Gerhard Engelbrecht

Bio: Gerhard Engelbrecht is an academic researcher from Siemens. The author has contributed to research in topics: Smart city & Smart grid. The author has an hindex of 5, co-authored 5 publications receiving 44 citations.

Aspern smart ICT: Data analytics and privacy challenges in a smart city

Abstract: The abundance of data in the context of smart cities yields huge potential for data-driven businesses but raises unprecedented challenges on data privacy and security. Some of these challenges can be addressed merely through appropriate technical measures, while other issues can only be solved through strategic organizational decisions. In this paper, we present few cases from a real smart city project. We outline some exemplary data analytics scenarios and describe the measures that we adopt for a secure handling of data. Finally, we show how the chosen solutions impact the awareness of the public and acceptability of the project.

Reusable architectural decision models for quality-driven decision support: a case study from a smart cities software ecosystem

Abstract: Architectural design decisions and architectural knowledge are becoming relevant in the current practice of software architecture. In addition, reusable architectural knowledge has gained much importance in the industrial practice. In the process of architectural decision making, quality attributes constitute key drivers for designing software systems, therefore, it is important to document quality attributes along with the decisions captured. However, most of the current tools for management of architectural decisions focus mainly on capturing or sharing of design decisions. We propose to enrich a reusable architectural decision meta-model with quality attributes and introduce a corresponding tool. Our goal is to support software architects during decision making based on reusable decisions driven by quality attributes. Our approach was motivated by and applied in an industrial case study on a large-scale software ecosystem for smart cities, that constitute a complex and challenging system-of-systems domain. We applied our proposal in a few scenarios in the smart cities domain, in which the consideration of quality attributes is required to model reusable architectural knowledge adequately.

Data-driven ecosystems in smart cities: A living example from Seestadt Aspern

Abstract: The new data collection opportunities offered by IoT and the recent advancements in data processing infrastructure have provided a significant impulse to the development of smart cities. Although reliable data collection and analysis is a fundamental prerequisite for urban intelligence, the smartness of a smart city also depends on the ability to translate IoT data into useful and innovative services: it is important to conceive new design principles for the development of applications for smart cities and IoT. To this extent, this paper presents a simplified conceptual framework for describing smart city ecosystems based on concepts of natural ecosystems. The goal of the framework is to derive new metaphors for designing IoT applications based on the observation of communication and interaction patterns in natural ecosystems. The proposed framework is used to describe a real smart city project in Vienna, Austria.

The Role of RDF Stream Processing in an Smart City ICT Infrastructure - The Aspern Smart City Use Case

Abstract: In this paper we discuss the opportunities of adopting RDF stream processing in the context of smart cities. As a concrete example we take the Aspern Smart City Research project --- one of the largest smart city projects in Europe --- which aims at overcoming silos in smart grid and smart building domains. We present the envisioned smart ICT infrastructure and identify how RDF Stream processing can be explored in the different interactions among data sources, storage centers and applications/services.

The privacy case: Matching privacy-protection goals to human and organizational privacy concerns

Abstract: Processing smart grid data for analytics purposes brings about a series of privacy-related risks In order to allow for the most suitable mitigation strategies, reasonable privacy risks need to be addressed by taking into consideration the perspective of each smart grid stakeholder separately In this context, we use the notion of privacy concerns to reflect potential privacy risks from the perspective of different smart grid stakeholders Privacy concerns help to derive privacy goals, which we represent using the goals structuring notation Thus represented goals can more comprehensibly be addressed through technical and non-technical strategies and solutions The thread of argumentation—from concerns to goals to strategies and solutions—is presented in form of a privacy case, which is analogous to the safety case used in the automotive domain We provide an exemplar privacy case for the smart grid developed as part of the Aspern Smart City Research project

A Private and Efficient Mechanism for Data Uploading in Smart Cyber-Physical Systems

Abstract: To provide fine-grained access to different dimensions of the physical world, the data uploading in smart cyber-physical systems suffers novel challenges on both energy conservation and privacy preservation. It is always critical for participants to consume as little energy as possible for data uploading. However, simply pursuing energy efficiency may lead to extreme disclosure of private information, especially when the uploaded contents from participants are more informative than ever. In this article, we propose a novel mechanism for data uploading in smart cyber-physical systems, which considers both energy conservation and privacy preservation. The mechanism preserves privacy by concealing abnormal behaviors of participants, while still achieves an energy-efficient scheme for data uploading by introducing an acceptable number of extra contents. To derive an optimal uploading scheme is proved to be NP-hard. Accordingly, we propose a heuristic algorithm and analyze its effectiveness. The evaluation results towards a real-world dataset demonstrate that the performance of the proposed algorithm is comparable with the optimal results.

Privacy in the Smart City—Applications, Technologies, Challenges, and Solutions

Abstract: Many modern cities strive to integrate information technology into every aspect of city life to create so-called smart cities. Smart cities rely on a large number of application areas and technologies to realize complex interactions between citizens, third parties, and city departments. This overwhelming complexity is one reason why holistic privacy protection only rarely enters the picture. A lack of privacy can result in discrimination and social sorting, creating a fundamentally unequal society. To prevent this, we believe that a better understanding of smart cities and their privacy implications is needed. We therefore systematize the application areas, enabling technologies, privacy types, attackers, and data sources for the attacks, giving structure to the fuzzy term “smart city.” Based on our taxonomies, we describe existing privacy-enhancing technologies, review the state of the art in real cities around the world, and discuss promising future research directions. Our survey can serve as a reference guide, contributing to the development of privacy-friendly smart cities.

Security, Privacy and Risks Within Smart Cities: Literature Review and Development of a Smart City Interaction Framework.

Abstract: The complex and interdependent nature of smart cities raises significant political, technical, and socioeconomic challenges for designers, integrators and organisations involved in administrating these new entities. An increasing number of studies focus on the security, privacy and risks within smart cities, highlighting the threats relating to information security and challenges for smart city infrastructure in the management and processing of personal data. This study analyses many of these challenges, offers a valuable synthesis of the relevant key literature, and develops a smart city interaction framework. The study is organised around a number of key themes within smart cities research: privacy and security of mobile devices and services; smart city infrastructure, power systems, healthcare, frameworks, algorithms and protocols to improve security and privacy, operational threats for smart cities, use and adoption of smart services by citizens, use of blockchain and use of social media. This comprehensive review provides a useful perspective on many of the key issues and offers key direction for future studies. The findings of this study can provide an informative research framework and reference point for academics and practitioners.

A Survey on Biometric Authentication: Toward Secure and Privacy-Preserving Identification

Abstract: In order to overcome the difficulty of password management and improve the usability of authentication systems, biometric authentication has been widely studied and has attracted special attention in both academia and industry. Many biometric authentication systems have been researched and developed, especially for mobile devices. However, the existing biometric authentication systems still have defects. Some biological features have not been deeply investigated. The existing systems could be vulnerable to attacks, such as replay attack and suffer from user privacy intrusion, which seriously hinder their wide acceptance by end users. The literature still lacks a thorough review on the recent advances of biometric authentication for the purpose of secure and privacy-preserving identification. In this paper, we classify and thoroughly review the existing biometric authentication systems by focusing on the security and privacy solutions. We analyze the threats of biometric authentication and propose a number of criteria with regard to secure and privacy-preserving authentication. We further review the existing works of biometric authentication by analyzing their differences and summarizing the advantages and disadvantages of each based on the proposed criteria. In particular, we discuss the problems of aliveness detection and privacy protection in biometric authentication. Based on our survey, we figure out a number of open research issues and further specify a number of significant research directions that are worth special efforts in future research.

CITIESData: a smart city data management framework

Abstract: Smart city data come from heterogeneous sources including various types of the Internet of Things such as traffic, weather, pollution, noise, and portable devices. They are characterized with diverse quality issues and with different types of sensitive information. This makes data processing and publishing challenging. In this paper, we propose a framework to streamline smart city data management, including data collection, cleansing, anonymization, and publishing. The paper classifies smart city data in sensitive, quasi-sensitive, and open/public levels and then suggests different strategies to process and publish the data within these categories. The paper evaluates the framework using a real-world smart city data set, and the results verify its effectiveness and efficiency. The framework can be a generic solution to manage smart city data.