Analysis of cybersecurity threats in Industry 4.0: the case of intrusion detection

Nowadays, industrial control systems are experiencing a new revolution with the interconnection of the operational equipment with the Internet, and the introduction of cutting-edge technologies such as Cloud Computing or Big data within the organization. These and other technologies are paving the way to the Industry 4.0. However, the advent of these technologies, and the innovative services that are enabled by them, will also bring novel threats whose impact needs to be understood. As a result, this paper provides an analysis of the evolution of these cyber-security issues and the requirements that must be satis ed by intrusion detection defense mechanisms in this context.Springer ; Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Educating the educators: Incorporating bioinformatics into biological science education in Malaysia

Bioinformatics can be defined as a fusion of computational and biological sciences. The urgency to process and analyse the deluge of data created by proteomics and genomics studies has caused bioinformatics to gain prominence and importance. However, its multidisciplinary nature has created a unique demand for specialist trained in both biology and computing. In this review, we described the components that constitute the bioinformatics field and distinctive education criteria that are required to produce individuals with bioinformatics training. This paper will also provide an introduction and overview of bioinformatics in Malaysia. The existing bioinformatics scenario in Malaysia was surveyed to gauge its advancement and to plan for future bioinformatics education strategies. For comparison, we surveyed methods and strategies used in education by other countries so that lessons can be learnt to further improve the implementation of bioinformatics in Malaysia. It is believed that accurate and sufficient steerage from the academia and industry will enable Malaysia to produce quality bioinformaticians in the future

The impact of Cloud Computing and organizational sustainability

When economic times get tough, businesses worldwide are compelled to review their organizational expenses and priorities and to strategically consider how best to save. Traditionally, Information Technology (IT) department is one area that would be affected negatively in the review. To better serve the organization and clients and for business to continue to increase productivity, it is important to understand which technology investments might allow for cost reduction and efficient use of resources. Continuing to fund these strategic technologies during an economic downturn is vital to organizations. It is predicted that in coming years IT resources will only be available online. More and more organizations are looking at operating smarter businesses by investigating technologies such as cloud computing, virtualization and green IT to find ways to cut costs and increase efficiencies. 'Cloud computing' is one recent phenomenon which is predominantly driven by industry recognition of the triple bottom line making sustainability their focus. This is also driven by industry needs that may have the ability to transform the workplace, with a focus on capital expenditure, infrastructure, applications, usage, mobility, and cost structure.The attraction of cloud computing is obvious with noticeable freedom from managing and hosting applications, platforms, and infrastructure. Though advantages of cloud computing are countless, cloud computing is still in its infancy and has disadvantages such as security, privacy, reliability, physical location of data and the unavailability of service due to crashes or bugs in providers' storages; the consequences of which are merely unknown. These disadvantages might be tackled through the proper introduction, training and implementation of codes of ethics as guiding principle to those involved in the usage of cloud computing in business. This paper provides a brief literature review of cloud computing, followed by an analysis of the cloud-computing environment using the PESTEL framework. The future implications and limitations of adopting cloud computing as an effective ecofriendly strategy to reduce carbon footprint are also discussed in the paper. This paper concludes with a recommendation to guide researchers to further examine this phenomenon

The impact of digital disruption in the maintenance service industry, in the oil and gas sector

Master's thesis in Technology and Operations managementThe industry is on the brink on what many consider as paradigm shift due to disruptive technological developments. The current trend of automation, Internet of things, big data analysis, cloud computing, together with the emergence of artificial intelligence, advanced robotics and autonomous vehicles has been labelled as a digital disruption. A combination of better computing power and data storage, together with more reasonable pricing structures makes the digital disruption more accessible and possible to any industry. There is broad consensus among think tanks, experts and industrial leaders that organization needs to embrace this development to stay relevant and competitive in the future. The thesis is an exploratory research to examine how the digital disruption will impact the maintenances service industry in the Oil and Gas sector. To understand the complexity of the transformation, it covers analysis of multiple elements that includes: expectations and semantics, technological solutions and services, changes in competences and skill sets, changes in business model and strategy, stakeholder perspective, and a summary of risk and opportunities. The research is conducted with a mixed-method approach, which covers quantitative survey data from global trends, together with qualitative case studies and interviews from relevant stakeholders in the industry. The research highlights that the digital disruption is more than a buzzword or an incremental change towards existing business models and practices. Digital technologies enable a whole new way to create and harness value, and is about to transform the nature of work tasks and future job requirements. Data driven technologies will require more digital literacy of the entire workforce, which puts an added pressure on training and development. Digital talents, such as data analysts and computer scientists are becoming more central to the business operations, and requires more cross-functional collaboration across the organization. Organizational structure and culture must adapt to a digital environment, where employees are empowered to make business decisions and initiate digital innovation efforts. The digital disruption will also reshape the organizational environment, which results in reshaping existing stakeholder relationships and the introduction of new ones. Change management is going to be key to succeed in the digital transformation, and viewing it as an opportunity rather than a threat will decide the fate of success for many organizations.publishedVersio

How the Growth of Technology has Forced Accounting Firms to put an Emphasis on Cybersecurity

The advancement of technology has brought many changes to accounting firms. Computer applications such as Microsoft Excel have made calculators and physical spreadsheets obsolete. Then with the introduction of cloud computing employees can store, access, and exchange large amounts of data instantaneously from any location. These technological innovations have increased the accuracy and efficiency of firms substantially. However, this growth in technology has shown the importance of putting an emphasis on cybersecurity throughout the accounting industry. The emphasis placed on cybersecurity throughout accounting firms is more prevalent than any other industry. This is primarily because accounting firms not only deal with large amounts of internal financial data, but also other companies’ financial data for audit and tax purposes. This paper begins by showing the biggest and most common cybersecurity threats firms face today. It then outlines the steps firms can put in place to minimize the risk of falling victim to these threats. Moreover, it will compare the challenges of maintaining sufficient cybersecurity between large and small accounting firms and provide examples of different repercussions firms faced after experiencing a breach in their cybersecurity. Finally, it will highlight the new regulations and guidelines established in order to strengthen a firm’s cybersecurity throughout the accounting field

Facing the Industrial Revolution 4.0: Taiwanese and Indonesian Perspective

Industrial Revolution 4.0 offers both challenges and opportunities for all countries. Every country has to adopt best strategies to deal with its dynamic and complexity. This paper aims at discussing the legal policies adopted by Indonesia and Taiwan to face this industrial revolution. This research employs a descriptive- qualitative method with comparative approach. It is found that Industrial Rrevolution 4.0, also known as the intelligent industry, seeks to transform a company into an intelligent organization to achieve the best business results. Indonesia officially launched the road-map called “Making Indonesia 4.0” in 2018. In the same year, Indonesia has started to set up the main plain of the program for five focuses sectors ex: food and drink, textile and clothing, automotive, chemist and electronic, and additional ten cross priority sectors. While Taiwan proposed its own version of Industry 4.0 called “Productivity 4.0” in 2014. This includes the use of large quantity of robots and production lines, the automation of manufacturing procedures, the introduction of Industry 4.0 and Internet of Things (IoT) technology, and cloud computing for immediate data processing. It makes Industry 4.0 as the national policy for industrial transformation

Industrial internet of things platform for predictive maintenance

POCI-01-0247-FEDER-038436Industry 4.0, allied with the growth and democratization of Artificial Intelligence (AI) and the advent of IoT, is paving the way for the complete digitization and automation of industrial processes. Maintenance is one of these processes, where the introduction of a predictive approach, as opposed to the traditional techniques, is expected to considerably improve the industry maintenance strategies with gains such as reduced downtime, improved equipment effectiveness, lower maintenance costs, increased return on assets, risk mitigation, and, ultimately, profitable growth. With predictive maintenance, dedicated sensors monitor the critical points of assets. The sensor data then feed into machine learning algorithms that can infer the asset health status and inform operators and decision-makers. With this in mind, in this paper, we present TIP4.0, a platform for predictive maintenance based on a modular software solution for edge computing gateways. TIP4.0 is built around Yocto, which makes it readily available and compliant with Commercial Off-the-Shelf (COTS) or proprietary hardware. TIP4.0 was conceived with an industry mindset with communication interfaces that allow it to serve sensor networks in the shop floor and modular software architecture that allows it to be easily adjusted to new deployment scenarios. To showcase its potential, the TIP4.0 platform was validated over COTS hardware, and we considered a public data-set for the simulation of predictive maintenance scenarios. We used a Convolution Neural Network (CNN) architecture, which provided competitive performance over the state-of-the-art approaches, while being approximately four-times and two-times faster than the uncompressed model inference on the Central Processing Unit (CPU) and Graphical Processing Unit, respectively. These results highlight the capabilities of distributed large-scale edge computing over industrial scenarios.publishersversionpublishe

D 3 -MapReduce: Towards MapReduce for Distributed and Dynamic Data Sets

International audienceSince its introduction in 2004 by Google, MapRe-duce has become the programming model of choice for processing large data sets. Although MapReduce was originally developed for use by web enterprises in large data-centers, this technique has gained a lot of attention from the scientific community for its applicability in large parallel data analysis (including geographic, high energy physics, genomics, etc.). So far MapReduce has been mostly designed for batch processing of bulk data. The ambition of D 3-MapReduce is to extend the MapReduce programming model and propose efficient implementation of this model to: i) cope with distributed data sets, i.e. that span over multiple distributed infrastructures or stored on network of loosely connected devices; ii) cope with dynamic data sets, i.e. which dynamically change over time or can be either incomplete or partially available. In this paper, we draw the path towards this ambitious goal. Our approach leverages Data Life Cycle as a key concept to provide MapReduce for distributed and dynamic data sets on heterogeneous and distributed infrastructures. We first report on our attempts at implementing the MapReduce programming model for Hybrid Distributed Computing Infrastructures (Hybrid DCIs). We present the architecture of the prototype based on BitDew, a middleware for large scale data management, and Active Data, a programming model for data life cycle management. Second, we outline the challenges in term of methodology and present our approaches based on simulation and emulation on the Grid'5000 experimental testbed. We conduct performance evaluations and compare our prototype with Hadoop, the industry reference MapReduce implementation. We present our work in progress on dynamic data sets that has lead us to implement an incremental MapReduce framework. Finally, we discuss our achievements and outline the challenges that remain to be addressed before obtaining a complete D 3-MapReduce environment

Innovation in manufacturing through digital technologies and applications: Thoughts and Reflections on Industry 4.0

The rapid pace of developments in digital technologies offers many opportunities to increase the efficiency, flexibility and sophistication of manufacturing processes; including the potential for easier customisation, lower volumes and rapid changeover of products within the same manufacturing cell or line. A number of initiatives on this theme have been proposed around the world to support national industries under names such as Industry 4.0 (Industrie 4.0 in Germany, Made-in-China in China and Made Smarter in the UK). This book presents an overview of the state of art and upcoming developments in digital technologies pertaining to manufacturing. The starting point is an introduction on Industry 4.0 and its potential for enhancing the manufacturing process. Later on moving to the design of smart (that is digitally driven) business processes which are going to rely on sensing of all relevant parameters, gathering, storing and processing the data from these sensors, using computing power and intelligence at the most appropriate points in the digital workflow including application of edge computing and parallel processing. A key component of this workflow is the application of Artificial Intelligence and particularly techniques in Machine Learning to derive actionable information from this data; be it real-time automated responses such as actuating transducers or informing human operators to follow specified standard operating procedures or providing management data for operational and strategic planning. Further consideration also needs to be given to the properties and behaviours of particular machines that are controlled and materials that are transformed during the manufacturing process and this is sometimes referred to as Operational Technology (OT) as opposed to IT. The digital capture of these properties and behaviours can then be used to define so-called Cyber Physical Systems. Given the power of these digital technologies it is of paramount importance that they operate safely and are not vulnerable to malicious interference. Industry 4.0 brings unprecedented cybersecurity challenges to manufacturing and the overall industrial sector and the case is made here that new codes of practice are needed for the combined Information Technology and Operational Technology worlds, but with a framework that should be native to Industry 4.0. Current computing technologies are also able to go in other directions than supporting the digital ‘sense to action’ process described above. One of these is to use digital technologies to enhance the ability of the human operators who are still essential within the manufacturing process. One such technology, that has recently become accessible for widespread adoption, is Augmented Reality, providing operators with real-time additional information in situ with the machines that they interact with in their workspace in a hands-free mode. Finally, two linked chapters discuss the specific application of digital technologies to High Pressure Die Casting (HDPC) of Magnesium components. Optimizing the HPDC process is a key task for increasing productivity and reducing defective parts and the first chapter provides an overview of the HPDC process with attention to the most common defects and their sources. It does this by first looking at real-time process control mechanisms, understanding the various process variables and assessing their impact on the end product quality. This understanding drives the choice of sensing methods and the associated smart digital workflow to allow real-time control and mitigation of variation in the identified variables. Also, data from this workflow can be captured and used for the design of optimised dies and associated processes