Till Örebro universitet

An increasing interest is growing around the idea of microservices and the promise of improving scalability when compared to monolithic systems. Several companies are evaluating pros and cons of a complex migration. In particular, financial institutions are positioned in a difficult situation due to the economic climate and the appearance of agile competitors that can navigate in a more flexible legal framework and started their business since day one with more agile architectures and without being bounded to outdated technological standard. In this paper, we present a real world case study in order to demonstrate how scalability is positively affected by re-implementing a monolithic architecture (MA) into a microservices architecture (MSA). The case study is based on the FX Core system, a mission critical system of Danske Bank, the largest bank in Denmark and one of the leading financial institutions in Northern Europe. The technical problem that has been addressed and solved in this paper is the identification of a repeatable migration process that can be used to convert a real world Monolithic architecture into a Microservices architecture in the specific setting of financial domain, typically characterized by legacy systems and batch-based processing on heterogeneous data sources.

The tsunami of connectivity brought by the Internet of Things is rapidly revolutionising several sectors, ranging from industry and manufacturing, to home automation, healthcare and many more. When it comes to enforce security within an IoT network such as a smart home, there is a need to automatically recognise the type of each joining devices, in order to apply the right security policy. In this paper, we propose a method for identifying IoT devices’ types based on natural language processing (NLP), text classification, and web search engines. We implement a proof of concept and we test it against 33 different IoT devices. With a success rate of 88.9% for BACnet and 87.5% for MUD devices, our experiments show that we can efficiently and effectively identify different IoT devices.

A key application of the Internet of Things (IoT) paradigm lies within industrial contexts. Indeed, the emerging Industrial Internet of Things (IIoT), commonly referred to as Industry 4.0, promises to revolutionize production and manufacturing through the use of large numbers of networked embedded sensing devices, and the combination of emerging computing technologies, such as Fog/Cloud Computing and Artificial Intelligence. The IIoT is characterized by an increased degree of inter-connectivity, which not only creates opportunities for the industries that adopt it, but also for cyber-criminals. Indeed, IoT security currently represents one of the major obstacles that prevent the widespread adoption of IIoT technology. Unsurprisingly, such concerns led to an exponential growth of published research over the last few years. To get an overview of the field, we deem it important to systematically survey the academic literature so far, and distill from it various security requirements as well as their popularity. This paper consists of two contributions: our primary contribution is a systematic review of the literature over the period 2011-2019 on IIoT Security, focusing in particular on the security requirements of the IIoT. Our secondary contribution is a reflection on how the relatively new paradigm of Fog computing can be leveraged to address these requirements, and thus improve the security of the IIoT.

Disbursement registration has always been a cumbersome, opaque, and inefficient process, up to the point that most businesses perform cash-flow evaluations only on a quarterly basis. We believe that automatic cash-flow evaluations can actively mitigate these issues. In this paper, we presentBitFlow, ablockchain-based architecture thatprovides complete cash-flow transparency and diminishes the probability of undetected frauds through the BitKrone, a non-volatile cryptocurrency that maps to the Danish Krone (DKK). We show that confidentiality can be effectively achieved on a permissionless blockchain using Zero-Knowledge proofs, ensuring verifiable transfers and automatic evaluations. Furthermore, we discuss several experiments to evaluate our proposal, in particular, the impact that confidential transactions have on the whole system, in terms of responsiveness and from an economical expenditure perspective.

Security is a serious, and often neglected, issue in the Internet of Things (IoT). In order to improve IoT security, researchers proposed to use Security-by-Contract (S×C), a paradigm originally designed for mobile application platforms. However, S×C assumes that manufacturers equip their devices with security contracts, which makes hard to integrate legacy devices with S×C. In this paper, we explore a method to extract S×C contracts from legacy devices’ Manufacturer Usage Descriptions (MUDs). We tested our solution on 28 different MUD files, and we show that it is possible to create basic S×C contracts, paving the way to complete extraction tools.

The Internet of Things (IoT) has been one of the key disruptive technologies over the last few years, with its promise of optimizing and automating current manual tasks and evolving existing services. However, the increasing adoption of IoT devices both in industries and personal environments has exposed businesses and consumers to a number of security threats, such as Distributed Denial of Service (DDoS) attacks. Along the way, Fog computing was born. A novel paradigm that aims at bridging the gap between IoT and Cloud computing, providing a number of benefits, including security. In this paper, we present ANTIBIOTIC 2.0, an anti-malware that relies upon Fog computing to secure IoT devices and to overcome the main issues of its predecessor (ANTIBIOTIC 1.0). In particular, we discuss the design and implementation of the system, including possible models for deployment, security assumptions, interaction among system components, and possible modes of operation.

The Internet of Things (IoT) has been one of the key disruptive technologies over the last few years, with its promise of optimizing and automating current manual tasks and evolving existing services. From the security perspective, the increasing adoption of IoT devices in all aspects of our society has exposed businesses and consumers to a number of threats, such as Distributed Denial of Service (DDoS) attacks. To tackle this IoT security problem, we proposed ANTIBIOTIC 1.0 In However, this solution has some limitations that make it difficult (when not impossible) to be implemented in a legal and controlled manner. Along the way, Fog computing was born: a novel paradigm that aims at bridging the gap between IoT and Cloud computing, providing a number of benefits, including security. As a result, in this paper, we present ANTIBIOTIC 2.0, an anti-malware that relies upon Fog computing to secure IoT devices and to overcome the main issues of its predecessor (ANTIBIOTIC 1.0). First, we present ANTIBIOTIC 1.0 and its main problem. Then, after introducing Fog computing, we present ANTIBIOTIC 2.0, showing how it overcomes the main issues of its predecessor by including Fog computing in its design.

The Internet of Things (IoT) is rapidly changing our society to a world where every thing is connected to the Internet, making computing pervasive like never before. This tsunami of connectivity and data collection relies more and more on the Cloud, where data analytics and intelligence actually reside. Cloud computing has indeed revolutionized the way computational resources and services can be used and accessed, implementing the concept of utility computing whose advantages are undeniable for every business. However, despite the benefits in terms of flexibility, economic savings, and support of new services, its widespread adoption is hindered by the security issues arising with its usage. From a security perspective, the technological revolution introduced by IoT and Cloud computing can represent a disaster, as each object might become inherently remotely hackable and, as a consequence, controllable by malicious actors. While the literature mostly focuses on the security of IoT and Cloud computing as separate entities, in this article we provide an up-to-date and well-structured survey of the security issues of cloud computing in the IoT era. We give a clear picture of where security issues occur and what their potential impact is. As a result, we claim that it is not enough to secure IoT devices, as cyber-storms come from Clouds.

In the last few years, Internet of Things, Cloud computing, Edge computing, and Fog computing have gained a lot of attention in both industry and academia. However, a clear and neat definition of these computing paradigms and their correlation is hard to find in the literature. This makes it difficult for researchers new to this area to get a concrete picture of these paradigms. This work tackles this deficiency, representing a helpful resource for those who will start next. First, we show the evolution of modern computing paradigms and related research interest. Then, we address each paradigm, neatly delineating its key points and its relation with the others. Thereafter, we extensively address Fog computing, remarking its outstanding role as the glue between IoT, Cloud, and Edge computing. In the end, we briefly present open challenges and future research directions for IoT, Cloud, Edge, and Fog computing.