ITC/USA 2015 Conference Proceedings / The Fifty-First Annual International Telemetering Conference and Technical Exhibition / October 26-29, 2015 / Bally's Hotel & Convention Center, Las Vegas, NV / Data security is becoming increasingly important in all areas of storage. The news services frequently have stories about lost or stolen storage devices and the panic it causes. Data security in an SSD usually involves two components: data protection and data elimination. Data protection includes passwords to protect against unauthorized access and encryption to protect against recovering data from the flash chips. Data elimination includes erasing the encryption key and erasing the flash. Telemetry applications frequently add requirements such as write protection, external erase triggers, and overwriting the flash after the erase. This presentation will review these data security features.

published_or_final_version / abstract / Computer Science / Doctoral / Doctor of Philosophy

Idag regleras personuppgiftsbehandlingar i Sverige främst genom Dataskyddsdirektivet och personuppgiftslagen. I takt med den omfattande användningen och utvecklingen av internet, av såväl privatpersoner som företag, krävs en uppdatering kring dataskydd för personuppgifter.Personuppgifter lagras hos företag i enorma mängder och skyddet för den personliga integriteten anses inte längre vara lika stort, varför en Dataskyddsförordning har utformats som en gemensam reglering i EU. Uppsatsen är en framläggning av hur privata bolag påverkas av de kommande förändringarna med huvudfokus på ansvar, roller, förberedelser, planering samt vilka sanktioner bolag står inför om reglerna inte efterlevs. I Dataskyddsförordningen utnämns ett flertal befattningar med skilda roller inomorganisationen. Dessa är personuppgiftsansvarig, personuppgiftsbiträde samtdataskyddsombud. I och med den nya regleringen har varje befattning ett utökat ansvareftersom att reglerna skärps. Med Dataskyddsförordningen kommer nya regler som kräver förberedelser samt planering för att artiklarna ska kunna efterlevas den dag ikraftträdandet sker. Exempel här är incidentrapportering som kräver tydliga rutiner för att verksamheten ska fungera. För att organisationer ska förstå allvaret, i och med de höga sanktionsavgifterna bolaget kan påföras, krävs att ledningen tar implementeringen på allvar och upprättar en analys samt en genomtänkt plan för arbetet. Det kan konstateras att Dataskyddsförordningen leder till ett omfattande arbete för varje organisation där rollerna behöver tydliggöras, i vissa fall behöver nya roller utses. Samtidigtbehöver kompetens finnas och det krävs stor planering i varje verksamhet för att reglerna ska efterlevas. Implementeringsarbetet behöver sättas igång direkt för att allt ska vara i sin ordning till den dag Dataskyddsförordningen träder i kraft. Dataskyddsförordningen är ett komplext regelverk. Osäkerheter kring Dataskyddsförordningens reglering kommer dock troligtvis att minska när Europeiska dataskyddsstyrelsen och Datainspektionen utfärdar fler tydliggöranden samt genom svensk utredning. Övergripande i hela bolaget gäller samma regler med vissa undantag, men viktigt är att anpassa och föra implementeringsarbetet utifrån den egna specifika verksamheten.

Open dissemination of the Trusted Computing Exemplar (TCX) project is needed. This dissemination must include methods to provide secure web access to project material, integrity verification of data, and group-based access controls. Because previously developed dissemination systems do not meet these requirements, a hybrid web-based dissemination system is necessary. The development of the TCX Dissemination System requirements involved the analysis of assumptions, threats, policies, and security objectives for the system and its environment based on the Common Criteria methodology. The requirements yielded a design specification that included a dissemination application that uses XML capabilities for redaction and preparation of releasable materials. This led to the creation of an initial implementation to satisfy a subset of the TCX dissemination requirements. Future work was identified for a subsequent implementation that fulfills additional project requirements. The complete implementation of the dissemination environment described in this thesis will provide a seamless dissemination interface for the TCX project. The Dissemination System provides an example of how controlled information can be organized and made available on the web. When combined with TCX project results, it supports the assured information sharing objectives of the Department of Defense Global Information Grid vision. / US Navy (USN) author.

Protection of personal data in the course of rendering health care SUMMARY Medical treatment is based on trust. Patients coming to the medical facility often share details about their personal lives that could potentially embarrass or dishonour them and eventually discourage them from getting medical treatment at all. That is why patients seeking medical help need to know that those to whom they confide in are willing to keep the information private and discreet. This thesis will address the protection of personal data in the healthcare area and its main purpose is to provide complex analysis of the relevant legal framework, especially in the light of the recently passed legislation. Protection of personal data in the healthcare are is governed by two pieces of legislation - The Data Protection Act and The Healthcare Act. These statutes present main instruments by which the protection of patients' information is provided. The first part of the thesis examines the general principles of the data protection as they are outlined by the Data Protection Act. It also looks at the key terms of data protection, such as personal data, sensitive data, data subjects and processing and examines the role of the Data Protection Office. Second part the thesis deals with the duty of confidentiality and its personal,...

No description available.

Ziel der vorliegenden Arbeit ist es, die historische Konstruktion des Datenschutzproblems, des Datenschutzes als seiner (abstrakten) Lösung sowie die Architektur seiner rechtlichen Implementation aufzudecken und einer kritischen Revision aus informatischer Sicht zu unterziehen, um daraus Folgerungen für die Technikgestaltung zu ziehen. Die Arbeit legt offen, welches Verständnis vom Menschen und von der Gesellschaft, von Organisationen, von der Informationstechnik und von der Informationsverarbeitung, welche informatischen, informationswissenschaftlichen, soziologischen und rechtswissenschaftlichen Konzepte, Denkschulen und Theoriegebäude und welche wissenschaftlichen und vorwissenschaftlichen Annahmen und Prämissen der Analyse des Datenschutzproblems zugrunde liegen und wie sie darüber hinaus die spezifische Lösung des Datenschutzproblems – den Datenschutz – gespeist haben. Auf der Basis einer informatisch fundierten Kritik zieht die Arbeit den Schluss, dass der Datenschutz als Lösung des durch die Industrialisierung der gesellschaftlichen Informationsverarbeitung erzeugten Datenmachtproblems neu abgeleitet werden muss, und legt dafür ein dem Stand der wissenschaftlichen Debatte entsprechendes, abstraktes – und damit jeweils noch anwendungsbereichsspezifisch zu konkretisierendes – Datenschutz-Angreifermodell, ein analytisches Raster für eine darauf aufbauende Bedrohungsanalyse sowie einen prozeduralen Operationalisierungsansatz, der die Vorgehensweise und die jeweils zu analysierenden oder zu prüfenden inhaltlichen Fragen deutlich werden lässt, vor. Abschließend zieht die Arbeit Folgerungen für die Gestaltung datenschutzfreundlicher – und dabei nicht notwendig nur datenschutzrechtskonformer – informationstechnischer Systeme. / The aim of this thesis is to uncover the historical construction of the data protection problem, of data protection as its (abstract) solution, as well as the architecture of its legal implementation, in order to critically assess this construction and to draw conclusions for the design of ICT systems. The thesis reveals which concepts of humankind and society, organizations, information technology and information processing, which informatics, information science, sociological and jurisprudential concepts, schools of thought and theories, and which scientific and pre-scientific assumptions and premises underlie the analysis of the data protection problem, and how they have influenced the specific solution of this problem. Based on a critical assessment of this construction the thesis concludes that data protection must be re-derived as a solution for the information power problem, which is generated by the industrialization of social information processing, and presents an abstract, state-of-the-art data protection attacker model, an analytical framework for a data protection impact assessment as well as a procedural operationalization approach illustrating the sequence as well as the substantive issues to be examined and addressed in this process. The thesis then draws conclusions for the design of data protection friendly—and not necessarily just legally compliant—ICT systems.

The Internet and computer networks have become an important part of our organizations and everyday life. With the increase in our dependence on computers and communication networks, malicious activities have become increasingly prevalent. Network attacks are an important problem in today’s communication environments. The network traffic must be monitored and analyzed to detect malicious activities and attacks to ensure reliable functionality of the networks and security of users’ information. Recently, machine learning techniques have been applied toward the detection of network attacks. Machine learning models are able to extract similarities and patterns in the network traffic. Unlike signature based methods, there is no need for manual analyses to extract attack patterns. Applying machine learning algorithms can automatically build predictive models for the detection of network attacks. This dissertation reports an empirical analysis of the usage of machine learning methods for the detection of network attacks. For this purpose, we study the detection of three common attacks in computer networks: SSH brute force, Man In The Middle (MITM) and application layer Distributed Denial of Service (DDoS) attacks. Using outdated and non-representative benchmark data, such as the DARPA dataset, in the intrusion detection domain, has caused a practical gap between building detection models and their actual deployment in a real computer network. To alleviate this limitation, we collect representative network data from a real production network for each attack type. Our analysis of each attack includes a detailed study of the usage of machine learning methods for its detection. This includes the motivation behind the proposed machine learning based detection approach, the data collection process, feature engineering, building predictive models and evaluating their performance. We also investigate the application of feature selection in building detection models for network attacks. Overall, this dissertation presents a thorough analysis on how machine learning techniques can be used to detect network attacks. We not only study a broad range of network attacks, but also study the application of different machine learning methods including classification, anomaly detection and feature selection for their detection at the host level and the network level. / Includes bibliography. / Dissertation (Ph.D.)--Florida Atlantic University, 2017. / FAU Electronic Theses and Dissertations Collection

Li, Jiexing. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2008. / Includes bibliographical references (leaves [105]-110). / Abstracts in English and Chinese. / Abstract --- p.i / Acknowledgement --- p.iv / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Problem Statement --- p.1 / Chapter 1.2 --- Contributions --- p.3 / Chapter 1.3 --- Thesis Organization --- p.5 / Chapter 2 --- Background Study --- p.7 / Chapter 2.1 --- Generalization Algorithms --- p.7 / Chapter 2.2 --- Privacy Principles --- p.10 / Chapter 2.3 --- Other Related Research --- p.11 / Chapter 3 --- Anti-Corruption Privacy Preserving Publication --- p.13 / Chapter 3.1 --- Motivation --- p.13 / Chapter 3.2 --- Problem Settings --- p.14 / Chapter 3.3 --- Defects of Generalization --- p.18 / Chapter 3.4 --- Perturbed Generalization --- p.23 / Chapter 3.5 --- Modeling Privacy Attacks --- p.26 / Chapter 3.5.1 --- Corruption-Aided Linking Attacks --- p.26 / Chapter 3.5.2 --- Posterior Confidence Derivation --- p.28 / Chapter 3.6 --- Formal Results --- p.30 / Chapter 3.7 --- Experiments --- p.34 / Chapter 3.8 --- Summary --- p.37 / Chapter 4 --- Preservation of Proximity Privacy --- p.39 / Chapter 4.1 --- Motivation --- p.39 / Chapter 4.2 --- Formalization --- p.40 / Chapter 4.2.1 --- Privacy Attacks --- p.41 / Chapter 4.2.2 --- "(ε, m)-Anonymity" --- p.42 / Chapter 4.3 --- Inadequacy of the Existing Methods --- p.44 / Chapter 4.3.1 --- Inadequacy of Generalization Principles --- p.45 / Chapter 4.3.2 --- Inadequacy of Perturbation --- p.49 / Chapter 4.4 --- "Characteristics of (Epsilon, m) Anonymity" --- p.51 / Chapter 4.4.1 --- A Reduction --- p.51 / Chapter 4.4.2 --- Achievable Range of m Given e1and e2 --- p.53 / Chapter 4.4.3 --- Achievable e1 and e2 Given m --- p.57 / Chapter 4.4.4 --- Selecting the Parameters --- p.60 / Chapter 4.5 --- Generalization Algorithm --- p.61 / Chapter 4.5.1 --- Non-Monotonicity and Predictability --- p.61 / Chapter 4.5.2 --- The Algorithm --- p.63 / Chapter 4.6 --- Experiments --- p.65 / Chapter 4.7 --- Summary --- p.70 / Chapter 5 --- Privacy Preserving Publication for Multiple Users --- p.71 / Chapter 5.1 --- Motivation --- p.71 / Chapter 5.2 --- Problem Definition --- p.74 / Chapter 5.2.1 --- K-Anonymity --- p.75 / Chapter 5.2.2 --- An Observation --- p.76 / Chapter 5.3 --- The Butterfly Method --- p.78 / Chapter 5.3.1 --- The Butterfly Structure --- p.78 / Chapter 5.3.2 --- Anonymization Algorithm --- p.83 / Chapter 5.4 --- Extensions --- p.89 / Chapter 5.4.1 --- Handling More Than Two QIDs --- p.89 / Chapter 5.4.2 --- Handling Collusion --- p.91 / Chapter 5.5 --- Experiments --- p.93 / Chapter 5.6 --- Summary --- p.101 / Chapter 6 --- Conclusions and Future Work --- p.102 / Chapter A --- List of Publications --- p.104 / Bibliography --- p.105

Contemporary computers attempt to understand a user's actions and preferences in order to make decisions that better serve the user. In pursuit of this goal, computers can make observations that range from simple pattern recognition to listening in on conversations without the device being intentionally active. While these developments are incredibly useful for customization, the inherent security risks involving personal data are not always worth it. This thesis attempts to tackle one issue in this domain, computer usage identification, and presents a solution that identifies high-level usage of a system at any given moment without looking into any personal data. This solution, what I call "knowing without knowing," gives the computer just enough information to better serve the user without knowing any data that compromises privacy. With prediction accuracy at 99% and system overhead below 0.5%, this solution is not only reliable but is also scalable, giving valuable information that will lead to newer, less invasive solutions in the future.