Computational Soundness for Dalvik Bytecode

Automatically analyzing information flow within Android applications that rely on cryptographic operations with their computational security guarantees imposes formidable challenges that existing approaches for understanding an app's behavior struggle to meet. These approaches do not distinguish cryptographic and non-cryptographic operations, and hence do not account for cryptographic protections: f(m) is considered sensitive for a sensitive message m irrespective of potential secrecy properties offered by a cryptographic operation f. These approaches consequently provide a safe approximation of the app's behavior, but they mistakenly classify a large fraction of apps as potentially insecure and consequently yield overly pessimistic results. In this paper, we show how cryptographic operations can be faithfully included into existing approaches for automated app analysis. To this end, we first show how cryptographic operations can be expressed as symbolic abstractions within the comprehensive Dalvik bytecode language. These abstractions are accessible to automated analysis, and they can be conveniently added to existing app analysis tools using minor changes in their semantics. Second, we show that our abstractions are faithful by providing the first computational soundness result for Dalvik bytecode, i.e., the absence of attacks against our symbolically abstracted program entails the absence of any attacks against a suitable cryptographic program realization. We cast our computational soundness result in the CoSP framework, which makes the result modular and composable.Comment: Technical report for the ACM CCS 2016 conference pape

A generic framework for process execution and secure multi-party transaction authorization

Process execution engines are not only an integral part of workflow and business process management systems but are increasingly used to build process-driven applications. In other words, they are potentially used in all kinds of software across all application domains. However, contemporary process engines and workflow systems are unsuitable for use in such diverse application scenarios for several reasons. The main shortcomings can be observed in the areas of interoperability, versatility, and programmability. Therefore, this thesis makes a step away from domain specific, monolithic workflow engines towards generic and versatile process runtime frameworks, which enable integration of process technology into all kinds of software. To achieve this, the idea and corresponding architecture of a generic and embeddable process virtual machine (ePVM), which supports defining process flows along the theoretical foundation of communicating extended finite state machines, are presented. The architecture focuses on the core process functionality such as control flow and state management, monitoring, persistence, and communication, while using JavaScript as a process definition language. This approach leads to a very generic yet easily programmable process framework. A fully functional prototype implementation of the proposed framework is provided along with multiple example applications. Despite the fact that business processes are increasingly automated and controlled by information systems, humans are still involved, directly or indirectly, in many of them. Thus, for process flows involving sensitive transactions, a highly secure authorization scheme supporting asynchronous multi-party transaction authorization must be available within process management systems. Therefore, along with the ePVM framework, this thesis presents a novel approach for secure remote multi-party transaction authentication - the zone trusted information channel (ZTIC). The ZTIC approach uniquely combines multiple desirable properties such as the highest level of security, ease-of-use, mobility, remote administration, and smooth integration with existing infrastructures into one device and method. Extensively evaluating both, the ePVM framework and the ZTIC, this thesis shows that ePVM in combination with the ZTIC approach represents a unique and very powerful framework for building workflow systems and process-driven applications including support for secure multi-party transaction authorization

On the definition of non-player character behaviour for real-time simulated virtual environments.

Computer games with complex virtual worlds, which are populated by artificial characters and creatures, are the most visible application of artificial intelligence techniques. In recent years game development has been fuelled by dramatic advances in computer graphics hardware which have led to a rise in the quality of real-time computer graphics and increased realism in computer games. As a result of these developments video games are gaining acceptance and cultural significance as a form of art and popular culture. An important factor for the attainment of realism in games is the artificially intelligent behaviour displayed by the virtual entities that populate the games' virtual worlds. It is our firm belief that to further improve the behaviour of virtual entities, game AI development will have to mirror the advances achieved in game graphics. A major contributing factor for these advancements has been the advent of programmable shaders for real-time graphics, which in turn has been significantly simplified by the introduction of higher level programming languages for the creation of shaders. This has demonstrated that a good system can be vastly improved by the addition of a programming language. This thesis presents a similar (syntactic) approach to the definition of the behaviour of virtual entities in computer games. We introduce the term behaviour definition language (BDL), describing a programming language for the definition of game entity behaviour. We specify the requirements for this type of programming language, which are applied to the development and implementation of several behaviour definition languages, culminating in the design of a new game-genre independent behaviour definition (scripting) language. This extension programming language includes several game AI techniques within a single unified system, allowing the use of different methods of behaviour definition. A subset of the language (itself a BDL) was implemented as a proof of concept of this design, providing a framework for the syntactic definition of the behaviour of virtual entities in computer games

Bridging the Gap between Enumerative and Symbolic Model Checkers

We present a method to perform symbolic state space generation for languages with existing enumerative state generators. The method is largely independent from the chosen modelling language. We validated this on three different types of languages and tools: state-based languages (PROMELA), action-based process algebras (muCRL, mCRL2), and discrete abstractions of ODEs (Maple).\ud Only little information about the combinatorial structure of the\ud underlying model checking problem need to be provided. The key enabling data structure is the "PINS" dependency matrix. Moreover, it can be provided gradually (more precise information yield better results).\ud \ud Second, in addition to symbolic reachability, the same PINS matrix contains enough information to enable new optimizations in state space generation (transition caching), again independent from the chosen modelling language. We have also based existing optimizations, like (recursive) state collapsing, on top of PINS and hint at how to support partial order reduction techniques.\ud \ud Third, PINS allows interfacing of existing state generators to, e.g., distributed reachability tools. Thus, besides the stated novelties, the method we propose also significantly reduces the complexity of building modular yet still efficient model checking tools.\ud \ud Our experiments show that we can match or even outperform existing tools by reusing their own state generators, which we have linked into an implementation of our ideas

Advanced Grid programming with components: a biometric identification case study

Component-oriented software development has been attracting increasing attention for building complex distributed applications. A new infrastructure supporting this advanced concept is our prototype component framework based on the Grid component model. This paper provides an overview of the component framework and presents a case study where we utilise the component-oriented approach to develop a business process application for a biometric identification system. We then introduce the tools being developed as part of an integrated development environment to enable graphical component-based development of Grid applications. Finally, we report our initial findings and experiences of efficiently using the component framework and set of software tools

DATA DRIVEN INTELLIGENT AGENT NETWORKS FOR ADAPTIVE MONITORING AND CONTROL

To analyze the characteristics and predict the dynamic behaviors of complex systems over time, comprehensive research to enable the development of systems that can intelligently adapt to the evolving conditions and infer new knowledge with algorithms that are not predesigned is crucially needed. This dissertation research studies the integration of the techniques and methodologies resulted from the fields of pattern recognition, intelligent agents, artificial immune systems, and distributed computing platforms, to create technologies that can more accurately describe and control the dynamics of real-world complex systems. The need for such technologies is emerging in manufacturing, transportation, hazard mitigation, weather and climate prediction, homeland security, and emergency response. Motivated by the ability of mobile agents to dynamically incorporate additional computational and control algorithms into executing applications, mobile agent technology is employed in this research for the adaptive sensing and monitoring in a wireless sensor network. Mobile agents are software components that can travel from one computing platform to another in a network and carry programs and data states that are needed for performing the assigned tasks. To support the generation, migration, communication, and management of mobile monitoring agents, an embeddable mobile agent system (Mobile-C) is integrated with sensor nodes. Mobile monitoring agents visit distributed sensor nodes, read real-time sensor data, and perform anomaly detection using the equipped pattern recognition algorithms. The optimal control of agents is achieved by mimicking the adaptive immune response and the application of multi-objective optimization algorithms. The mobile agent approach provides potential to reduce the communication load and energy consumption in monitoring networks. The major research work of this dissertation project includes: (1) studying effective feature extraction methods for time series measurement data; (2) investigating the impact of the feature extraction methods and dissimilarity measures on the performance of pattern recognition; (3) researching the effects of environmental factors on the performance of pattern recognition; (4) integrating an embeddable mobile agent system with wireless sensor nodes; (5) optimizing agent generation and distribution using artificial immune system concept and multi-objective algorithms; (6) applying mobile agent technology and pattern recognition algorithms for adaptive structural health monitoring and driving cycle pattern recognition; (7) developing a web-based monitoring network to enable the visualization and analysis of real-time sensor data remotely. Techniques and algorithms developed in this dissertation project will contribute to research advances in networked distributed systems operating under changing environments