Wie die Blockchain-Technologie die Politik beeinflussen könnte und heute bereits tatsächlich beeinflusst.

Software applications become more and more dominant in our daily life and work. However, it is very difficult to provide sophisticated tools for all arising use cases. End-User Development (EUD) is a term that describes the development of applications by end users rather than professional developers. This enables them creating highly specialized solutions. End users are laypersons when it comes to building software, therefore they need appropriate tools for managing the whole development process. This includes designing, implementing and deploying applications. While there are already various tools available, we focus on a recommendation feature for graphical EUD tools, utilizing their spatial hypertext capabilities. In this paper we provide an overview of some common issues such tools are often struggling with. We explain how visually analyzing the workspace, parsing an implicit spatial hypertext and eventually presenting recommendations may tackle them. We further describe the project HEIMDALL in detail, especially the way of generating recommendations for software modules with the aim to raise users' awareness. Furthermore, we discuss the use of such a system that reaches a similar understanding of relationships between software modules as users have. Finally, we point to open issues that still need to be addressed to improve results and their presentation.

As of IEEE 802.11n, a wireless Network Interface Card (NIC) uses Channel State Information (CSI) to optimize the transmission over multiple antennas. CSI contain radio-metrics such as amplitude and phase. Due to scattering during hardware production these metrics exhibit unique properties. Since these information are transmitted unencrypted, they can be captured by a passive observer. We show that these information can be used to create a unique fingerprint of a wireless device, based on as little as 100 CSI packets per device collected with an off-the-shelf Wi-Fi card. For our proof of concept we captured data from seven smartphones including two identical models. We were able to identify more than 90% when using out-of-the-box Random Forrest (RF).

Blockchain ist derzeit ein Hype. Bekanntlich folgt nach dem Gipfel der überzogenen Erwartungen der Absturz in das Tal der Enttäuschungen. Das liegt unter anderem daran, dass bisher nur wenige der sinnvollen Anwendungsfälle auch tatsächlich praktisch umgesetzt werden konnten und viele existierende Szenarien auch mit herkömmlichen Technologien ohne Blockchain funktionieren würden. Und dennoch kann Blockchain sinnvoll eingesetzt werden, beispielsweise auf dem Katasteramt oder in einer elektronischen Patientenakte.

Various empirical studies are concerned with the success factors of the digital transformation process. However, a critical review of the literature shows that empirical studies in BtB sales management predominantly focus on company sizes as well as industries, but mostly neglect the relevance of business types. In the following paper, the results of an empirical study will be presented, which will fill the existing research gap. It will be demonstrated that the business type is having a major influence on the design of the various sales process steps as well as on the digitalization potential of the respective processes.

Industrial and Automation Control systems traditionally achieved security thanks to the use of proprietary protocols and isolation from the telecommunication networks. Nowadays, the advent of the Industrial Internet of Things poses new security challenges. In this paper, we first highlight the main security challenges that advocate for new risk assessment and security strategies. To this end, we propose a security framework and advanced tools to properly manage vulnerabilities, and to timely react to the threats. The proposed architecture fills the gap between computer science and control theoretic approaches. The physical layers connected to Industrial Control Systems are prone to disrupt when facing cyber-attacks. Considering the modules of the proposed architecture, we focus on the development of a practical framework to compare information about physical faults and cyber-attacks. This strategy is implemented in the ATENA architecture that has been designed as an innovative solution for the protection of critical assets.

In this paper, we describe a new algorithm designed to generate lexical resources in the field of sentiment analysis. For this approach, based on corpora of customer reviews, we determine words and phrases as candidates for our sentiment lexicon solely by calculating a word co-occurrence measure and by considering word frequencies. The sentiment values of every single word or phrase are derived automatically from the review titles and the associated given ratings. We consciously renounce the use of natural language processing methods in order to ensure language independency of our algorithm. Furthermore, by using exclusively statistical methods, we are able to identify rather unusual word combinations, such as idiomatic expressions. This differentiates our work from most prior approaches which concentrate on single words or word-modifier combinations. An example lexicon is generated by the use of a corpus of 1.5 million German Amazon customer reviews.