Emerging Internet of Things (IoTs) technologies provide many benefits to the improvement of eHealth. The successful deployment of IoTs depends on ensuring security and privacy that need to adapt to their processing capabilities and resource use. IoTs are vulnerable to attacks since communications are mostly wireless, unattended things are usually vulnerable to physical attacks, and most IoT components are constrained by energy, communications, and computation capabilities necessary for the implementation of complex security-supporting schemes. This paper describes a risk-based adaptive security framework for IoTs in eHealth that will estimate and predict risk damages and future benefits using game theory and context-awareness techniques. The paper also describes the validation case study.

Risk-based adaptive security for smart IoT in eHealth

Self-protecting software systems are a class of autonomic systems capable of detecting and mitigating security threats at runtime. They are growing in importance, as the stovepipe static methods of securing software systems have been shown to be inadequate for the challenges posed by modern software systems. Self-protection, like other self-* properties, allows the system to adapt to the changing environment through autonomic means without much human intervention, and can thereby be responsive, agile, and cost effective. While existing research has made significant progress towards autonomic and adaptive security, gaps and challenges remain. This article presents a significant extension of our preliminary study in this area. In particular, unlike our preliminary study, here we have followed a systematic literature review process, which has broadened the scope of our study and strengthened the validity of our conclusions. By proposing and applying a comprehensive taxonomy to classify and characterize the state-of-the-art research in this area, we have identified key patterns, trends and challenges in the existing approaches, which reveals a number of opportunities that will shape the focus of future research efforts.

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A Systematic Survey of Self-Protecting Software Systems

At NASA we have been developing and applying a risk management framework, "Defect Detection and Prevention" (DDP) It is based on a simple quantitative model of risk and is supported by custom software We have used it to aid in study and planning for systems that employ advanced technologies The framework has proven successful at identifying problematic requirements (those which will be the most difficult to attain), at optimizing the allocation of resources so as to maximize requirements attainment, at identifying areas where research investments should be made, and at supporting tradeoff analyses among major alternatives We describe the DDP model, the information that populates a model, how DDP is used, and its tool support DDP has been designed to aid decision making early in development Detailed information is lacking at this early stage Accordingly, DDP exhibits a number of strategic compromises between fidelity and tractability The net result is an approach that appears both feasible and useful during early requirements decision making

Quantitative risk-based requirements reasoning

Context: With the increased use of software for running key functions in modern society it is of utmost importance to understand software robustness and how to support it. Although there have been many contributions to the field there is a lack of a coherent and summary view. Objective: To address this issue, we have conducted a literature review in the field of robustness. Method: This review has been conducted by following guidelines for systematic literature reviews. Systematic reviews are used to find and classify all existing and available literature in a certain field. Results: From 9193 initial papers found in three well-known research databases, the 144 relevant papers were extracted through a multi-step filtering process with independent validation in each step. These papers were then further analyzed and categorized based on their development phase, domain, research, contribution and evaluation type. The results indicate that most existing results on software robustness focus on verification and validation of Commercial of the shelf (COTS) or operating systems or propose design solutions for robustness while there is a lack of results on how to elicit and specify robustness requirements. The research is typically solution proposals with little to no evaluation and when there is some evaluation it is primarily done with small, toy/academic example systems. Conclusion: We conclude that there is a need for more software robustness research on real-world, industrial systems and on software development phases other than testing and design, in particular on requirements engineering.

http://robertfeldt.net/publications/shahrokni_2013_sysrev_robustness.pdf

A systematic review of software robustness

Planning for the optimal attainment of requirements is an important early lifecycle activity. However, such planning is difficult when dealing with competing requirements, limited resources, and the incompleteness of information available at requirements time. A novel approach to requirements optimization is described. A requirements interaction model is executed to randomly sample the space of options. This produces a large amount of data, which is then condensed by a summarization tool. The result is a small list of critical decisions (i.e., those most influential in leading towards the desired optimum). This focuses human experts' attention on a relatively few decisions and makes them aware of major alternatives. This approach is iterative. Each iteration allows experts to select from among the major alternatives. In successive iterations the execution and summarization modules are run again, but each time further constrained by the decisions made in previous iteration. In the case study shown here, out of 99 yes/no decisions (approximately 10/sup 30/ possibilities), five iterations were sufficient to find and make the 30 key ones.

/pdf/converging-on-the-optimal-attainment-of-requirements-4b8ceha13b.pdf

Converging on the optimal attainment of requirements

GEMOM (Genetic Message Oriented Secure Middleware) is an EU FP7 ICT project that focuses on the significant and measurable increase in the end-to-end intelligence, security and resilience of complex, distributed information systems. Complex, distributed software systems are virtually impossible to implement without heavy use of messaging infrastructure. While the existing state of the art achieves arbitrary resilience by a brute-force approach, self-healing is either rudimentary or non-existent. GEMOM, with its fluid, resilient, self-healing and adaptive messaging allows for flexible messaging solutions and offers monitoring, management and maintenance incrementally. Its adaptive security solution will learn and adapt to changing environments during run-time in the face of changing threats without sacrificing the efficiency, flexibility, reliability and security of the system. This paper describes the significant and measurable progress beyond state of the art envisioned by the GEMOM project.

GEMOM - Significant and Measurable Progress beyond the State of the Art

Current business-critical systems have stringent requirements for the significant and measurable increase in the end-to-end intelligence, security, scalability, self-adaptation and resilience. Existing state-of-the-art messaging systems achieve arbitrary resilience by a brute-force approach. Selfhealing is either rudimentary or non-existent. In this study we present a self-healing and secure adaptive messaging middleware that provides solutions to overcome limitations in robustness, resilience, self-adaptability, scalability, and assurance against security threats and erroneous input during run-time in the face of changing threats. This developed system supports a messaging infrastructure which enables adaptive functions and assurance against security vulnerabilities and erroneous input vulnerabilities to improve the reliability, robustness and dependability of business-critical infrastructures. It provides autonomous adjustments of the run-time configuration of the system in order to preserve and maintain optimal and uninterrupted operation, improvement of the strength of security and degree of trust in the system, and improvement of the assessability and verifiability of the trustworthiness of the system. The methodology used in this research is partly analytical and partly experimental. We develop the new core functionalities theoretically and validate them practically by prototyping.

Self-healing and secure adaptive messaging middleware for business-critical systems

Current business critical systems have stringent requirements for the significant and measurable increase in the end-to-end intelligence, security, scalability, self-adaptation and resilience. Existing state of the art messaging systems achieve arbitrary resilience by a brute-force approach. Self-healing is either rudimentary or non-existent. In this study we present a robust, secure, self-adaptive and resilient messaging middleware that provides solutions to overcome limitations in robustness, resilience, evolvability, self-adaptability, scalability, and assurance against security threats and erroneous input during run-time in the face of changing threats. This developed system supports a messaging infrastructure which enables adaptive functions and assurance against security vulnerabilities and erroneous input vulnerabilities to improve the reliability, robustness and dependability of business critical infrastructures. The methodology used in this research is partly analytical and partly experimental. We develop the core novel functionalities theoretically and validate them practically by prototyping.

Robust, Secure, Self-Adaptive and Resilient Messaging Middleware for Business Critical Systems

This paper describes an approach to enhance the resilience of message oriented middleware to faults and attacks. The system is designed to work with different message oriented middleware as long as the messaging system can supply the information and control API required. The structure of the system and the approach to handling link failures, broker failures and anomalous behaviour through the planning of mirroring and relaying mechanisms to suit the tolerable risk and the deployment context is the focus of the paper. Validation is through industrial case studies and end user assessment.

Adding resilience to message oriented middleware

In a large software management programme, the number of software changes and enhancements requested for inclusion in the next software release often far exceeds the implementation resources available. Thus, during the preceding months before the final decision is made on which changes to include, there needs to be a way of incorporating all the different factors that influence these possible changes into a coherent set of information to enable good decisions to be made. This paper describes the use of influence diagrams to implement a risk model to formalise the combining of these different factors to aid the decision process. This model not only reflects the likelihood of all the necessary criteria for a requested change to be viable being met, but also considers the financial or other benefits to the organisation that would result from the change being included in the next software release.

Ilesh Dattani

Papers

GEMOM - Significant and Measurable Progress beyond the State of the Art

Self-healing and secure adaptive messaging middleware for business-critical systems

Robust, Secure, Self-Adaptive and Resilient Messaging Middleware for Business Critical Systems

Adding resilience to message oriented middleware

Using Influence Diagrams to Aid the Management of Software Change