Emerging research directions in computer science : contributions from the young informatics faculty in Karlsruhe

In order to build better human-friendly human-computer interfaces, such interfaces need to be enabled with capabilities to perceive the user, his location, identity, activities and in particular his interaction with others and the machine. Only with these perception capabilities can smart systems ( for example human-friendly robots or smart environments) become posssible. In my research I\u27m thus focusing on the development of novel techniques for the visual perception of humans and their activities, in order to facilitate perceptive multimodal interfaces, humanoid robots and smart environments. My work includes research on person tracking, person identication, recognition of pointing gestures, estimation of head orientation and focus of attention, as well as audio-visual scene and activity analysis. Application areas are humanfriendly humanoid robots, smart environments, content-based image and video analysis, as well as safety- and security-related applications. This article gives a brief overview of my ongoing research activities in these areas

Blockchain-based data privacy management with Nudge theory in open banking

Open banking brings both opportunities and challenges to banks all over the world especially in data management. A blockchain as a continuously growing list of records managed by a peer-to-peer network is widely used in various application scenarios; and it is commonly agreed that the blockchain technology can improve the protection of financial data privacy. However, current blockchain technology still poses some challenges in fully meeting the needs of financial data privacy protection. In order to address the existing problems, this paper proposes a new data privacy management framework based on the blockchain technology for the financial sector. The framework consists of three components: (1) a data privacy classification method according to the characteristics of financial data; (2) a new collaborative-filtering-based model; and (3) a data disclosure confirmation scheme for customer strategies based on the Nudge Theory. We implement a prototype and propose a set of algorithms for this framework. The framework is validated through field experiments and laboratory experiments. © 2019 Elsevier B.V

Blockchain-Based Water-Energy Transactive Management with Spatial-Temporal Uncertainties

Water resources are vital to the energy conversion process but few efforts have been devoted to the joint optimization problem which is fundamentally critical to the water-energy nexus for small-scale or remote energy systems (e.g., energy hubs). Traditional water and energy trading mechanisms depend on centralized authorities and cannot preserve security and privacy effectively. Also, their transaction process cannot be verified and is subject to easy tampering and frequent exposures to cyberattacks, forgery, and network failures. Toward that end, water-energy hubs (WEHs) offers a promising way to analyse water-energy nexus for greater resource utilization efficiency. We propose a two-stage blockchain-based transactive management method for multiple, interconnected WEHs. Our method considers peer-topeer (P2P) trading and demand response, and leverages blockchain to create a secure trading environment. It features auditing and resource transaction record management via system aggregators enabled by a consortium blockchain, and entails spatial-temporal distributionally robust optimization (DRO) for renewable generation and load uncertainties. A spatial-temporal ambiguity set is incorporated in DRO to characterize the spatial-temporal dependencies of the uncertainties in distributed renewable generation and load demand. We conduct a simulation-based evaluation that includes robust optimization and the moment-based DRO as benchmarks. The results reveal that our method is consistently more effective than both benchmarks. Key findings include i) our method reduces conservativeness with lower WEH trading and operation costs, and achieves important performance improvements by up to 6.1%; and ii) our method is efficient and requires 18.7% less computational time than the moment-based DRO. Overall, this study contributes to the extant literature by proposing a novel two-stage blockchain-based WEH transaction method, developing a realistic spatialtemporal ambiguity set to effectively hedge against the uncertainties for distributed renewable generation and load demand, and producing empirical evidence suggesting its greater effectiveness and values than several prevalent methods.</p

Blockchain-Based Water-Energy Transactive Management with Spatial-Temporal Uncertainties

Water resources are vital to the energy conversion process but few efforts have been devoted to the joint optimization problem which is fundamentally critical to the water-energy nexus for small-scale or remote energy systems (e.g., energy hubs). Traditional water and energy trading mechanisms depend on centralized authorities and cannot preserve security and privacy effectively. Also, their transaction process cannot be verified and is subject to easy tampering and frequent exposures to cyberattacks, forgery, and network failures. Toward that end, water-energy hubs (WEHs) offers a promising way to analyse water-energy nexus for greater resource utilization efficiency. We propose a two-stage blockchain-based transactive management method for multiple, interconnected WEHs. Our method considers peer-topeer (P2P) trading and demand response, and leverages blockchain to create a secure trading environment. It features auditing and resource transaction record management via system aggregators enabled by a consortium blockchain, and entails spatial-temporal distributionally robust optimization (DRO) for renewable generation and load uncertainties. A spatial-temporal ambiguity set is incorporated in DRO to characterize the spatial-temporal dependencies of the uncertainties in distributed renewable generation and load demand. We conduct a simulation-based evaluation that includes robust optimization and the moment-based DRO as benchmarks. The results reveal that our method is consistently more effective than both benchmarks. Key findings include i) our method reduces conservativeness with lower WEH trading and operation costs, and achieves important performance improvements by up to 6.1%; and ii) our method is efficient and requires 18.7% less computational time than the moment-based DRO. Overall, this study contributes to the extant literature by proposing a novel two-stage blockchain-based WEH transaction method, developing a realistic spatialtemporal ambiguity set to effectively hedge against the uncertainties for distributed renewable generation and load demand, and producing empirical evidence suggesting its greater effectiveness and values than several prevalent methods.</p

A Decentralized Trust Management System for Intelligent Transportation Environments

Commercialized 5G technology will provide reliable and efficient connectivity of motor vehicles that could support the dissemination of information under an intelligent transportation system. However, such service still suffers from risks or threats due to malicious content producers. The traditional public key infrastructure (PKI) cannot restrain such untrusted but legitimate publishers. Therefore, a trust-based service management mechanism is required to secure information dissemination. The issue of how to achieve a trust management model becomes a key problem in the situation. This paper proposes a novel prototype of the decentralized trust management system (DTMS) based on blockchain technologies. Compared with the conventional and centralized trust management system, DTMS adopts a decentralized consensus-based trust evaluation model and a blockchain-based trust storage system, which provide a transparent evaluation procedure and irreversible storage of trust credits. Moreover, the proposed trust model improves blockchain efficiency by only allowing trusted nodes participating in the validation and consensus process. Additionally, the designed system creatively applies a trusted execution environment (TEE) to secure the trust evaluation process together with an incentive model that is used to stimulate more participation and penalize malicious behaviours. Finally, to evaluate our new design prototype, both numerical analysis and practical experiments are implemented for performance evaluation

Security and Performance Verification of Distributed Authentication and Authorization Tools

Parallel distributed systems are widely used for dealing with massive data sets and high performance computing. Securing parallel distributed systems is problematic. Centralized security tools are likely to cause bottlenecks and introduce a single point of failure. In this paper, we introduce existing distributed authentication and authorization tools. We evaluate the quality of the security tools by verifying their security and performance. For security tool verification, we use process calculus and mathematical modeling languages. Casper, Communicating Sequential Process (CSP) and Failure Divergence Refinement (FDR) to test for security vulnerabilities, Petri nets and Karp Miller trees are used to find performance issues of distributed authentication and authorization methods. Kerberos, PERMIS, and Shibboleth are evaluated. Kerberos is a ticket based distributed authentication service, PERMIS is a role and attribute based distributed authorization service, and Shibboleth is an integration solution for federated single sign-on authentication. We find no critical security and performance issues

Novel Charging and Discharging Schemes for Electric Vehicles in Smart Grids

PhD ThesisThis thesis presents smart Charging and Discharging (C&D) schemes in the smart grid that enable a decentralised scheduling with large volumes of Electric Vehicles (EV) participation. The proposed C&D schemes use di erent strategies to atten the power consumption pro le by manipulating the charging or discharging electricity quantity. The novelty of this thesis lies in: 1. A user-behaviour based smart EV charging scheme that lowers the overall peak demand with an optimised EV charging schedule. It achieves the minimal impacts on users' daily routine while satisfying EV charging demands. 2. A decentralised EV electricity exchange process matches the power demand with an adaptive blockchain-enabled C&D scheme and iceberg order execution algorithm. It demonstrates improved performance in terms of charging costs and power consumption pro le. 3. The Peer-to-Peer (P2P) electricity C&D scheme that stimulates the trading depth and energy market pro le with the best price guide. It also increases the EV users' autonomy and achieved maximal bene ts for the network peers while protecting against potential attacks. 4. A novel consensus-mechanism driven EV C&D scheme for the blockchain-based system that accommodates high volume EV scenarios and substantially reduces the power uctuation level. The theoretical and comprehensive simulations prove that the penetration of EV with the proposed schemes minimises the power uctuation level in an urban area, and also increases the resilience of the smart grid system