Experiences of women in secure care who have been prescribed clozapine for borderline personality disorder

Background: Clozapine is an atypical antipsychotic medicine which can cause significant side-effects. It is often prescribed off-license in severe cases of borderline personality disorder contrary to national treatment guidelines. Little is known about the experiences of those who take clozapine for borderline personality disorder. We explored the lived-experience of women in secure inpatient care who were prescribed clozapine for borderline personality disorder. Findings: Adult females (N=20) participated in audio-taped semi-structured interviews. Transcripts were subject to thematic analysis. The central themes related to evaluation, wellbeing, understanding and self-management; for many, their subjective wellbeing on clozapine was preferred to prior levels of functioning and symptomatology, sometimes profoundly so. The negative and potentially adverse effects of clozapine were explained as regrettable but relatively unimportant. Conclusions: When psychological interventions are, at least initially, ineffective then clozapine treatment is likely to be evaluated positively by a group of women with borderline personality disorder in secure care despite the potential disadvantages.

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.

Discontinuous Galerkin Computation of the Maxwell Eigenvalues on Simplicial Meshes

This paper is concerned with the discontinuous Galerkin approximation of the Maxwell eigenproblem. After reviewing the theory developed in [5], we present a set of numerical experiments which both validate the theory, and provide further insight regarding the practical performance of discontinuous Galerkin methods, particularly in the case when non-conforming meshes, characterized by the presence of hanging nodes, are employed.

The MUSE Machine -- an Architecture for Structured Data Flow Computation

Computers employing some degree of data flow organisation are now well established as providing a possible vehicle for concurrent computation. Although data-driven computation frees the architecture from the constraints of the single program counter, processor and global memory, inherent in the classic von Neumann computer, there can still be problems with the unconstrained generation of fresh result tokens if a pure data flow approach is adopted. The advantages of allowing serial processing for those parts of a program which are inherently serial, and of permitting a demand-driven, as well as data-driven, mode of operation are identified and described. The MUSE machine described here is a structured architecture supporting both serial and parallel processing which allows the abstract structure of a program to be mapped onto the machine in a logical way.

A new distributed MIKEY mode to secure e-health applications.

Securing e-health applications in the context of Internet of Things (IoT) is challenging. Indeed, resources scarcity in such environment hinders the implementation of existing standard based protocols. Among these protocols, MIKEY (Multimedia Internet KEYing) aims at establishing security credentials between two communicating entities. However, the existing MIKEY modes fail to meet IoT specificities. In particular, the pre-shared key mode is energy efficient, but suffers from severe scalability issues. On the other hand, asymmetric modes such as the public key mode are scalable, but are highly resource consuming. To address this issue, we combine two previously proposed approaches to introduce a new hybrid MIKEY mode. Indeed, relying on a cooperative approach, a set of third parties is used to discharge the constrained nodes from heavy computational operations. Doing so, the pre-shared mode is used in the constrained part of the network, while the public key mode is used in the unconstrained part of the network. Preliminary results show that our proposed mode is energy preserving whereas its security properties are kept safe.

Distributed and compressed MIKEY mode to secure end-to-end communications in the Internet of things.

Multimedia Internet KEYing protocol (MIKEY) aims at establishing secure credentials between two communicating entities. However, existing MIKEY modes fail to meet the requirements of low-power and low-processing devices. To address this issue, we combine two previously proposed approaches to introduce a new distributed and compressed MIKEY mode for the Internet of Things. Indeed, relying on a cooperative approach, a set of third parties is used to discharge the constrained nodes from heavy computational operations. Doing so, the preshared mode is used in the constrained part of network, while the public key mode is used in the unconstrained part of the network. Furthermore, to mitigate the communication cost we introduce a new header compression scheme that reduces the size of MIKEY’s header from 12 Bytes to 3 Bytes in the best compression case. Preliminary results show that our proposed mode is energy preserving whereas its security properties are preserved untouched.

Secure, dynamic and distributed access control stack for database applications

In database applications, access control security layers are mostly developed from tools provided by vendors of database management systems and deployed in the same servers containing the data to be protected. This solution conveys several drawbacks. Among them we emphasize: 1) if policies are complex, their enforcement can lead to performance decay of database servers; 2) when modifications in the established policies implies modifications in the business logic (usually deployed at the client-side), there is no other possibility than modify the business logic in advance and, finally, 3) malicious users can issue CRUD expressions systematically against the DBMS expecting to identify any security gap. In order to overcome these drawbacks, in this paper we propose an access control stack characterized by: most of the mechanisms are deployed at the client-side; whenever security policies evolve, the security mechanisms are automatically updated at runtime and, finally, client-side applications do not handle CRUD expressions directly. We also present an implementation of the proposed stack to prove its feasibility. This paper presents a new approach to enforce access control in database applications, this way expecting to contribute positively to the state of the art in the field.

Secure, dynamic and distributed access control stack for database applications

In database applications, access control security layers are mostly developed from tools provided by vendors of database management systems and deployed in the same servers containing the data to be protected. This solution conveys several drawbacks. Among them we emphasize: (1) if policies are complex, their enforcement can lead to performance decay of database servers; (2) when modifications in the established policies implies modifications in the business logic (usually deployed at the client-side), there is no other possibility than modify the business logic in advance and, finally, 3) malicious users can issue CRUD expressions systematically against the DBMS expecting to identify any security gap. In order to overcome these drawbacks, in this paper we propose an access control stack characterized by: most of the mechanisms are deployed at the client-side; whenever security policies evolve, the security mechanisms are automatically updated at runtime and, finally, client-side applications do not handle CRUD expressions directly. We also present an implementation of the proposed stack to prove its feasibility. This paper presents a new approach to enforce access control in database applications, this way expecting to contribute positively to the state of the art in the field.

Bezpieczeństwo protokołów w środowisku o ograniczonym zaufaniu

Wydział Matematyki i Informatyki UAM

Processing of laser Doppler flowmetry signals from healthy subjects and patients with varicose veins: information categorization approach based on intrinsic mode functions and entropy computation

International audience

Modernizing Secure OLAP Applications with a Model-Driven Approach

The majority of the organizations store their historical business information in data warehouses which are queried to make strategic decisions by using online analytical processing (OLAP) tools. This information has to be correctly assured against unauthorized accesses, but nevertheless there are a great amount of legacy OLAP applications that have been developed without considering security aspects or these have been incorporated once the system was implemented. This work defines a reverse engineering process that allows us to obtain the conceptual model corresponding to a legacy OLAP application, and also analyses and represents the security aspects that could have established. This process has been aligned with a model-driven architecture for developing secure OLAP applications by defining the transformations needed to automatically apply it. Once the conceptual model has been extracted, it can be easily modified and improved with security, and automatically transformed to generate the new implementation.

A MATLAB program for the computation of the confluent hypergeometric function Φ2

We here present a sample MATLAB program for the numerical evaluation of the confluent hypergeometric function Φ2. This program is based on the calculation of the inverse Laplace transform using the algorithm suggested by Simon and Alouini in their reference textbook [1].

SECURITY, PRIVACY AND APPLICATIONS IN VEHICULAR AD HOC NETWORKS

With wireless vehicular communications, Vehicular Ad Hoc Networks (VANETs) enable numerous applications to enhance traffic safety, traffic efficiency, and driving experience. However, VANETs also impose severe security and privacy challenges which need to be thoroughly investigated. In this dissertation, we enhance the security, privacy, and applications of VANETs, by 1) designing application-driven security and privacy solutions for VANETs, and 2) designing appealing VANET applications with proper security and privacy assurance. First, the security and privacy challenges of VANETs with most application significance are identified and thoroughly investigated. With both theoretical novelty and realistic considerations, these security and privacy schemes are especially appealing to VANETs. Specifically, multi-hop communications in VANETs suffer from packet dropping, packet tampering, and communication failures which have not been satisfyingly tackled in literature. Thus, a lightweight reliable and faithful data packet relaying framework (LEAPER) is proposed to ensure reliable and trustworthy multi-hop communications by enhancing the cooperation of neighboring nodes. Message verification, including both content and signature verification, generally is computation-extensive and incurs severe scalability issues to each node. The resource-aware message verification (RAMV) scheme is proposed to ensure resource-aware, secure, and application-friendly message verification in VANETs. On the other hand, to make VANETs acceptable to the privacy-sensitive users, the identity and location privacy of each node should be properly protected. To this end, a joint privacy and reputation assurance (JPRA) scheme is proposed to synergistically support privacy protection and reputation management by reconciling their inherent conflicting requirements. Besides, the privacy implications of short-time certificates are thoroughly investigated in a short-time certificates-based privacy protection (STCP2) scheme, to make privacy protection in VANETs feasible with short-time certificates. Secondly, three novel solutions, namely VANET-based ambient ad dissemination (VAAD), general-purpose automatic survey (GPAS), and VehicleView, are proposed to support the appealing value-added applications based on VANETs. These solutions all follow practical application models, and an incentive-centered architecture is proposed for each solution to balance the conflicting requirements of the involved entities. Besides, the critical security and privacy challenges of these applications are investigated and addressed with novel solutions. Thus, with proper security and privacy assurance, these solutions show great application significance and economic potentials to VANETs. Thus, by enhancing the security, privacy, and applications of VANETs, this dissertation fills the gap between the existing theoretic research and the realistic implementation of VANETs, facilitating the realistic deployment of VANETs.

Secure and Privacy-aware Data Collection and Processing in Mobile Health Systems

Healthcare systems have assimilated information and communication technologies in order to improve the quality of healthcare and patient's experience at reduced costs. The increasing digitalization of people's health information raises however new threats regarding information security and privacy. Accidental or deliberate data breaches of health data may lead to societal pressures, embarrassment and discrimination. Information security and privacy are paramount to achieve high quality healthcare services, and further, to not harm individuals when providing care. With that in mind, we give special attention to the category of Mobile Health (mHealth) systems. That is, the use of mobile devices (e.g., mobile phones, sensors, PDAs) to support medical and public health. Such systems, have been particularly successful in developing countries, taking advantage of the flourishing mobile market and the need to expand the coverage of primary healthcare programs. Many mHealth initiatives, however, fail to address security and privacy issues. This, coupled with the lack of specific legislation for privacy and data protection in these countries, increases the risk of harm to individuals. The overall objective of this thesis is to enhance knowledge regarding the design of security and privacy technologies for mHealth systems. In particular, we deal with mHealth Data Collection Systems (MDCSs), which consists of mobile devices for collecting and reporting health-related data, replacing paper-based approaches for health surveys and surveillance. This thesis consists of publications contributing to mHealth security and privacy in various ways: with a comprehensive literature review about mHealth in Brazil; with the design of a security framework for MDCSs (SecourHealth); with the design of a MDCS (GeoHealth); with the design of Privacy Impact Assessment template for MDCSs; and with the study of ontology-based obfuscation and anonymisation functions for health data.