What ‘Security’, whose ‘Rights’ and which ‘Law’? : the Israeli High Court of Justice and the Israeli settlements in the occupied West Bank

Cette thèse examine l’interprétation et l’application, par l’Haute Cour d'Israël (HCJ), de principes du droit international de l’occupation et du droit international des droits de la personne dans le traitement de requêtes judiciaires formulées par des justiciables palestiniens. Elle s’intéresse plus particulièrement aux jugements rendus depuis le déclenchement de la deuxième Intifada (2000) suite à des requêtes mettant en cause la légalité des mesures adoptées par les autorités israéliennes au nom d’un besoin prétendu d’accroitre la sécurité des colonies et des colons israéliens dans le territoire occupé de la Cisjordanie. La première question sous étude concerne la mesure dans laquelle la Cour offre un recours effectif aux demandeurs palestiniens face aux violations alléguées de leurs droits internationaux par l’occupant. La recherche fait sienne la position de la HJC selon laquelle le droit de l’occupation est guidé par une logique interne tenant compte de la balance des intérêts en cause, en l’occurrence le besoin de sécurité de l’occupant, d’une part, et les droits fondamentaux de l’occupé, d’autre part. Elle considère, en outre, que cette logique se voit reflétée dans les principes normatifs constituant la base de ce corpus juridique, soit que l’occupation est par sa nature temporaire, que de l’occupation découle un rapport de fiduciaire et, finalement, que l’occupant n’acquiert point de souveraineté sur le territoire. Ainsi, la deuxième question qui est posée est de savoir si l’interprétation du droit par la Cour (HCJ) a eu pour effet de promouvoir ces principes normatifs ou, au contraire, de leur porter préjudice. La réunion de plusieurs facteurs, à savoir la durée prolongée de l’occupation de la Cisjordanie par Israël, la menace accrue à la sécurité depuis 2000 ainsi qu’une politique de colonisation israélienne active, soutenue par l’État, présentent un cas de figure unique pour vérifier l’hypothèse selon laquelle les tribunaux nationaux des États démocratiques, généralement, et ceux jouant le rôle de la plus haute instance judiciaire d’une puissance occupante, spécifiquement, parviennent à assurer la protection des droits et libertés fondamentaux et de la primauté du droit au niveau international. Le premier chapitre présente une étude, à la lumière du premier principe normatif énoncé ci-haut, des jugements rendus par la HCJ dans les dossiers contestant la légalité de la construction du mur à l’intérieur de la Cisjordanie et de la zone dite fermée (Seam Zone), ainsi que des zones de sécurité spéciales entourant les colonies. Le deuxième chapitre analyse, cette fois à la lumière du deuxième principe normatif, des jugements dans les dossiers mettant en cause des restrictions sur les déplacements imposées aux Palestiniens dans le but allégué de protéger la sécurité des colonies et/ou des colons. Le troisième chapitre jette un regard sur les jugements rendus dans les dossiers mettant en cause la légalité du tracé du mur à l’intérieur et sur le pourtour du territoire annexé de Jérusalem-Est. Les conclusions découlant de cette recherche se fondent sur des données tirées d’entrevues menées auprès d’avocats israéliens qui s’adressent régulièrement à la HCJ pour le compte de justiciables palestiniens.

B-1 Monthly Report of Medical Services Provided under Title XIX of the Social Security Act, June 2016

B-1 Medicaid Reports -- The monthly Medicaid series of eight reports provide summaries of Medicaid eligibles, recipients served, and total payments by county, category of service, and aid category. These reports may also be known as the B-1 Reports. These reports are each available as a PDF for printing or as a CSV file for data analysis. Report Report name IAMM1800-R001--Medically Needy by County - No Spenddown and With Spenddown; IAMM1800-R002--Total Medically Needy, All Other Medicaid, and Grand Total by County; IAMM2200-R002--Monthly Expenditures by Category of Service; IAMM2200-R003--Fiscal YTD Expenditures by Category of Service; IAMM3800-R001--ICF & ICF-MR Vendor Payments by County; IAMM4400-R001--Monthly Expenditures by Eligibility Program; IAMM4400-R002--Monthly Expenditures by Category of Service by Program; IAMM4600-R002--Elderly Waiver Summary by County.

B-1 Monthly Report of Medical Services Provided under Title XIX of the Social Security Act, July 2016

B-1 Medicaid Reports -- The monthly Medicaid series of eight reports provide summaries of Medicaid eligibles, recipients served, and total payments by county, category of service, and aid category. These reports may also be known as the B-1 Reports. These reports are each available as a PDF for printing or as a CSV file for data analysis. Report Report name IAMM1800-R001--Medically Needy by County - No Spenddown and With Spenddown; IAMM1800-R002--Total Medically Needy, All Other Medicaid, and Grand Total by County; IAMM2200-R002--Monthly Expenditures by Category of Service; IAMM2200-R003--Fiscal YTD Expenditures by Category of Service; IAMM3800-R001--ICF & ICF-MR Vendor Payments by County; IAMM4400-R001--Monthly Expenditures by Eligibility Program; IAMM4400-R002--Monthly Expenditures by Category of Service by Program; IAMM4600-R002--Elderly Waiver Summary by County.

B-1 Monthly Report of Medical Services Provided under Title XIX of the Social Security Act, August 2016

B-1 Medicaid Reports -- The monthly Medicaid series of eight reports provide summaries of Medicaid eligibles, recipients served, and total payments by county, category of service, and aid category. These reports may also be known as the B-1 Reports. These reports are each available as a PDF for printing or as a CSV file for data analysis. Report Report name IAMM1800-R001--Medically Needy by County - No Spenddown and With Spenddown; IAMM1800-R002--Total Medically Needy, All Other Medicaid, and Grand Total by County; IAMM2200-R002--Monthly Expenditures by Category of Service; IAMM2200-R003--Fiscal YTD Expenditures by Category of Service; IAMM3800-R001--ICF & ICF-MR Vendor Payments by County; IAMM4400-R001--Monthly Expenditures by Eligibility Program; IAMM4400-R002--Monthly Expenditures by Category of Service by Program; IAMM4600-R002--Elderly Waiver Summary by County.

A Framework for Security Transparency in Cloud Computing

Individuals and corporate users are persistently considering cloud adoption due to its significant benefits compared to traditional computing environments. The data and applications in the cloud are stored in an environment that is separated, managed and maintained externally to the organisation. Therefore, it is essential for cloud providers to demonstrate and implement adequate security practices to protect the data and processes put under their stewardship. Security transparency in the cloud is likely to become the core theme that underpins the systematic disclosure of security designs and practices that enhance customer confidence in using cloud service and deployment models. In this paper, we present a framework that enables a detailed analysis of security transparency for cloud based systems. In particular, we consider security transparency from three different levels of abstraction, i.e., conceptual, organisation and technical levels, and identify the relevant concepts within these levels. This allows us to provide an elaboration of the essential concepts at the core of transparency and analyse the means for implementing them from a technical perspective. Finally, an example from a real world migration context is given to provide a solid discussion on the applicability of the proposed framework.

B-1 Monthly Report of Medical Services Provided under Title XIX of the Social Security Act, September 2016

B-1 Medicaid Reports -- The monthly Medicaid series of eight reports provide summaries of Medicaid eligibles, recipients served, and total payments by county, category of service, and aid category. These reports may also be known as the B-1 Reports. These reports are each available as a PDF for printing or as a CSV file for data analysis. Report Report name IAMM1800-R001--Medically Needy by County - No Spenddown and With Spenddown; IAMM1800-R002--Total Medically Needy, All Other Medicaid, and Grand Total by County; IAMM2200-R002--Monthly Expenditures by Category of Service; IAMM2200-R003--Fiscal YTD Expenditures by Category of Service; IAMM3800-R001--ICF & ICF-MR Vendor Payments by County; IAMM4400-R001--Monthly Expenditures by Eligibility Program; IAMM4400-R002--Monthly Expenditures by Category of Service by Program; IAMM4600-R002--Elderly Waiver Summary by County.

A Provenance-Aware Policy Language (cProvl) and a Data Traceability Model (cProv) for the Cloud

Provenance plays a pivotal in tracing the origin of something and determining how and why something had occurred. With the emergence of the cloud and the benefits it encompasses, there has been a rapid proliferation of services being adopted by commercial and government sectors. However, trust and security concerns for such services are on an unprecedented scale. Currently, these services expose very little internal working to their customers; this can cause accountability and compliance issues especially in the event of a fault or error, customers and providers are left to point finger at each other. Provenance-based traceability provides a mean to address part of this problem by being able to capture and query events occurred in the past to understand how and why it took place. However, due to the complexity of the cloud infrastructure, the current provenance models lack the expressibility required to describe the inner-working of a cloud service. For a complete solution, a provenance-aware policy language is also required for operators and users to define policies for compliance purpose. The current policy standards do not cater for such requirement. To address these issues, in this paper we propose a provenance (traceability) model cProv, and a provenance-aware policy language (cProvl) to capture traceability data, and express policies for validating against the model. For implementation, we have extended the XACML3.0 architecture to support provenance, and provided a translator that converts cProvl policy and request into XACML type.

Pervasive eHealth services a security and privacy risk awareness survey

The human factor is often recognised as a major aspect of cyber-security research. Risk and situational perception are identified as key factors in the decision making process, often playing a lead role in the adoption of security mechanisms. However, risk awareness and perception have been poorly investigated in the field of eHealth wearables. Whilst end-users often have limited understanding of privacy and security of wearables, assessing the perceived risks and consequences will help shape the usability of future security mechanisms. This paper present a survey of the the risks and situational awareness in eHealth services. An analysis of the lack of security and privacy measures in connected health devices is described with recommendations to circumvent critical situations.

Federated architecture for biomedical data integration

The last decades have been characterized by a continuous adoption of IT solutions in the healthcare sector, which resulted in the proliferation of tremendous amounts of data over heterogeneous systems. Distinct data types are currently generated, manipulated, and stored, in the several institutions where patients are treated. The data sharing and an integrated access to this information will allow extracting relevant knowledge that can lead to better diagnostics and treatments. This thesis proposes new integration models for gathering information and extracting knowledge from multiple and heterogeneous biomedical sources. The scenario complexity led us to split the integration problem according to the data type and to the usage specificity. The first contribution is a cloud-based architecture for exchanging medical imaging services. It offers a simplified registration mechanism for providers and services, promotes remote data access, and facilitates the integration of distributed data sources. Moreover, it is compliant with international standards, ensuring the platform interoperability with current medical imaging devices. The second proposal is a sensor-based architecture for integration of electronic health records. It follows a federated integration model and aims to provide a scalable solution to search and retrieve data from multiple information systems. The last contribution is an open architecture for gathering patient-level data from disperse and heterogeneous databases. All the proposed solutions were deployed and validated in real world use cases.

B-1 Monthly Report of Medical Services Provided under Title XIX of the Social Security Act, September 2016

B-1 Medicaid Reports -- The monthly Medicaid series of eight reports provide summaries of Medicaid eligibles, recipients served, and total payments by county, category of service, and aid category. These reports may also be known as the B-1 Reports. These reports are each available as a PDF for printing or as a CSV file for data analysis. Report Report name IAMM1800-R001--Medically Needy by County - No Spenddown and With Spenddown; IAMM1800-R002--Total Medically Needy, All Other Medicaid, and Grand Total by County; IAMM2200-R002--Monthly Expenditures by Category of Service; IAMM2200-R003--Fiscal YTD Expenditures by Category of Service; IAMM3800-R001--ICF & ICF-MR Vendor Payments by County; IAMM4400-R001--Monthly Expenditures by Eligibility Program; IAMM4400-R002--Monthly Expenditures by Category of Service by Program; IAMM4600-R002--Elderly Waiver Summary by County.

Context-awareness privacy in data communications

Internet users consume online targeted advertising based on information collected about them and voluntarily share personal information in social networks. Sensor information and data from smart-phones is collected and used by applications, sometimes in unclear ways. As it happens today with smartphones, in the near future sensors will be shipped in all types of connected devices, enabling ubiquitous information gathering from the physical environment, enabling the vision of Ambient Intelligence. The value of gathered data, if not obvious, can be harnessed through data mining techniques and put to use by enabling personalized and tailored services as well as business intelligence practices, fueling the digital economy. However, the ever-expanding information gathering and use undermines the privacy conceptions of the past. Natural social practices of managing privacy in daily relations are overridden by socially-awkward communication tools, service providers struggle with security issues resulting in harmful data leaks, governments use mass surveillance techniques, the incentives of the digital economy threaten consumer privacy, and the advancement of consumergrade data-gathering technology enables new inter-personal abuses. A wide range of fields attempts to address technology-related privacy problems, however they vary immensely in terms of assumptions, scope and approach. Privacy of future use cases is typically handled vertically, instead of building upon previous work that can be re-contextualized, while current privacy problems are typically addressed per type in a more focused way. Because significant effort was required to make sense of the relations and structure of privacy-related work, this thesis attempts to transmit a structured view of it. It is multi-disciplinary - from cryptography to economics, including distributed systems and information theory - and addresses privacy issues of different natures. As existing work is framed and discussed, the contributions to the state-of-theart done in the scope of this thesis are presented. The contributions add to five distinct areas: 1) identity in distributed systems; 2) future context-aware services; 3) event-based context management; 4) low-latency information flow control; 5) high-dimensional dataset anonymity. Finally, having laid out such landscape of the privacy-preserving work, the current and future privacy challenges are discussed, considering not only technical but also socio-economic perspectives.

B-1 Monthly Report of Medical Services Provided under Title XIX of the Social Security Act, October 2016

B-1 Medicaid Reports -- The monthly Medicaid series of eight reports provide summaries of Medicaid eligibles, recipients served, and total payments by county, category of service, and aid category. These reports may also be known as the B-1 Reports. These reports are each available as a PDF for printing or as a CSV file for data analysis. Report Report name IAMM1800-R001--Medically Needy by County - No Spenddown and With Spenddown; IAMM1800-R002--Total Medically Needy, All Other Medicaid, and Grand Total by County; IAMM2200-R002--Monthly Expenditures by Category of Service; IAMM2200-R003--Fiscal YTD Expenditures by Category of Service; IAMM3800-R001--ICF & ICF-MR Vendor Payments by County; IAMM4400-R001--Monthly Expenditures by Eligibility Program; IAMM4400-R002--Monthly Expenditures by Category of Service by Program; IAMM4600-R002--Elderly Waiver Summary by County.

Introduction to Security Onion

Security Onion is a Network Security Manager (NSM) platform that provides multiple Intrusion Detection Systems (IDS) including Host IDS (HIDS) and Network IDS (NIDS). Many types of data can be acquired using Security Onion for analysis. This includes data related to: Host, Network, Session, Asset, Alert and Protocols. Security Onion can be implemented as a standalone deployment with server and sensor included or with a master server and multiple sensors allowing for the system to be scaled as required. Many interfaces and tools are available for management of the system and analysis of data such as Sguil, Snorby, Squert and Enterprise Log Search and Archive (ELSA). These interfaces can be used for analysis of alerts and captured events and then can be further exported for analysis in Network Forensic Analysis Tools (NFAT) such as NetworkMiner, CapME or Xplico. The Security Onion platform also provides various methods of management such as Secure SHell (SSH) for management of server and sensors and Web client remote access. All of this with the ability to replay and analyse example malicious traffic makes the Security Onion a suitable low cost alternative for Network Security Management. In this paper, we have a feature and functionality review for the Security Onion in terms of: types of data, configuration, interface, tools and system management.

Security and Trust in Distributed Computation

We propose three research problems to explore the relations between trust and security in the setting of distributed computation. In the first problem, we study trust-based adversary detection in distributed consensus computation. The adversaries we consider behave arbitrarily disobeying the consensus protocol. We propose a trust-based consensus algorithm with local and global trust evaluations. The algorithm can be abstracted using a two-layer structure with the top layer running a trust-based consensus algorithm and the bottom layer as a subroutine executing a global trust update scheme. We utilize a set of pre-trusted nodes, headers, to propagate local trust opinions throughout the network. This two-layer framework is flexible in that it can be easily extensible to contain more complicated decision rules, and global trust schemes. The first problem assumes that normal nodes are homogeneous, i.e. it is guaranteed that a normal node always behaves as it is programmed. In the second and third problems however, we assume that nodes are heterogeneous, i.e, given a task, the probability that a node generates a correct answer varies from node to node. The adversaries considered in these two problems are workers from the open crowd who are either investing little efforts in the tasks assigned to them or intentionally give wrong answers to questions. In the second part of the thesis, we consider a typical crowdsourcing task that aggregates input from multiple workers as a problem in information fusion. To cope with the issue of noisy and sometimes malicious input from workers, trust is used to model workers' expertise. In a multi-domain knowledge learning task, however, using scalar-valued trust to model a worker's performance is not sufficient to reflect the worker's trustworthiness in each of the domains. To address this issue, we propose a probabilistic model to jointly infer multi-dimensional trust of workers, multi-domain properties of questions, and true labels of questions. Our model is very flexible and extensible to incorporate metadata associated with questions. To show that, we further propose two extended models, one of which handles input tasks with real-valued features and the other handles tasks with text features by incorporating topic models. Our models can effectively recover trust vectors of workers, which can be very useful in task assignment adaptive to workers' trust in the future. These results can be applied for fusion of information from multiple data sources like sensors, human input, machine learning results, or a hybrid of them. In the second subproblem, we address crowdsourcing with adversaries under logical constraints. We observe that questions are often not independent in real life applications. Instead, there are logical relations between them. Similarly, workers that provide answers are not independent of each other either. Answers given by workers with similar attributes tend to be correlated. Therefore, we propose a novel unified graphical model consisting of two layers. The top layer encodes domain knowledge which allows users to express logical relations using first-order logic rules and the bottom layer encodes a traditional crowdsourcing graphical model. Our model can be seen as a generalized probabilistic soft logic framework that encodes both logical relations and probabilistic dependencies. To solve the collective inference problem efficiently, we have devised a scalable joint inference algorithm based on the alternating direction method of multipliers. The third part of the thesis considers the problem of optimal assignment under budget constraints when workers are unreliable and sometimes malicious. In a real crowdsourcing market, each answer obtained from a worker incurs cost. The cost is associated with both the level of trustworthiness of workers and the difficulty of tasks. Typically, access to expert-level (more trustworthy) workers is more expensive than to average crowd and completion of a challenging task is more costly than a click-away question. In this problem, we address the problem of optimal assignment of heterogeneous tasks to workers of varying trust levels with budget constraints. Specifically, we design a trust-aware task allocation algorithm that takes as inputs the estimated trust of workers and pre-set budget, and outputs the optimal assignment of tasks to workers. We derive the bound of total error probability that relates to budget, trustworthiness of crowds, and costs of obtaining labels from crowds naturally. Higher budget, more trustworthy crowds, and less costly jobs result in a lower theoretical bound. Our allocation scheme does not depend on the specific design of the trust evaluation component. Therefore, it can be combined with generic trust evaluation algorithms.

Dynamic-Data Driven Real-Time Identification for Electric Power Systems

Power system engineers face a double challenge: to operate electric power systems within narrow stability and security margins, and to maintain high reliability. There is an acute need to better understand the dynamic nature of power systems in order to be prepared for critical situations as they arise. Innovative measurement tools, such as phasor measurement units, can capture not only the slow variation of the voltages and currents but also the underlying oscillations in a power system. Such dynamic data accessibility provides us a strong motivation and a useful tool to explore dynamic-data driven applications in power systems. To fulfill this goal, this dissertation focuses on the following three areas: Developing accurate dynamic load models and updating variable parameters based on the measurement data, applying advanced nonlinear filtering concepts and technologies to real-time identification of power system models, and addressing computational issues by implementing the balanced truncation method. By obtaining more realistic system models, together with timely updated parameters and stochastic influence consideration, we can have an accurate portrait of the ongoing phenomena in an electrical power system. Hence we can further improve state estimation, stability analysis and real-time operation.