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Microservice Architectures (MSA) structure applications as a collection of loosely coupled services that implement business capabilities. The key advantages of MSA include inherent support for continuous deployment of large complex applications, agility and enhanced productivity. However, studies indicate that most MSA are homogeneous, and introduce shared vulnerabilites, thus vulnerable to multi-step attacks, which are economics-of-scale incentives to attackers. In this paper, we address the issue of shared vulnerabilities in microservices with a novel solution based on the concept of Moving Target Defenses (MTD). Our mechanism works by performing risk analysis against microservices to detect and prioritize vulnerabilities. Thereafter, security risk-oriented software diversification is employed, guided by a defined diversification index. The diversification is performed at runtime, leveraging both model and template based automatic code generation techniques to automatically transform programming languages and container images of the microservices. Consequently, the microservices attack surfaces are altered thereby introducing uncertainty for attackers while reducing the attackability of the microservices. Our experiments demonstrate the efficiency of our solution, with an average success rate of over 70% attack surface randomization.
Resource constrained smart micro-grid architectures describe a class of smart micro-grid architectures that handle communications operations over a lossy network and depend on a distributed collection of power generation and storage units. Disadvantaged communities with no or intermittent access to national power networks can benefit from such a micro-grid model by using low cost communication devices to coordinate the power generation, consumption, and storage. Furthermore, this solution is both cost-effective and environmentally-friendly. One model for such micro-grids, is for users to agree to coordinate a power sharing scheme in which individual generator owners sell excess unused power to users wanting access to power. Since the micro-grid relies on distributed renewable energy generation sources which are variable and only partly predictable, coordinating micro-grid operations with distributed algorithms is necessity for grid stability. Grid stability is crucial in retaining user trust in the dependability of the micro-grid, and user participation in the power sharing scheme, because user withdrawals can cause the grid to breakdown which is undesirable. In this chapter, we present a distributed architecture for fair power distribution and billing on microgrids. The architecture is designed to operate efficiently over a lossy communication network, which is an advantage for disadvantaged communities. We build on the architecture to discuss grid coordination notably how tasks such as metering, power resource allocation, forecasting, and scheduling can be handled. All four tasks are managed by a feedback control loop that monitors the performance and behaviour of the micro-grid, and based on historical data makes decisions to ensure the smooth operation of the grid. Finally, since lossy networks are undependable, differentiating system failures from adversarial manipulations is an important consideration for grid stability. We therefore provide a characterisation of potential adversarial models and discuss possible mitigation measures.
ASEDS
(2018)
The Massive adoption of social media has provided new ways for individuals to express their opinion and emotion online. In 2016, Facebook introduced a new reactions feature that allows users to express their psychological emotions regarding published contents using so-called Facebook reactions. In this paper, a framework for predicting the distribution of Facebook post reactions is presented. For this purpose, we collected an enormous amount of Facebook posts associated with their reactions labels using the proposed scalable Facebook crawler. The training process utilizes 3 million labeled posts for more than 64,000 unique Facebook pages from diverse categories. The evaluation on standard benchmarks using the proposed features shows promising results compared to previous research. The final model is able to predict the reaction distribution on Facebook posts with a recall score of 0.90 for "Joy" emotion.
The classification of vulnerabilities is a fundamental step to derive formal attributes that allow a deeper analysis. Therefore, it is required that this classification has to be performed timely and accurate. Since the current situation demands a manual interaction in the classification process, the timely processing becomes a serious issue. Thus, we propose an automated alternative to the manual classification, because the amount of identified vulnerabilities per day cannot be processed manually anymore. We implemented two different approaches that are able to automatically classify vulnerabilities based on the vulnerability description. We evaluated our approaches, which use Neural Networks and the Naive Bayes methods respectively, on the base of publicly known vulnerabilities.
Blockchain
(2018)
The term blockchain has recently become a buzzword, but only few know what exactly lies behind this approach. According to a survey, issued in the first quarter of 2017, the term is only known by 35 percent of German medium-sized enterprise representatives. However, the blockchain technology is very interesting for the mass media because of its rapid development and global capturing of different markets.
For example, many see blockchain technology either as an all-purpose weapon— which only a few have access to—or as a hacker technology for secret deals in the darknet. The innovation of blockchain technology is found in its successful combination of already existing approaches: such as decentralized networks, cryptography, and consensus models. This innovative concept makes it possible to exchange values in a decentralized system. At the same time, there is no requirement for trust between its nodes (e.g. users).
With this study the Hasso Plattner Institute would like to help readers form their own opinion about blockchain technology, and to distinguish between truly innovative properties and hype.
The authors of the present study analyze the positive and negative properties of the blockchain architecture and suggest possible solutions, which can contribute to the efficient use of the technology. We recommend that every company define a clear target for the intended application, which is achievable with a reasonable cost-benefit ration, before deciding on this technology. Both the possibilities and the limitations of blockchain technology need to be considered. The relevant steps that must be taken in this respect are summarized /summed up for the reader in this study.
Furthermore, this study elaborates on urgent problems such as the scalability of the blockchain, appropriate consensus algorithm and security, including various types of possible attacks and their countermeasures. New blockchains, for example, run the risk of reducing security, as changes to existing technology can lead to lacks in the security and failures.
After discussing the innovative properties and problems of the blockchain technology, its implementation is discussed. There are a lot of implementation opportunities for companies available who are interested in the blockchain realization. The numerous applications have either their own blockchain as a basis or use existing and widespread blockchain systems. Various consortia and projects offer "blockchain-as-a-serviceänd help other companies to develop, test and deploy their own applications.
This study gives a detailed overview of diverse relevant applications and projects in the field of blockchain technology. As this technology is still a relatively young and fast developing approach, it still lacks uniform standards to allow the cooperation of different systems and to which all developers can adhere. Currently, developers are orienting themselves to Bitcoin, Ethereum and Hyperledger systems, which serve as the basis for many other blockchain applications.
The goal is to give readers a clear and comprehensive overview of blockchain technology and its capabilities.
This Research-to-Practice paper examines the practical application of various forms of collaborative learning in MOOCs. Since 2012, about 60 MOOCs in the wider context of Information Technology and Computer Science have been conducted on our self-developed MOOC platform. The platform is also used by several customers, who either run their own platform instances or use our white label platform. We, as well as some of our partners, have experimented with different approaches in collaborative learning in these courses. Based on the results of early experiments, surveys amongst our participants, and requests by our business partners we have integrated several options to offer forms of collaborative learning to the system. The results of our experiments are directly fed back to the platform development, allowing to fine tune existing and to add new tools where necessary. In the paper at hand, we discuss the benefits and disadvantages of decisions in the design of a MOOC with regard to the various forms of collaborative learning. While the focus of the paper at hand is on forms of large group collaboration, two types of small group collaboration on our platforms are briefly introduced.
In the course of patient treatments, psychotherapists aim to meet the challenges of being both a trusted, knowledgeable conversation partner and a diligent documentalist. We are developing the digital whiteboard system Tele-Board MED (TBM), which allows the therapist to take digital notes during the session together with the patient. This study investigates what therapists are experiencing when they document with TBM in patient sessions for the first time and whether this documentation saves them time when writing official clinical documents. As the core of this study, we conducted four anamnesis session dialogues with behavior psychotherapists and volunteers acting in the role of patients. Following a mixed-method approach, the data collection and analysis involved self-reported emotion samples, user experience curves and questionnaires. We found that even in the very first patient session with TBM, therapists come to feel comfortable, develop a positive feeling and can concentrate on the patient. Regarding administrative documentation tasks, we found with the TBM report generation feature the therapists save 60% of the time they normally spend on writing case reports to the health insurance.
Design thinking is a well-established practical and educational approach to fostering high-level creativity and innovation, which has been refined since the 1950s with the participation of experts like Joy Paul Guilford and Abraham Maslow. Through real-world projects, trainees learn to optimize their creative outcomes by developing and practicing creative cognition and metacognition. This paper provides a holistic perspective on creativity, enabling the formulation of a comprehensive theoretical framework of creative metacognition. It focuses on the design thinking approach to creativity and explores the role of metacognition in four areas of creativity expertise: Products, Processes, People, and Places. The analysis includes task-outcome relationships (product metacognition), the monitoring of strategy effectiveness (process metacognition), an understanding of individual or group strengths and weaknesses (people metacognition), and an examination of the mutual impact between environments and creativity (place metacognition). It also reviews measures taken in design thinking education, including a distribution of cognition and metacognition, to support students in their development of creative mastery. On these grounds, we propose extended methods for measuring creative metacognition with the goal of enhancing comprehensive assessments of the phenomenon. Proposed methodological advancements include accuracy sub-scales, experimental tasks where examinees explore problem and solution spaces, combinations of naturalistic observations with capability testing, as well as physiological assessments as indirect measures of creative metacognition.
Social networking sites (SNS) are a rich source of latent information about individual characteristics. Crawling and analyzing this content provides a new approach for enterprises to personalize services and put forward product recommendations. In the past few years, commercial brands made a gradual appearance on social media platforms for advertisement, customers support and public relation purposes and by now it became a necessity throughout all branches. This online identity can be represented as a brand personality that reflects how a brand is perceived by its customers. We exploited recent research in text analysis and personality detection to build an automatic brand personality prediction model on top of the (Five-Factor Model) and (Linguistic Inquiry and Word Count) features extracted from publicly available benchmarks. Predictive evaluation on brands' accounts reveals that Facebook platform provides a slight advantage over Twitter platform in offering more self-disclosure for users' to express their emotions especially their demographic and psychological traits. Results also confirm the wider perspective that the same social media account carry a quite similar and comparable personality scores over different social media platforms. For evaluating our prediction results on actual brands' accounts, we crawled the Facebook API and Twitter API respectively for 100k posts from the most valuable brands' pages in the USA and we visualize exemplars of comparison results and present suggestions for future directions.