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

E-health applications utilizing IoT (Internet of Things) technologies hold a significant promise: biomedical sensor networks and the appropriate interpretation of the data originating from them enable better self-care of chronic diseases, and thus are potential to imply remarkable savings in national healthcare budgets However, security is a major concern in these applications due to varying use context, changing threats and the high privacy and confidentiality requirements of healthcare data Novel adaptive security management solutions, based on security effectiveness, correctness and efficiency evidence, can be used to respond to these needs We analyze security objectives of E-health IoT applications and their adaptive security decision-making needs, and propose a high-level adaptive security management mechanism based on security metrics to cope with the challenges

Towards metrics-driven adaptive security management in e-health IoT applications

A survey of security solutions for distributed publish/subscribe systems

Health care is one of the primary beneficiaries of the technological revolution created by Internet of Things (IoT). In the implementation of health care with IoT, wireless body area network (WBAN) is a suitable communication tool. That being the case security has been one of the major concerns to efficiently utilize the services of WBAN. The diverse nature of the technologies involved in WBAN, the broadcast nature of wireless networks, and the existence of resource constrained devices are the main challenges to implement heavy security protocols for WBAN. In this paper we develop a risk-based adaptive authentication mechanism which continuously monitors the channel characteristics variation, analyzes a potential risk using naive Bayes machine learning algorithm and performs adaptation of the authentication solution. Our solution validates both the authenticity of the user and the device. In addition we evaluate the resource need of the selected authentication solution and provide an offloading functionality in case of scarce resource to perform the selected protocol. The approach is novel because it defines the whole adaptation process and methods required in each phase of the adaptation. The paper also briefly describes the evaluation case study - Smart Home eHealth.

Risk-based adaptive authentication for internet of things in smart home eHealth

Our national security and critical infrastructure sectors have become increasingly dependent on commercial information systems and technologies whose pedigree is uncertain given the globalization of the supply chain. Furthermore, these system architectures are brittle and fail or are compromised when subjected to ever-increasingly advanced and adaptive cyber attacks, resulting in failed, disrupted or compromised mission operations. While we must continue to raise the bar to protect mission critical systems from these threats by implementing best security practices, the current philosophy of trying to keep the adversaries out, or the assumption that they will be detected if they get through the first line of defense, is no longer valid. Given the sophistication, adaptiveness, and persistence of cyber threats, we can no longer assume that we can completely defend against intruders and must change our mindset to assume some degree of adversary success and be prepared to “fight through” cyber attacks to ensure mission success even in a degraded or contested environment. This paper will focus on actionable architectural and operational recommendations to address the advanced cyber threat and to enable mission assurance for critical operations. These recommendations can create transformational improvements by helping to reverse adversary advantage, minimize exploit impact to essential operations, increase adversary cost and uncertainty, and act as a deterrent. These approaches go well beyond traditional information assurance, disaster recovery and survivability techniques. The approaches and strategies to be discussed include creative applications of trust technologies and advanced detection capabilities in conjunction with combination of techniques using diversity, redundancy, isolation and containment, least privilege, moving target defense, randomization and unpredictability, deception, and adaptive management and response.

Cyber resilience for mission assurance

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.

Giorgio Da Bormida

Papers

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