004 Datenverarbeitung; Informatik
Refine
Year of publication
Document Type
- Report (19) (remove)
Has Fulltext
- yes (19)
Is part of the Bibliography
- no (19)
Keywords
- Datenschutz (3)
- Computerlinguistik (2)
- Linguistische Datenverarbeitung (2)
- Mobile Telekommunikation / Electronic Commerce (2)
- Privacy (2)
- Textanalyse (2)
- Textanalyse ; Linguistische Datenverarbeitung; Computerlinguistik (2)
- Adoptionsfaktoren (1)
- Assurance (1)
- Bildnisschutz (1)
- Bluetooth-Standard (1)
- Cameras (1)
- Certification (1)
- Common Criteria (1)
- Data protection (1)
- Digital Rights Management (1)
- Digitalkamera (1)
- Elektronisches Wasserzeichen (1)
- ISO 15408 (1)
- Information Security (1)
- Informationelles Selbstbestimmungsrecht (1)
- Infrarot (1)
- Innovationsplanung (1)
- Innovationsprozess (1)
- Internationaler Datenschutz (1)
- Mehrseitige Sicherheit (1)
- Mobile Phones (1)
- Netzzusammenschaltung (1)
- Online algorithms (1)
- Paging (1)
- Persönlichkeitsrecht (1)
- Produ (1)
- Randomized algorithms (1)
- Recht am eignenen Bild (1)
- Software Engineering (1)
- Standortbezogener Dienst (1)
- TCP/IP (1)
- Telekommunikationsnetz (1)
- Telekommunikationswirtschaft (1)
- Trusted Computing (1)
- UPT (1)
- Unternehmen / Innovation (1)
- Voyeurism (1)
- Voyeurismus (1)
- Watermarking (1)
- Zertifizierung (1)
- adoption factors (1)
- attack scenarios (1)
- automotive sector (1)
- comparison (1)
- de-identification (1)
- diffusion of innovations (1)
- diffusion theory (1)
- drahtlos (1)
- empiric survey (1)
- factor analysis (1)
- location based services (1)
- mobile commerce (1)
- online privacy (1)
- online-Privatsphäre (1)
- relative termination (1)
- requirements analysis (1)
- rewriting systems (1)
- string rewriting (1)
- technischer Datenschutz (1)
- termination (1)
- wireless business model pyramid scheme multi-level (1)
Institute
- Informatik (12)
- Wirtschaftswissenschaften (5)
- Erziehungswissenschaften (1)
- Gesellschaftswissenschaften (1)
- Präsidium (1)
The aim of this study was to identify and evaluate different de-identification techniques that may be used in several mobility-related use cases. To do so, four use cases have been defined in accordance with a project partner that focused on the legal aspects of this project, as well as with the VDA/FAT working group. Each use case aims to create different legal and technical issues with regards to the data and information that are to be gathered, used and transferred in the specific scenario. Use cases should therefore differ in the type and frequency of data that is gathered as well as the level of privacy and the speed of computation that is needed for the data. Upon identifying use cases, a systematic literature review has been performed to identify suitable de-identification techniques to provide data privacy. Additionally, external databases have been considered as data that is expected to be anonymous might be reidentified through the combination of existing data with such external data.
For each case, requirements and possible attack scenarios were created to illustrate where exactly privacy-related issues could occur and how exactly such issues could impact data subjects, data processors or data controllers. Suitable de-identification techniques should be able to withstand these attack scenarios. Based on a series of additional criteria, de-identification techniques are then analyzed for each use case. Possible solutions are then discussed individually in chapters 6.1 - 6.2. It is evident that no one-size-fits-all approach to protect privacy in the mobility domain exists. While all techniques that are analyzed in detail in this report, e.g., homomorphic encryption, differential privacy, secure multiparty computation and federated learning, are able to successfully protect user privacy in certain instances, their overall effectiveness differs depending on the specifics of each use case.
We present techniques to prove termination of cycle rewriting, that is, string rewriting on cycles, which are strings in which the start and end are connected. Our main technique is to transform cycle rewriting into string rewriting and then apply state of the art techniques to prove termination of the string rewrite system. We present three such transformations, and prove for all of them that they are sound and complete. In this way not only termination of string rewriting of the transformed system implies termination of the original cycle rewrite system, a similar conclusion can be drawn for non-termination. Apart from this transformational approach, we present a uniform framework of matrix interpretations, covering most of the earlier approaches to automatically proving termination of cycle rewriting. All our techniques serve both for proving termination and relative termination. We present several experiments showing the power of our techniques.
Since Mobile Virtual Assistants are rising in popularity and come with most new smartphones out of the box and theoretical work in the field is hard to come by, a test is in order to establish the status quo of development. We did a manual test on six different Mobile Virtual Assistants in the categories Voice Recognition, Online Search, Phone Control and Natural Conversation and the results show that Siri is currently the best Mobile Virtual Assistant on the market with a success rate of 65.8% on average over all four categories.
Paging is one of the prominent problems in the field of on-line algorithms. While in the deterministic setting there exist simple and efficient strongly competitive algorithms, in the randomized setting a tradeoff between competitiveness and memory is still not settled. Bein et al. [4] conjectured that there exist strongly competitive randomized paging algorithms, using o(k) bookmarks, i.e. pages not in cache that the algorithm keeps track of. Also in [4] the first algorithm using O(k) bookmarks (2k more precisely), Equitable2, was introduced, proving in the affirmative a conjecture in [7].
We prove tighter bounds for Equitable2, showing that it requires less than k bookmarks, more precisely ≈ 0.62k. We then give a lower bound for Equitable2 showing that it cannot both be strongly competitive and use o(k) bookmarks. Nonetheless, we show that it can trade competitiveness for space. More precisely, if its competitive ratio is allowed to be (Hk + t), then it requires k/(1 + t) bookmarks.
Our main result proves the conjecture that there exist strongly competitive paging algorithms using o(k) bookmarks. We propose an algorithm, denoted Partition2, which is a variant of the Partition algorithm byMcGeoch and Sleator [13]. While classical Partition is unbounded in its space requirements, Partition2 uses θ(k/ log k) bookmarks. Furthermore, we show that this result is asymptotically tight when the forgiveness steps are deterministic.
In diesem Bericht wurde das in [Pae02] eingeführte Verfahren "GenDurchschnitt" auf die symbolischen Daten zweier Datenbanken septischer Schock-Patienten angewendet. Es wurden jeweils Generalisierungsregeln generiert, die neben einer robusten Klassifikation der Patienten in die Klassen "überlebt" und "verstorben" auch eine Interpretation der Daten ermöglichten. Ein Vergleich mit den aktuellen Verfahren A-priori und FP-Baum haben die gute Verwendbarkeit des Algorithmus belegt. Die Heuristiken führten zu Laufzeitverbesserungen. Insbesondere die Möglichkeit, die Wichtigkeit von Variablen pro Klasse zu berechnen, führte zu einer Variablenreduktion im Eingaberaum und zu der Identifikation wichtiger Items. Einige Regelbeispiele wurden für jeden Datensatz genannt. Die Frühzeitigkeit von Regeln lieferte für die beiden Datenbanken ein unterschiedliches Ergebnis: Bei den ASK-Daten treten die Regeln für die Klasse "verstorben" früher als die der Klasse "überlebt" auf; bei den MEDAN-Klinikdaten ist es umgekehrt. Eine Erklärung hierfür könnte sein, dass es sich im Vergleich zu den MEDAN-Klinikdaten bei den ASK-Daten um ein Patientenkollektiv mit einer anderen, speziellen Patientencharakteristik handelt. Anhand der Ähnlichkeit der Regeln konnten für den Anwender eine überschaubare Anzahl zuverlässiger Regeln ausgegeben werden, die möglichst unähnlich zueinander sind und somit für einen Arzt in ihrer Gesamtheit interessant sind. Assoziationsregeln und FP-Baum-Regeln erzeugen zwar kürzere Regeln, die aber zu zahlreich und nicht hinreichend sind (vgl. [Pae02, Abschnitt 4]). Zusätzlich zu der Analyse der symbolischen Daten ist auch die Analyse der metrischen MEDAN-Klinikdaten der septischen Schock-Patienten interessant. Ebenfalls ist eine Kombination der Analysen der metrischen und symbolischen Daten sinnvoll. Solche Analysen wurden ebenfalls durchgeführt; die Ergebnisse dieser Analysen werden an anderer Stelle präsentiert werden. Weitere Anwendungen der Generalisierungsregeln sind denkbar. Auch eine Verbesserung des theoretischen Fundaments (vgl. [Pae02]) erscheint sinnvoll, da erst das Zusammenspiel theoretischer und praktischer Anstrengungen zum Ziel führt.
For the efficient management of large image databases, the automated characterization of images and the usage of that characterization for searching and ordering tasks is highly desirable. The purpose of the project SEMACODE is to combine the still unsolved problem of content-oriented characterization of images with scale-invariant object recognition and modelbased compression methods. To achieve this goal, existing techniques as well as new concepts related to pattern matching, image encoding, and image compression are examined. The resulting methods are integrated in a common framework with the aid of a content-oriented conception. For the application, an image database at the library of the university of Frankfurt/Main (StUB; about 60000 images), the required operations are developed. The search and query interfaces are defined in close cooperation with the StUB project “Digitized Colonial Picture Library”. This report describes the fundamentals and first results of the image encoding and object recognition algorithms developed within the scope of the project.
The prevention of credit card fraud is an important application for prediction techniques. One major obstacle for using neural network training techniques is the high necessary diagnostic quality: Since only one financial transaction of a thousand is invalid no prediction success less than 99.9% is acceptable. Due to these credit card transaction proportions complete new concepts had to be developed and tested on real credit card data. This paper shows how advanced data mining techniques and neural network algorithm can be combined successfully to obtain a high fraud coverage combined with a low false alarm rate.
This paper documents the experiences of assurance evaluation during the early stage of a large software development project. This project researches, contracts and integrates privacy-respecting software to business environments. While assurance evaluation with ISO 15408 Common Criteria (CC) within the certification schemes is done after a system has been completed, our approach executes evaluation during the early phases of the software life cycle. The promise is to increase quality and to reduce testing and fault removal costs for later phases of the development process. First results from the still-ongoing project suggests that the Common Criteria can define a framework for assurance evaluation in ongoing development projects.