Blockchain Papers

Xiwei Xu, Ingo Weber, Mark Staples

No abstract is available for this record.

Davy Preuveneers, Vera Rimmer, Ilias Tsingenopoulos, Jan Spooren · 6 authors

The adoption of machine learning and deep learning is on the rise in the cybersecurity domain where these AI methods help strengthen traditional system monitoring and threat detection solutions. However, adversaries too are becoming more effective in concealing malicious behavior amongst large amounts of benign behavior data. To address the increasing time-to-detection of these stealthy attacks, interconnected and federated learning systems can improve the detection of malicious behavior by joining forces and pooling together monitoring data. The major challenge that we address in this work is that in a federated learning setup, an adversary has many more opportunities to poison one of the local machine learning models with malicious training samples, thereby influencing the outcome of the federated learning and evading detection. We present a solution where contributing parties in federated learning can be held accountable and have their model updates audited. We describe a permissioned blockchain-based federated learning method where incremental updates to an anomaly detection machine learning model are chained together on the distributed ledger. By integrating federated learning with blockchain technology, our solution supports the auditing of machine learning models without the necessity to centralize the training data. Experiments with a realistic intrusion detection use case and an autoencoder for anomaly detection illustrate that the increased complexity caused by blockchain technology has a limited performance impact on the federated learning, varying between 5 and 15%, while providing full transparency over the distributed training process of the neural network. Furthermore, our blockchain-based federated learning solution can be generalized and applied to more sophisticated neural network architectures and other use cases.

Alina Buzachis, Massimo Villari

In recent years, the rapid development of Cloud, Edge and Internet of Things (IoT) technologies has accelerated the advancement trends forcing applications and information systems (IS) to evolve. In this new ecosystem, ISs are federated and usually highly distributed becoming complex and very dynamic that have to extend not only through the Cloud/Edge and IoT layers but also the federated organizational boundaries. In this context, Osmotic Computing (OC) is a new paradigm driven by the significant increase in capacity/capability of resources in highly distributed and federated environments, that solves problems related to the deployment, networking and security of microservices called MicroElements (MEL) that are composed and interconnected over Cloud/Edge and IoT infrastructures with specified levels of QoS and security constraints. In this federated collaborative system, each organization needs to have proper administration and security policies to maintain data security while allowing selective sharing of resources. Classical models of access control are not effective in protecting resources while allowing users to access to the resources within their privileges. Blockchain is an underlying technology that could help organizations to improve access control systems through consensus mechanisms, and underlying features of immutability, transparency, auditability, and cryptography. In this work, we propose a MELs orchestration approach through a Software Defined Membrane (SDMem) that leverages Blockchain facilities obeying the osmosis principles.

Dongho Kim, Hye-Won Kim

As the complexity of software increases, the importance of software quality is ever increasing, as everyone recognizes. In order to secure software quality, various engineering methods have been proposed. However, because these methods are very specialized, the reality is that it is difficult to apply them to a distributed and small-scale development environment. So, to solve this problem, a tool to analyze the quality of source code is used. Still, it is not easy to rely on code quality in a distributed development environment. In this study, source code quality data measured in a distributed development environment is stored in a blockchain ledger based on a graph database. In this way, the reliability of code quality in a distributed development environment can be enhanced.

Ioana Stănescu, Lenuța Alboaie, Andrei Panu

Blockchain has emerged as a trusted and secure distributed ledger for transactions while also being decentralised, distributed and its legitimacy not guaranteed by a trusted authority. Since the appearance of Bitcoin, Blockchain has known many implementations based on P2P architectures. This paper presents how the blockchain and smart contracts technologies can be integrated into the SwarmESB ecosystem. SwarmESB is a framework that helps building distributed applications, which benefit from privacy and scalability features. Our proposal will present the flexibility in building not only microservices based applications, but also decen-tralised applications employing blockchain and smart-contracts by modeling a sample Dapp.

Kristjan Kuhi, Kati Kõrbe Kaare, Ott Koppel

Information and communication technology has been a positive dynamic force behind improving performance. Simultaneously enabling digital business ecosystems to become an increasingly popular concept for modelling and building distributed systems in heterogeneous, decentralized and open environments. These business solutions have created an opportunity for automated business relations and transactions as well as implementing blockchain based performance measurement systems (PMS), allowing PMS to be more advanced giving validation and verification of received data hence the indicators. This paper evaluates feasibility of blockchain based PMS for logistics industry. Today the performance of supply chain stakeholders including transport logistics is lacking transparency and restraining innovative digital improvements towards a connected, smart and efficient ecosystem. Current public blockchains are not feasible for given use case due to limited throughput, and transaction cost. In this paper we have evaluated different technological alternatives and found several new developments that make blockchain technology suitable for ensuring logistics sector performance measurement integrity. Validated indicators can add trustworthiness and visibility to management and process improvement decisions, as well as be subject to smart contracts and monetary transactions.

Jungho Kim, Sungwon Kang, Hwi Ahn, Changsup Keum · 5 authors

Recently, public interest in the blockchain technology has surged and various applications based on the technology have emerged. However, there has been little study on architectural evaluations of popular block chain platforms that can help the developers choose an appropriate architecture matching their needs. In this paper, we reconstruct and evaluate the architecture of Hyperledger and Ethereum, which are representative open source platforms for blockchain. The evaluation results indicate that Hyperledger is strong in modifiability and performance whereas Ethereum is better in security.

Holger Kinkelin, Valentin Hauner, Heiko Niedermayer, Georg Carle

Numerous IoT applications, like building automation or process control of\nindustrial sites, exist today. These applications inherently have a strong\nconnection to the physical world. Hence, IT security threats cannot only cause\nproblems like data leaks but also safety issues which might harm people.\nAttacks on IT systems are not only performed by outside attackers but also\ninsiders like administrators. For this reason, we present ongoing work on a\nconfiguration management system (CMS) that provides control over\nadministrators, restrains their rights, and enforces separation of concerns. We\nreach this goal by conducting a configuration management process that requires\nmulti-party authorization for critical configurations to achieve Byzantine\nfault tolerance against attacks and faults by administrators. Only after a\nconfiguration has been authorized by multiple experts, it is applied to the\ntargeted devices. For the whole configuration management process, our CMS\nguarantees accountability and traceability. Lastly, our system is\ntamper-resistant as we leverage Hyperledger Fabric, which provides a\ndistributed execution environment for our CMS and a blockchain-based\ndistributed ledger that we use to store the configurations. A beneficial side\neffect of this approach is that our CMS is also suitable to manage\nconfigurations for infrastructure shared across different organizations that do\nnot need to trust each other.\n

Holger Kinkelin, Valentin Hauner, Heiko Niedermayer, Georg Carle

Numerous IoT applications, like building automation or process control of industrial sites, exist today. These applications inherently have a strong connection to the physical world. Hence, IT security threats cannot only cause problems like data leaks but also safety issues which might harm people. Attacks on IT systems are not only performed by outside attackers but also insiders like administrators. For this reason, we present ongoing work on a Byzantine fault tolerant configuration management system (CMS) that provides control over administrators, restrains their rights, and enforces separation of concerns. We reach this goal by conducting a configuration management process that requires multi-party authorization for critical configurations to prevent individual malicious administrators from performing undesired actions. Only after a configuration has been authorized by multiple experts, it is applied to the targeted devices. For the whole configuration management process, our CMS guarantees accountability and traceability. Lastly, our system is tamper-resistant as we leverage Hyperledger Fabric, which provides a distributed execution environment for our CMS and a blockchain-based distributed ledger that we use to store the configurations. A beneficial side effect of this approach is that our CMS is also suitable to manage configurations for infrastructure shared across different organizations that do not need to trust each other.

Imre Kocsis, Attila Klenik, András Pataricza, Miklós Telek · 6 authors

Timeliness and throughput critical applications require a framework offering predictable temporal characteristics. The best practice for estimating a prediction of the system dynamics relies on benchmarking. Each novel middleware solution needs such an evaluation as part of the development process to assure an appropriate throughput in the future use. General purpose blockchain frameworks are viable replacements for many current systems in several sectors by providing a fully distributed, secure, and non-repudiable ledger as a service. Blockchain technologies target domains with a large number of interactions, thus demanding strict performance guarantees. Engineering for performance targets in a trustworthy manner requires performance models. However, performance characteristics of blockchain systems are highly unexplored due to the novelty of the technology. This paper proposes a general-purpose, systematic methodology for the performance analysis of complex systems, aided by a component-in-the-loop approach. The Linux foundation-hosted hyperledger fabric serves as a case study for the presented methodology.

Franco Callegati, Maurizio Gabbrielli, Saverio Giallorenzo, Andrea Melis · 5 authors

Multi-modal travelling is a common phenomenon. However, planning multi-modal journeys is still an unstructured and time-consuming experience for customers: they lose time assembling a comprehensive plan out of disparate data, spread over a multitude of information systems - each corresponding to a different company responsible for one of the legs in the journey. Also transport operators are affected by the sparsity of the transportation market, as they might lose potential customers who could not find or know about their services. In this paper, we propose Mobility as a Service (MaaS) as a solution to such problems. Key element of MaaS is that MaaS operators can aggregate solutions of multiple providers to deliver dynamic, transparent multi-modal travels to their users, who experience transportation as managed directly by a single operator. However, given the volume and sparsity of the transportation market, we argue that MaaS operators cannot rely on one-to-one, custom contracts of usage with single mobility operators. Instead, we envision the creation of platforms that automatise the marketing of services for mobility among many mobility providers. In this work, we detail the required features of a general software platform for such a MaaS market. In particular, we provide a precise definition of MaaS through the MaaS Stack - a tiered view of the components needed by entities to join the MaaS market. Then, through the lens of the MaaS Stack, we elicit the features of an enabling software platform. Finally, to validate our approach, we present a compliant prototype, called SMAll, and discuss its main design choices, among which: i) how SMAll supports the creation of a federation-based MaaS market and ii) how microservices - an emerging architectural style that fosters cohesiveness and minimality of components - enhance flexibility and let the platform and the services of its members efficiently scale according to dynamic demands.

Rajitha Yasaweerasinghelage, Mark Staples, Ingo Weber

Blockchain is an emerging technology for sharing transactional data and computation without using a central trusted third party. It is an architectural choice to use a blockchain instead of traditional databases or protocols, and this creates trade-offs between non-functional requirements such as performance, cost, and security. However, little is known about predicting the behaviour of blockchain-based systems. This paper shows the feasibility of using architectural performance modelling and simulation tools to predict the latency of blockchain-based systems. We use established tools and techniques, but explore new blockchain-specific issues such as the configuration of the number of confirmation blocks and inter-block times. We report on a lab-based experimental study using an incident management system, showing predictions of median system level response time with a relative error mostly under 10%. We discuss how the approach can be used to support architectural decision-making, during the design of blockchain-based systems.

M. Teresa Higuera‐Toledano, Uwe Brinkschulte, Achim Rettberg

The increasing complexity of contemporary embedded computing systems requires the use of self-management in order to handle unforeseen changes in both hardware and application environments (i.e., hardware/software defects, resource changes, and non-continual feature usage). Moreover, often these systems are distributed, running on processor architectures with multiple cores, which may require self-organization to ensure efficiency and reliability. Real-time properties are another key issue in many complex systems. Adaptive and self-organized properties extent the area of operations and improves the efficiency of the system resources at the cost to introduce additional complexity, overhead, and resource requirements. Consequently, real-time adaptive systems must be careful analyzed, designed, and built taken into account the right tradeoffs between flexibility and complexity, while accomplishing time-constrains. The combination of the flexibility and uncertain behavior of self-organizing systems with time-predictability is a grand challenge. Therefore, substantial research has been done in the last years to address the so-called Self-X features (e.g., self-configuration, self-optimization, self-adaptation, self-healing, and self-protection). This fact has as resutl that self-organizing computing systems become an established research nowadays as they promise to handle the increasing complexity resulting from highly distributed systems and ubiquitous applications. In addition, real-time properties are required in many areas (such as cyber physical systems) self-organizing computing systems are dealing with. Combining the flexible and and uncertain behavior of self-organizing systems with time-predictability necessary for real-time systems is a grand challenge. The Workshop on Self-Organizing Real-Time Systems (SORT) is specifically dedicated to research on adaptive real-time systems. SORT started 2014 as a workshop attached at International Symposium on Object/Component/Service-Oriented Real-Time Distributed Computing (ISORC). The purpose of this workshop is to provide an open forum to discuss new and ongoing research that is centered on the idea of adaptability in real-time systems. The target audience includes researchers from academia, tool vendors, system suppliers, and users in industry who are interested in the all aspects of the topics mentioned below. This special issue of Concurrency and Computation: Practice and Experience contains four invited papers from the SORT 2014 workshop that has been expanded and carefully peer reviewed. The first paper, titled An Artificial DNA for Self-Descripting and Self-Building Embedded Real-Time Systems 1, Uwe Brinkschulte proposes an approach to use an artificial DNA-based approach for embedded real-time and distributed systems. This kind of systems is growing more and more complex because of the increasing chip integration density, larger number of chips in distributed applications and demanding application fields (e.g., in cars and in households). Bio-inspired techniques like self-organization are a key feature to handle this complexity. Because many embedded systems can be composed from a limited number of basic elements, the structure and parameters of such systems can be stored in a compact way representing an artificial DNA deposited in each computation node. This leads to a self-describing system. Based on the DNA, the self-organization mechanisms can build the system autonomously providing a selfbuilding system. System repair and optimization at runtime are also possible, leading to higher robustness, dependability, and flexibility. Autonomous adaptation in self-adapting embedded real-time systems introduces novel risks as it may lead to unforeseen system behavior. An anomaly detection framework integrated in a real-time operating system can ease the identification of such suspicious novel behavior and, thereby, offers the potential to enhance the reliability of the considered self-x system. However, anomaly detection is based on knowledge about normal behavior. When dealing with self-reconfiguring applications, normal behavior changes. Hence, knowledge base requires adaptation or even reconstruction at runtime. The stringent restrictions of real-time systems considering runtime and memory consumption make this task to a really challenging problem. In next paper, Two-Level Extensions of an Artifical Hormone System 2, Mathias Pacher describes a decentralized software which is able to allocate tasks in a system of heterogeneous processing elements. Tasks are allocated according to their suitability for the heterogeneous processing elements, the current processing element and task relationships. This software provides properties like self-configuration, self-optimization, and self-healing in the context of task allocation. In addition, it is able to guarantee real-time bounds for such self-X-properties. However, using self-organization principles introduces increased system complexity such as control of system parameters for self-organization and additional communication effort, which have been addressed by using a hierarchic structure. This solution uses a machine learning approach presenting an Observer-/Controller architecture. The user has to provide a simple set of initial rules and the Observer-/Controller is able to generate new rules if needed. This paper also presents a hierarchical structure to save communication bandwidth, which consists of several different clusters of processing elements where each cluster has its own communication infrastructure (e.g., a bus system). In the paper titled Online behavior classification for anomaly detection in self-x real-time systems 3, Katharina Stahl presents an online construction of application behavior knowledge that does not rely on training phase. The applications' behavior is defined by the application's system call invocations. For the knowledge base, they use Suffix Trees to represent application behavior patterns and associated information in a compact manner. The online algorithm provided by Suffix Trees is a basis to construct the knowledge base with low computational effort. Anomaly detection and classification is integrated into the online construction method. New behavioral patterns do not unconditionally update the behavior knowledge base. They are evaluated in a context-related manner inspired by Danger Theory, a special discipline of Artificial Immune Systems. For highly safety-critical applications, rigorous offline verification should be complemented by online verification. One promising technique is Online Model Checking (OMC). As OMC is a run- time-provided service, it seems to be natural providing it by an operating system service like any other service offered by the OS. In the paper titled Efficient Integration of Online Model Checking into a Small-Footprint Real-time Operating System 4 the authors study the feasibility of integrating OMC as an RTOS service. In order to ease understanding the approach, the paper discusses various integration methods in which OMC runs concurrently to the application task to be online model checked. The OMC may become: (i) an integral part of the RTOS, (ii) a separate task running on the same host as the RTOS, or (iii) a remote host as a kind of service-oriented architecture.

Fu Hou, Xinjun Mao, Wei Wu, Lu Liu · 5 authors

The services in open and dynamic Cloud Computing environments are often decentralized, evolving and are cross-organized. Efficient management of the Cloud resources for the improvement of the quality and efficiency of the service provisions is still being a continuous challenge in Cloud domain. To this end, this paper proposes a self-management approach for the cloud services, with an autonomous and context-aware management of the resources by employing a number of service agents in the Cloud environment. Such service agents are responsible for organizing the service management through their local interactions in the system, and further leading to the expected emergence of the service organization. Based on this approach, we present a cloud-oriented services self-management framework with suitable mechanisms for service aggregations and service provisions. And, two supporting algorithms are designed to implement the proposed services self-organization process and also the service provision process. We conduct various experiments on public data sets, and the experimental results prove the efficiency of our system in improving the quality of the Cloud services and also the practical adaptability of our system to the ever changing Cloud environment.

Flavio Junqueira, I. W. Kelly, Benjamin Reed

Practical systems must often guarantee that changes to the system state are durable. Examples of such systems are databases, file systems, and messaging middleware with guaranteed delivery. One common way of implementing durability while keeping performance high is to use a log to persist updates to the system state. Such systems use the log to reconstruct the system state in the event of a crash. When implementing such a log, if the log is only stored locally, the system state is permanently lost when the server writing the log experiences a permanent hardware failure. BookKeeper is a system that exposes a log abstraction for building high performance, highly available distributed systems. BookKeeper transparently implements replication for high availability and striping for high performance. A Book- Keeper deployment comprises storage servers called bookies, which are designed to serve a large number of concurrent ledgers. BookKeeper is currently an open-source project and is in production use at Yahoo!

Antonia Bertolino, Guglielmo De Angelis, Antonino Sabetta, Andrea Polini

Service Oriented Architecture (SOA) is changing the way in which software applications are designed, deployed and maintained. A service-oriented application consists of the runtime composition of autonomous services that are typically owned and controlled by different organizations. This decentralization impacts on the dependability of applications that consist of dynamic services agglomerates, and challenges their validation. Different techniques can be used or combined for the verification of dependability aspects, spanning over traditional off-line testing approaches, monitoring, and on-line testing. In this chapter we discuss issues and opportunities of SOA validation, we identify three different stages for validation along the service life-cycle model, and we overview some proposed research approaches and tools. The emphasis is on on-line testing, which to us is the most peculiar stage in the SOA validation process. Finally, we claim that on-line testing is only possible within an agreed governance framework.

ICSOC 2020 Online, Kafeza, Eleanna, Benatallah, Boualem, Martinelli, Fabio · 7 authors

No abstract is available for this record.

Wei-Lun Kao, R.K. Iyer

This paper presents a distributed fault injection and monitoring environment (DEFINE) as a tool to evaluate system dependability, to investigate fault propagation, and to validate fault-tolerant mechanisms. DEFINE can inject both hardware faults (hardware-induced software errors) and software faults into any process running in a distributed system, either in user mode or in supervisor mode, and monitor the fault impact and propagation in software systems and among machines. It employs two fault injection techniques: (i) using hardware clock interrupts to control the time of fault injection and activation, and (ii) using software traps to inject all the faults except communication faults and memory faults in the data/stack segment. Experiments on six Sun SPARCstations to study the system behavior under faults are conducted to demonstrate the application of DEFINE.

C.-Q. Yang, B.P. Miller

The authors present the design, implementation, and testing of the critical path analysis technique using the IPS performance measurement tool for parallel and distributed programs. They create a precedence graph of a program's activities (program activity graph) with the data collected during the execution of a program. The critical path, the longest path in the program activity graph, represents the sequence of the program activities that take the longest time to execute. Various algorithms are developed to track the critical path from this graph. The events in this path are associated with the entities in the source program, and the statistical results are displayed on the basis of the hierarchical structure of the IPS. The test results from the measurement of sample programs show that the knowledge of the critical path in a program's execution helps users identify performance problems and better understand the behavior of a program.>