analysis, verification and synthesis by providing an in...

Although the fields of logic and computation are intrinsically related, most courses treat the two topics separately. This unique textbook aims to compress and unify important concepts of logical reasoning and computational theory, facilitating an in-depth understanding. Delivering theory with practical approaches, the book features early chapters...

N-PAT is a new model-checking tool that supports the verification of nested-models, i.e. models whose behaviour depends on the results of verification tasks. In this paper, we describe its operation and discuss mechanisms that are tailored to the efficient verification of nested-models. Further, we motivate the advantages of N-PAT over traditional...

N-PAT is a new model-checking tool that supports the verification of nested-models, i.e. models whose behaviour depends on the results of verification tasks. In this paper, we describe its operation and discuss mechanisms that are tailored to the efficient verification of nested-models. Further, we motivate the advantages of N-PAT over traditional...

This book constitutes the proceedings of the 22nd International Conference on Formal Engineering Methods, ICFEM 2020, held in Singapore, Singapore, in March 2021. The 16 full and 4 short papers presented together with 1 doctoral symposium paper in this volume were carefully reviewed and selected from 41 submissions. The papers cover theory and appl...

In order to define executable hardware description language while at the same time be fit for formal proofs of properties, a hardware description language VeriFormal, embedded in Isabelle/HOL, was created. VeriFormal, together with a translator and Isabelle/HOL proof facility, provides a platform for designing, simulating and reasoning about hardwa...