Refine
Year of publication
- 2018 (26) (remove)
Document Type
- Other (17)
- Article (7)
- Monograph/Edited Volume (2)
Is part of the Bibliography
- yes (26)
Keywords
- E-Learning (3)
- Security Metrics (3)
- Security Risk Assessment (3)
- ACINQ (2)
- ASIC (2)
- Australian securities exchange (2)
- BCCC (2)
- BTC (2)
- BitShares (2)
- Bitcoin Core (2)
- Blockchain Auth (2)
- Blockchain-Konsortium R3 (2)
- Blockkette (2)
- Blockstack (2)
- Blockstack ID (2)
- Blumix-Plattform (2)
- Blöcke (2)
- Byzantine Agreement (2)
- Cloud-Security (2)
- Colored Coins (2)
- DAO (2)
- DPoS (2)
- Delegated Proof-of-Stake (2)
- Distributed Proof-of-Research (2)
- E-Wallet (2)
- ECDSA (2)
- Energy (2)
- Eris (2)
- Ether (2)
- Ethereum (2)
- Federated Byzantine Agreement (2)
- FollowMyVote (2)
- Fork (2)
- Gridcoin (2)
- Hard Fork (2)
- Hashed Timelock Contracts (2)
- Identitätsmanagement (2)
- Internet der Dinge (2)
- Internet of Things (2)
- IoT (2)
- Japanese Blockchain Consortium (2)
- Japanisches Blockchain-Konsortium (2)
- Kette (2)
- Konsensalgorithmus (2)
- Konsensprotokoll (2)
- Lecture Video Archive (2)
- Lightning Network (2)
- Lock-Time-Parameter (2)
- Micropayment-Kanäle (2)
- Microsoft Azur (2)
- NASDAQ (2)
- NameID (2)
- Namecoin (2)
- Off-Chain-Transaktionen (2)
- Onename (2)
- OpenBazaar (2)
- Oracles (2)
- Orphan Block (2)
- P2P (2)
- Peer-to-Peer Netz (2)
- Peercoin (2)
- PoB (2)
- PoS (2)
- PoW (2)
- Proof-of-Burn (2)
- Proof-of-Stake (2)
- Proof-of-Work (2)
- Ripple (2)
- SCP (2)
- SHA (2)
- SPV (2)
- Schwierigkeitsgrad (2)
- Secure Configuration (2)
- Simplified Payment Verification (2)
- Skalierbarkeit der Blockchain (2)
- Slock.it (2)
- Soft Fork (2)
- Steemit (2)
- Stellar Consensus Protocol (2)
- Storj (2)
- The Bitfury Group (2)
- The DAO (2)
- Transaktion (2)
- Two-Way-Peg (2)
- Unspent Transaction Output (2)
- Verträge (2)
- Watson IoT (2)
- Zielvorgabe (2)
- Zookos Dreieck (2)
- Zookos triangle (2)
- altchain (2)
- alternative chain (2)
- atomic swap (2)
- bidirectional payment channels (2)
- bitcoins (2)
- blockchain (2)
- blockchain consortium (2)
- blockchain-übergreifend (2)
- blocks (2)
- blumix platform (2)
- chain (2)
- cloud (2)
- confirmation period (2)
- consensus algorithm (2)
- consensus protocol (2)
- contest period (2)
- contracts (2)
- cross-chain (2)
- decentralized autonomous organization (2)
- dezentrale autonome Organisation (2)
- difficulty (2)
- difficulty target (2)
- doppelter Hashwert (2)
- double hashing (2)
- federated voting (2)
- hashrate (2)
- identity management (2)
- intelligente Verträge (2)
- inter-chain (2)
- ledger assets (2)
- merged mining (2)
- merkle root (2)
- micropayment (2)
- micropayment channels (2)
- miner (2)
- mining (2)
- mining hardware (2)
- minting (2)
- nonce (2)
- off-chain transaction (2)
- peer-to-peer network (2)
- pegged sidechains (2)
- quorum slices (2)
- rootstock (2)
- scalability of blockchain (2)
- scarce tokens (2)
- sidechain (2)
- smart contracts (2)
- transaction (2)
- Algorithms (1)
- Application Container Security (1)
- Approximation algorithms (1)
- Architectures (1)
- Automated parsing (1)
- Cloud Audit (1)
- Cloud Service Provider (1)
- Collaborative learning (1)
- Data breach (1)
- Data mining (1)
- Data mining Machine learning (1)
- Data partitioning (1)
- Data profiling (1)
- Deep learning (1)
- Denial of sleep (1)
- Disadvantaged communities (1)
- Distance Learning (1)
- Distributed snapshot algorithm (1)
- E-Learning exam preparation (1)
- E-Lecture (1)
- Electrical products (1)
- Embedded Programming (1)
- Emotion Mining (1)
- Feedback control loop (1)
- Flash (1)
- Forecasting (1)
- Grid stability (1)
- HLS (1)
- HTML5 (1)
- Home appliances (1)
- Identity leak (1)
- Internet of things (1)
- LSTM (1)
- Lecture Recording (1)
- Link layer security (1)
- Load modeling (1)
- Lossy networks (1)
- Low-processing capable devices (1)
- MAC security (1)
- MOOC (1)
- MOOC Remote Lab (1)
- Machine Learning (1)
- Micro-grid networks (1)
- Microservices Security (1)
- Monitoring (1)
- Moving Target Defense (1)
- Natural Language Processing (1)
- Neural Networks (1)
- Parallel processing (1)
- Peer assessment (1)
- Power consumption characterization (1)
- Power demand (1)
- Privacy (1)
- Psychological Emotions (1)
- Resource constrained smart micro-grids (1)
- Security (1)
- Security analytics (1)
- Sensor networks (1)
- Smart Home Education (1)
- Smart micro-grids (1)
- Social Media Analysis (1)
- Team based assignment (1)
- Teamwork (1)
- Threat Models (1)
- Unified logging system (1)
- Video annotations (1)
- Vulnerability analysis (1)
- Wireless sensor networks (1)
- activities (1)
- authentication (1)
- behavior psychotherapy (1)
- behavioral (1)
- cloud monitoring (1)
- computer-mediated therapy (1)
- continuous (1)
- data integration (1)
- emotion measurement (1)
- gait (1)
- human-computer interaction (1)
- image captioning (1)
- medical documentation (1)
- multimodal representations (1)
- mutli-task learning (1)
- note-taking (1)
- security analytics (1)
- smartphone (1)
- user experience (1)
- verification (1)
In rural/remote areas, resource constrained smart micro-grid (RCSMG) architectures can provide a cost-effective power supply alternative in cases when connectivity to the national power grid is impeded by factors such as load shedding. RCSMG architectures can be designed to handle communications over a distributed lossy network in order to minimise operation costs. However, due to the unreliable nature of lossy networks communication data can be distorted by noise additions that alter the veracity of the data. In this chapter, we consider cases in which an adversary who is internal to the RCSMG, deliberately distorts communicated data to gain an unfair advantage over the RCSMG’s users. The adversary’s goal is to mask malicious data manipulations as distortions due to additive noise due to communication channel unreliability. Distinguishing malicious data distortions from benign distortions is important in ensuring trustworthiness of the RCSMG. Perturbation data anonymisation algorithms can be used to alter transmitted data to ensure that adversarial manipulation of the data reveals no information that the adversary can take advantage of. However, because existing data perturbation anonymisation algorithms operate by using additive noise to anonymise data, using these algorithms in the RCSMG context is challenging. This is due to the fact that distinguishing benign noise additions from malicious noise additions is a difficult problem. In this chapter, we present a brief survey of cases of privacy violations due to inferences drawn from observed power consumption patterns in RCSMGs centred on inference, and propose a method of mitigating these risks. The lesson here is that while RCSMGs give users more control over power management and distribution, good anonymisation is essential to protecting personal information on RCSMGs.
Detecting and recognizing text in natural scene images is a challenging, yet not completely solved task. In recent years several new systems that try to solve at least one of the two sub-tasks (text detection and text recognition) have been proposed. In this paper we present SEE, a step towards semi-supervised neural networks for scene text detection and recognition, that can be optimized end-to-end. Most existing works consist of multiple deep neural networks and several pre-processing steps. In contrast to this, we propose to use a single deep neural network, that learns to detect and recognize text from natural images, in a semi-supervised way. SEE is a network that integrates and jointly learns a spatial transformer network, which can learn to detect text regions in an image, and a text recognition network that takes the identified text regions and recognizes their textual content. We introduce the idea behind our novel approach and show its feasibility, by performing a range of experiments on standard benchmark datasets, where we achieve competitive results.
In university teaching today, it is common practice to record regular lectures and special events such as conferences and speeches. With these recordings, a large fundus of video teaching material can be created quickly and easily. Typically, lectures have a length of about one and a half hours and usually take place once or twice a week based on the credit hours. Depending on the number of lectures and other events recorded, the number of recordings available is increasing rapidly, which means that an appropriate form of provisioning is essential for the students. This is usually done in the form of lecture video platforms. In this work, we have investigated how lecture video platforms and the contained knowledge can be improved and accessed more easily by an increasing number of students. We came up with a multistep process we have applied to our own lecture video web portal that can be applied to other solutions as well.
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.
Live migration is an important feature in modern software-defined datacenters and cloud computing environments. Dynamic resource management, load balance, power saving and fault tolerance are all dependent on the live migration feature. Despite the importance of live migration, the cost of live migration cannot be ignored and may result in service availability degradation. Live migration cost includes the migration time, downtime, CPU overhead, network and power consumption. There are many research articles that discuss the problem of live migration cost with different scopes like analyzing the cost and relate it to the parameters that control it, proposing new migration algorithms that minimize the cost and also predicting the migration cost. For the best of our knowledge, most of the papers that discuss the migration cost problem focus on open source hypervisors. For the research articles focus on VMware environments, none of the published articles proposed migration time, network overhead and power consumption modeling for single and multiple VMs live migration. In this paper, we propose empirical models for the live migration time, network overhead and power consumption for single and multiple VMs migration. The proposed models are obtained using a VMware based testbed.
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)
Der Begriff Blockchain ist in letzter Zeit zu einem Schlagwort geworden, aber nur wenige wissen, was sich genau dahinter verbirgt. Laut einer Umfrage, die im ersten Quartal 2017 veröffentlicht wurde, ist der Begriff nur bei 35 Prozent der deutschen Mittelständler bekannt. Dabei ist die Blockchain-Technologie durch ihre rasante Entwicklung und die globale Eroberung unterschiedlicher Märkte für Massenmedien sehr interessant.
So sehen viele die Blockchain-Technologie entweder als eine Allzweckwaffe, zu der aber nur wenige einen Zugang haben, oder als eine Hacker-Technologie für geheime Geschäfte im Darknet. Dabei liegt die Innovation der Blockchain-Technologie in ihrer erfolgreichen Zusammensetzung bereits vorhandener Ansätze: dezentrale Netzwerke, Kryptographie, Konsensfindungsmodelle. Durch das innovative Konzept wird ein Werte-Austausch in einem dezentralen System möglich. Dabei wird kein Vertrauen zwischen dessen Knoten (z.B. Nutzer) vorausgesetzt.
Mit dieser Studie möchte das Hasso-Plattner-Institut den Lesern helfen, ihren eigenen Standpunkt zur Blockchain-Technologie zu finden und dabei dazwischen unterscheiden zu können, welche Eigenschaften wirklich innovativ und welche nichts weiter als ein Hype sind.
Die Autoren der vorliegenden Arbeit analysieren positive und negative Eigenschaften, welche die Blockchain-Architektur prägen, und stellen mögliche Anpassungs- und Lösungsvorschläge vor, die zu einem effizienten Einsatz der Technologie beitragen können. Jedem Unternehmen, bevor es sich für diese Technologie entscheidet, wird dabei empfohlen, für den geplanten Anwendungszweck zunächst ein klares Ziel zu definieren, das mit einem angemessenen Kosten-Nutzen-Verhältnis angestrebt werden kann. Dabei sind sowohl die Möglichkeiten als auch die Grenzen der Blockchain-Technologie zu beachten. Die relevanten Schritte, die es in diesem Zusammenhang zu beachten gilt, fasst die Studie für die Leser übersichtlich zusammen.
Es wird ebenso auf akute Fragestellungen wie Skalierbarkeit der Blockchain, geeigneter Konsensalgorithmus und Sicherheit eingegangen, darunter verschiedene Arten möglicher Angriffe und die entsprechenden Gegenmaßnahmen zu deren Abwehr. Neue Blockchains etwa laufen Gefahr, geringere Sicherheit zu bieten, da Änderungen an der bereits bestehenden Technologie zu Schutzlücken und Mängeln führen können.
Nach Diskussion der innovativen Eigenschaften und Probleme der Blockchain-Technologie wird auf ihre Umsetzung eingegangen. Interessierten Unternehmen stehen viele Umsetzungsmöglichkeiten zur Verfügung. Die zahlreichen Anwendungen haben entweder eine eigene Blockchain als Grundlage oder nutzen bereits bestehende und weitverbreitete Blockchain-Systeme. Zahlreiche Konsortien und Projekte bieten „Blockchain-as-a-Service“ an und unterstützen andere Unternehmen beim Entwickeln, Testen und Bereitstellen von Anwendungen.
Die Studie gibt einen detaillierten Überblick über zahlreiche relevante Einsatzbereiche und Projekte im Bereich der Blockchain-Technologie. Dadurch, dass sie noch relativ jung ist und sich schnell entwickelt, fehlen ihr noch einheitliche Standards, die Zusammenarbeit der verschiedenen Systeme erlauben und an die sich alle Entwickler halten können. Aktuell orientieren sich Entwickler an Bitcoin-, Ethereum- und Hyperledger-Systeme, diese dienen als Grundlage für viele weitere Blockchain-Anwendungen.
Ziel ist, den Lesern einen klaren und umfassenden Überblick über die Blockchain-Technologie und deren Möglichkeiten zu vermitteln.
The relevance of identity data leaks on the Internet is more present than ever. Almost every week we read about leakage of databases with more than a million users in the news. Smaller but not less dangerous leaks happen even multiple times a day. The public availability of such leaked data is a major threat to the victims, but also creates the opportunity to learn not only about security of service providers but also the behavior of users when choosing passwords. Our goal is to analyze this data and generate knowledge that can be used to increase security awareness and security, respectively. This paper presents a novel approach to the processing and analysis of a vast majority of bigger and smaller leaks. We evolved from a semi-manual to a fully automated process that requires a minimum of human interaction. Our contribution is the concept and a prototype implementation of a leak processing workflow that includes the extraction of digital identities from structured and unstructured leak-files, the identification of hash routines and a quality control to ensure leak authenticity. By making use of parallel and distributed programming, we are able to make leaks almost immediately available for analysis and notification after they have been published. Based on the data collected, this paper reveals how easy it is for criminals to collect lots of passwords, which are plain text or only weakly hashed. We publish those results and hope to increase not only security awareness of Internet users but also security on a technical level on the service provider side.
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.
Studies indicate that reliable access to power is an important enabler for economic growth. To this end, modern energy management systems have seen a shift from reliance on time-consuming manual procedures , to highly automated management , with current energy provisioning systems being run as cyber-physical systems . Operating energy grids as a cyber-physical system offers the advantage of increased reliability and dependability , but also raises issues of security and privacy. In this chapter, we provide an overview of the contents of this book showing the interrelation between the topics of the chapters in terms of smart energy provisioning. We begin by discussing the concept of smart-grids in general, proceeding to narrow our focus to smart micro-grids in particular. Lossy networks also provide an interesting framework for enabling the implementation of smart micro-grids in remote/rural areas, where deploying standard smart grids is economically and structurally infeasible. To this end, we consider an architectural design for a smart micro-grid suited to low-processing capable devices. We model malicious behaviour, and propose mitigation measures based properties to distinguish normal from malicious behaviour .