Christoph Reich

Furtwangen University | HFU · Faculty of Computer Science

Industrial Internet of Things (IIoT) systems are enhancing the delivery of services and boosting productivity in a wide array of industries, from manufacturing to healthcare. However, IIoT devices are susceptible to cyber-threats such as the leaking of important information, products becoming compromised, and damage to industrial controls. Recently...

ML-based applications already play an important role in factories in areas such as visual quality inspection, process optimization, and maintenance prediction and will become even more important in the future. For ML to be used in an industrial setting in a safe and effective way, the different steps needed to use ML must be put together in an ML p...

To deliver better healthcare to patients and advance healthcare solutions as well as to increase the efficiency of the manufacturing process and thus reduce material and energy consumption in production, more and more artificial intelligence (AI) methods are applied in the field of both, Medicine and Manufacturing. Some of the exciting applications...

Image augmentation has become an important part of the data preprocessing pipeline, helping to acquire more samples by altering existing samples by cutting, shifting, etc.. For some domains, augmenting existing images is not sufficient, due to missing samples in the domains (e.g., faulty work pieces or events that occur infrequently). In such a cas...

The ‘things’ layer in Internet of Things (IoT) consists of a massive number of devices, many of which are power and resource constrained. Decentralized Attribute-based Encryption (DABE) provides a one-to-many scheme that fits the distributed nature of IoT, however requires extensive computation power which makes its adoption difficult. In this work...

The Internet of things (IoT) network resources generate enormous data. The generated real-time data can be used in various fields to improve the quality of the provided services and make smart decisions. One of the main concerns in such systems is validating the received data. Most data validations techniques rely and run on a centralized entity, w...

The traditional field of industrial manufacturing is in the process of being revolutionized as machines become smart and processes are translated to and perfected by digital systems. The application of Machine Learning (ML) has established itself as a smart technology in the manufacturing industry. The optimal operation and training of ML applicati...

In the context of Industry 4.0, smart factories use advanced sensing and data analytic technologies to understand and monitor the manufacturing processes. To enhance production efficiency and reliability, statistical Artificial Intelligence (AI) technologies such as machine learning and data mining are used to detect and predict potential anomalies...

To achieve a fully connected network in Internet of Things (IoT) there are number of challenges that have to be overcome. Among those, a big challenge is how to keep all of the devices accessible everywhere and every time. In the IoT network, the assumption is that each IoT device can be reached by any client at any given time. In practice, this is...

The resources in Internet of Things (IoT) are distributed among different physical geographic locations. In centralized resource discovery, the resources are registered in a centralized third-party server, and the clients can discover any resource by querying the centralized entity. In the decentralized resource discovery, the task of resource regi...

Enormous potential of artificial intelligence (AI) exists in numerous products and services, especially in healthcare and medical technology. Explainability is a central prerequisite for certification procedures around the world and the fulfilment of transparency obligations. Explainability tools increase the comprehensibility of object recognition...

In edge/fog computing infrastructures, the resources and services are offloaded to the edge and computations are distributed among different nodes instead of transmitting them to a centralized entity. Distributed Hash Table (DHT) systems provide a solution to organizing and distributing the computations and storage without involving a trusted third...

Distributed machine learning algorithms that employ Deep Neural Networks (DNNs) are widely used in Industry 4.0 applications, such as smart manufacturing. The layers of a DNN can be mapped onto different nodes located in the cloud, edge and shop floor for preserving privacy. The quality of the data that is fed into and processed through the DNN is...

Nowadays, machine learning projects have become more and more relevant to various real-world use cases. The success of complex Neural Network models depends upon many factors, as the requirement for structured and machine learning-centric project development management arises. Due to the multitude of tools available for different operational phases...

The resources in the Internet of Things (IoT) network are distributed among different parts of the network. Considering huge number of IoT resources, the task of discovering them is challenging. While registering them in a centralized server such as a cloud data center is one possible solution, but due to billions of IoT resources and their limited...

While the number of devices connected together as the Internet of Things (IoT) is growing, the demand for an efficient and secure model of resource discovery in IoT is increasing. An efficient resource discovery model distributes the registration and discovery workload among many nodes and allow the resources to be discovered based on their attribu...

The Internet of Things (IoT) consists of billions of resources distributed among different geographical locations. In centralized resource discovery, the resources are registered in a centralized third party server, and the clients can discover any resource by querying the centralized entity. In the decentralized resource discovery the task of reso...

The huge number of resources and their computation power capabilities in the Internet of Things (IoT) network brings new challenges comparing to traditional networks. Among those challenges is the used approach to register and discover the resources in IoT. In traditional network architectures, the resources are registered in a centralized trusted...

In recent years, both the Internet of Things (IoT) and blockchain technologies have been highly influential and revolutionary. IoT enables companies to embrace Industry 4.0, the Fourth Industrial Revolution, which benefits from communication and connectivity to reduce cost and to increase productivity through sensor-based autonomy. These automated...

Digital transformation strengthens the interconnection of companies in order to develop optimized and better customized, cross-company business models. These models require secure, reliable, and traceable evidence and monitoring of contractually agreed information to gain trust between stakeholders. Blockchain technology using smart contracts allow...

Within manufacturing processes, faults and failures may cause severe economic loss. With the vision of Industry 4.0, artificial intelligence techniques such as data mining play a crucial role in automatic fault and failure prediction. However, due to the heterogeneous nature of industrial data, data mining results normally lack both machine and hum...

The number of devices connected together in the Internet of Things (IoT) are growing and therefore the demand of an efficient and secure method for discovering the resources in IoT is increasing. In most of IoT schemes, the resources are discovered based on their properties (i.e. their location, types, etc.) and the clients are able to discover the...

Containers have become popular in HPC environments to improve the mobility of applications and the delivery of user-supplied code. In this paper we evaluate Podman, an enterprise container engine that supports rootless containers , in combination with runc and crun as container runtimes using a real-world workload with LS-DYNA and the industry-stan...

In the Industry 4.0 context, especially when considering large factories producing costly goods, monitoring sensor values is important to ensure high quality. This reduces large costs for mending faulty products or recall of those. Different approaches are used to ensure efficient monitoring and validation of sensor values. The Distributed Data Val...

The generated real-time data on the Internet of Things (IoT) and the ability to gather and manipulate them are positively affecting various fields. One of the main concerns in IoT is how to provide trustworthy data. The data validation network ensures that the generated data by data sources in the IoT are trustworthy. However, the existing data val...

In this paper, Region based Distributed Hash Table (RDHT) is proposed that can used in fog computing infrastructure to create an overlay of fog nodes divided logically into multiple regions based on their physical locations. RDHT generates a single overlay and it can be generated without specific organizing entity or location based devices.

Schleifen ist zu einem Standard-Produktionsschritt für die Präzisionsfertigung von Metallteilen geworden. Nicht optimale Prozessbedingungen während des Schleifprozesses können jedoch zu einer unangemessenen lokalen Temperaturerhöhung in der Randzone des Werkstücks führen und den sogenannten „Schleifbrand“ verursachen. Dies kann zu Gefügeveränderung...

Increased collaborative production and dynamic selection of production partners within industry 4.0 manufacturing leads to ever-increasing automatic data exchange between companies. Automatic and unsupervised data exchange creates new attack vectors, which could be used by a malicious insider to leak secrets via an otherwise considered secure chann...

The digital transformation of companies is expected to increase the digital interconnection between different companies to develop optimized, customized, hybrid business models. These cross-company business models require secure, reliable, and traceable logging and monitoring of contractually agreed information sharing between machine tools, operat...

The digital transformation of companies is expected to increase the digital interconnection between different companies to develop optimized, customized, hybrid business models. These cross-company business models require secure, reliable, and traceable logging and monitoring of contractually agreed information sharing between machine tools, operat...

Containers have to be secured in a multi-tenant environment. To secure the use of containerized environments, the effectiveness of a rule-based security monitoring approach have been investigated. The approach of this paper can be used to detect a wide range of potentially malicious behaviour of workloads in containerized environments. Additionally...

Billions of resources are connected to each other through the Internet of Things (IoT). Due to the huge number of connected resources in IoT, the challenge is how to discover the appropriate resources efficiently. The task becomes more challenging by taking into consideration the limited storage and computation power of devices and the distributed...

As today’s manufacturing domain is becoming more and more knowledge-intensive, knowledge-based systems (KBS) are widely applied in the predictive maintenance domain to detect and predict anomalies in machines and machine components. Within a KBS, decision rules are a comprehensive and interpretable tool for classification and knowledge discovery fr...

Ensuring data quality is central to the digital transformation in industry. Business processes such as predictive maintenance or condition monitoring can be implemented or improved based on the available data. In order to guarantee high data quality, a single data validation system are usually used to validate the production data for further use. H...

Cylindrical grinding is an important process in the manufacturing industry. During this process, the problem of grinding burn may appear, which can cause the workpiece to be worthless. In this work, a machine learning neural network approach is used to predict grinding burn based on the process parameters to prevent damage. A small dataset of 21 sa...

Current cloud architectures do not comply with today's digital forensics procedures-largely due to the fundamental dynamic nature of the cloud. Data acquisition is the first and arguably the most important process within digital forensics-to ensure data integrity and admissibility. Currently investigators have no option but to rely on the Cloud Ser...

Following the trend of Industry 4.0, automation in different manufacturing processes has triggered the use of intelligent condition monitoring systems, which are crucial for improving productivity and availability of production systems. To develop such an intelligent system, semantic technologies are of paramount importance. This paper introduces a...

Within the product life cycle, manufacturing processes are steps through which raw materials are assembled and transformed into final products. When different applications share information concerning manufacturing processes, the lack of information interoperability is a challenging issue that emerges during the manufacturing process implementation...

Condition monitoring is performed to identify the functioning state of a machine or a mechanical system. It is an important task by which the machine or mechanical system deterioration tendency and the location of a failure can be detected. In recent years, ontologies have shown promising results to enhance knowledge sharing in condition monitoring...

Within manufacturing processes, anomalies such as machinery faults and failures may lead to the outage situation of production lines. The outage of production lines is detrimental for the availability of production systems and may cause severe economic loss. To avoid the economic loss that may be caused by the outage situation, the prediction of an...

Cybersecurity becomes ever more important since the industry is transforming towards an Industrial Internet of Things (IIoT). Essential parts of the whole security concept are securing the communication between clients and servers on different business layers, like plant floor network and enterprise network, separation of information model and auth...

Condition monitoring is performed to identify the functioning state of a machine or a mechanical system. It is an important task by which the machine or mechanical system deterioration tendency and the location of a failure can be detected. In recent years, ontologies have shown promising results to enhance knowledge sharing in condition monitoring...

The popularity and open nature of cloud services has made them an attractive platform for cyber attacks. The increase in activities of attackers through Distributed Reflection Denial of service (DRDoS) attack is particularly alarming. There have been many reported cases of denial of service attacks on many cloud services in recent times. Most of th...

Within the product life cycle, manufacturing processes are steps through which raw materials are assembled and transformed into final products. When different applications share information concerning manufacturing pro-cesses, the lack of information interoperability is a challenging issue that emerges during the manufacturing process implementatio...

Big data is a new economic driver for many advanced technology domains, such as autonomous driving, reusable rockets or cancer research. Generating knowledge from large amounts of data in such domains, will become increasingly important. Management and processing is done in powerful big data infras-tructures located in the cloud. Diversifying requi...

Durch die Einführung von neuen europaweiten Datenschutzregulierungen rückt der Schutz der Privatsphäre in den Mittelpunkt von Entwicklungen in IT-Systemen. Die vorliegende Arbeit stellt die zugrundeliegenden Regelungen, den theoretischen Ansatz, sowie eine technische Umsetzung für den Schutz der Privatsphäre in Ambient Assisted Living Systemen durc...

The Industrial Internet of Things is a fast-growing business with many opportunities but also security risks. For instance, a crucial risk is an attack on customer’s or company’s internal data to violate the integrity, like order information or machine configurations. In addition, an attacker could inject packets which contain harmful manufacturing...

In the manufacturing domain, machinery faults cause a company high costs. To avoid faulty conditions, the discipline of condition monitoring contributes significantly. The objective of condition monitoring is to determine the correctness of a machine, process or system. This is crucial for improving the productivity and availability of production s...

The essential prerequisite for successfully implementing Industry 4.0 is the secure and trustworthy handling of data as well as the reliable protection of cross-company communication against attacks. Confidentiality and integrity are crucial for a secure cyber-physical communication infrastructure. Using a Privilege Management Infrastructure (PMI)...

Businesses, especially SMEs, increasingly integrate cloud services in their IT infrastructure. The assurance of the correct and effective implementation of security controls is required by businesses to attenuate the loss of control that is inherently associated with using cloud services. Giving this kind of assurance, is traditionally the task of...

Mobile Software Agent has become increasingly interesting as a basic software technology in the field of Internet of Things, like Smart Cities, Smart Home, Industry 4.0, etc. since it offers dynamic adaption, autonomous actions, flexible maintenance, parallel processing, and is tolerant to network faults. In particular, it is very challenging to gu...

Cloud computing technologies have significantly changed the way in which organizations implement their information technology infrastructure. It is a new paradigm that turned the long-held promises of computing services into reality. It allows organizations to focus on their business with minimal effort placed upon building, managing and maintainin...

Cloud computing has been advancing at a feverish pace. It has become one of the most important research topics in computer science and information systems. Cloud computing offers enterprise-scale platforms in a short time frame with little effort. Thus, it delivers significant economic benefits to both commercial and public entities. Despite this,...

Virtualization at the operating system level utilizing container technologies provides reduced performance overhead over Type-1 hypervisors for HPC and also adds many possibilities to significantly improve the often demanded flexibility of such an installation. This paper discusses technologies and concepts on several layers that can be applied to...

Elasticity is one of the essential characteristics for cloud computing. The presented use case is a Software as a Service for Ambient Assisted Living that is configurable and extensible by the user. By adding or deleting functionality to the application, the environment has to support the increase or decrease of computational demand by scaling. Thi...