Generating Secure Service Compositions

Ensuring that the compositions of services that constitute service-based systems satisfy given security properties is a key prerequisite for the adoption of the service oriented computing paradigm. In this paper, we address this issue using a novel approach that guarantees service composition security by virtue of the generation of compositions. Our approach generates service compositions that are guaranteed to satisfy security properties based on secure service orchestration (SESO) patterns. These patterns express primitive (e.g., sequential, parallel) service orchestrations, which are proven to have certain global security properties if the individual services participating in them have themselves other security properties. The paper shows how SESO patterns can be constructed and gives examples of proofs for such patterns. It also presents the process of using SESO patterns to generate secure service compositions and presents the results of an initial experimental evaluation of the approach

Service composition in stochastic settings

With the growth of the Internet-of-Things and online Web services, more services with more capabilities are available to us. The ability to generate new, more useful services from existing ones has been the focus of much research for over a decade. The goal is, given a specification of the behavior of the target service, to build a controller, known as an orchestrator, that uses existing services to satisfy the requirements of the target service. The model of services and requirements used in most work is that of a finite state machine. This implies that the specification can either be satisfied or not, with no middle ground. This is a major drawback, since often an exact solution cannot be obtained. In this paper we study a simple stochastic model for service composition: we annotate the tar- get service with probabilities describing the likelihood of requesting each action in a state, and rewards for being able to execute actions. We show how to solve the resulting problem by solving a certain Markov Decision Process (MDP) derived from the service and requirement specifications. The solution to this MDP induces an orchestrator that coincides with the exact solution if a composition exists. Otherwise it provides an approximate solution that maximizes the expected sum of values of user requests that can be serviced. The model studied although simple shades light on composition in stochastic settings and indeed we discuss several possible extensions

A framework for deriving semantic web services

Web service-based development represents an emerging approach for the development of distributed information systems. Web services have been mainly applied by software practitioners as a means to modularize system functionality that can be offered across a network (e.g., intranet and/or the Internet). Although web services have been predominantly developed as a technical solution for integrating software systems, there is a more business-oriented aspect that developers and enterprises need to deal with in order to benefit from the full potential of web services in an electronic market. This ‘ignored’ aspect is the representation of the semantics underlying the services themselves as well as the ‘things’ that the services manage. Currently languages like the Web Services Description Language (WSDL) provide the syntactic means to describe web services, but lack in providing a semantic underpinning. In order to harvest all the benefits of web services technology, a framework has been developed for deriving business semantics from syntactic descriptions of web services. The benefits of such a framework are two-fold. Firstly, the framework provides a way to gradually construct domain ontologies from previously defined technical services. Secondly, the framework enables the migration of syntactically defined web services toward semantic web services. The study follows a design research approach which (1) identifies the problem area and its relevance from an industrial case study and previous research, (2) develops the framework as a design artifact and (3) evaluates the application of the framework through a relevant scenario

Conditional Gene Expression in Mycobacterium abscessus

Mycobacterium abscessus is an emerging human pathogen responsible for lung infections, skin and soft-tissue infections and disseminated infections in immunocompromised patients. It may exist either as a smooth (S) or rough (R) morphotype, the latter being associated with increased pathogenicity in various models. Genetic tools for homologous recombination and conditional gene expression are desperately needed to allow the study of M. abscessus virulence. However, descriptions of knock-out (KO) mutants in M. abscessus are rare, with only one KO mutant from an S strain described so far. Moreover, of the three major tools developed for homologous recombination in mycobacteria, only the one based on expression of phage recombinases is working. Several conditional gene expression tools have recently been engineered for Mycobacterium tuberculosis and Mycobacterium smegmatis, but none have been tested yet in M. abscessus. Based on previous experience with genetic tools allowing homologous recombination and their failure in M. abscessus, we evaluated the potential interest of a conditional gene expression approach using a system derived from the two repressors system, TetR/PipOFF. After several steps necessary to adapt TetR/PipOFF for M. abscessus, we have shown the efficiency of this system for conditional expression of an essential mycobacterial gene, fadD32. Inhibition of fadD32 was demonstrated for both the S and R isotypes, with marginally better efficiency for the R isotype. Conditional gene expression using the dedicated TetR/PipOFF system vectors developed here is effective in S and R M. abscessus, and may constitute an interesting approach for future genetic studies in this pathogen

Molecular Longitudinal Tracking of Mycobacterium abscessus spp. during Chronic Infection of the Human Lung

<div><p>The <i>Mycobacterium abscessus</i> complex is an emerging cause of chronic pulmonary infection in patients with underlying lung disease. The <i>M. abscessus</i> complex is regarded as an environmental pathogen but its molecular adaptation to the human lung during long-term infection is poorly understood. Here we carried out a longitudinal molecular epidemiological analysis of 178 <i>M. abscessus</i> spp. isolates obtained from 10 cystic fibrosis (CF) and 2 non CF patients over a 13 year period. Multi-locus sequence and molecular typing analysis revealed that 11 of 12 patients were persistently colonized with the same genotype during the course of the infection while replacement of a <i>M. abscessus sensu stricto</i> strain with a <i>Mycobacterium massiliense</i> strain was observed for a single patient. Of note, several patients including a pair of siblings were colonized with closely-related strains consistent with intra-familial transmission or a common infection reservoir. In general, a switch from smooth to rough colony morphology was observed during the course of long-term infection, which in some cases correlated with an increasing severity of clinical symptoms. To examine evolution during long-term infection of the CF lung we compared the genome sequences of 6 sequential isolates of <i>Mycobacterium bolletii</i> obtained from a single patient over an 11 year period, revealing a heterogeneous clonal infecting population with mutations in regulators controlling the expression of virulence factors and complex lipids. Taken together, these data provide new insights into the epidemiology of <i>M. abscessus</i> spp. during long-term infection of the CF lung, and the molecular transition from saprophytic organism to human pathogen.</p></div

Application of data fusion techniques and technologies for wearable health monitoring

Technological advances in sensors and communications have enabled discrete integration into everyday objects, both in the home and about the person. Information gathered by monitoring physiological, behavioural, and social aspects of our lives, can be used to achieve a positive impact on quality of life, health, and well-being. Wearable sensors are at the cusp of becoming truly pervasive, and could be woven into the clothes and accessories that we wear such that they become ubiquitous and transparent. To interpret the complex multidimensional information provided by these sensors, data fusion techniques are employed to provide a meaningful representation of the sensor outputs. This paper is intended to provide a short overview of data fusion techniques and algorithms that can be used to interpret wearable sensor data in the context of health monitoring applications. The application of these techniques are then described in the context of healthcare including activity and ambulatory monitoring, gait analysis, fall detection, and biometric monitoring. A snap-shot of current commercially available sensors is also provided, focusing on their sensing capability, and a commentary on the gaps that need to be bridged to bring research to market

Mycobacterium abscessus-Induced Granuloma Formation Is Strictly Dependent on TNF Signaling and Neutrophil Trafficking

Mycobacterium abscessus is considered the most common respiratory pathogen among the rapidly growing non-tuberculous mycobacteria. Infections with M. abscessus are increasingly found in patients with chronic lung diseases, especially cystic fibrosis, and are often refractory to antibiotic therapy. M. abscessus has two morphotypes with distinct effects on host cells and biological responses. The smooth (S) variant is recognized as the initial airway colonizer while the rough (R) is known to be a potent inflammatory inducer associated with invasive disease, but the underlying immunopathological mechanisms of the infection remain unsolved. We conducted a comparative stepwise dissection of the inflammatory response in S and R pathogenesis by monitoring infected transparent zebrafish embryos. Loss of TNFR1 function resulted in increased mortality with both variants, and was associated with unrestricted intramacrophage bacterial growth and decreased bactericidal activity. The use of transgenic zebrafish lines harboring fluorescent macrophages and neutrophils revealed that neutrophils, like macrophages, interact with M. abscessus at the initial infection sites. Impaired TNF signaling disrupted the IL8-dependent neutrophil mobilization, and the defect in neutrophil trafficking led to the formation of aberrant granulomas, extensive mycobacterial cording, unrestricted bacterial growth and subsequent larval death. Our findings emphasize the central role of neutrophils for the establishment and maintenance of the protective M. abscessus granulomas. These results also suggest that the TNF/IL8 inflammatory axis is necessary for protective immunity against M. abscessus and may be of clinical relevance to explain why immunosuppressive TNF therapy leads to the exacerbation of M. abscessus infections