Engineering Software Diversity

Morin, Brice; Høgenes, Jakob; Song, Hui; Harrand, Nicolas; Baudry, Benoît

doi:10.1145/3239372.3239393

Cited by 3 publications

(2 citation statements)

References 22 publications

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“…Software diversity is a new dimension of architecture-level properties, which is both a result of the hardware heterogeneity and a method toward more secure system. The fleet deployment approach provides a implementation-level support to our theoretical approaches towards a more diverse software [29,45].…”

Section: On the Deployment At The Fleet Layermentioning

confidence: 99%

See 1 more Smart Citation

4. Model-based Continuous Deployment of SIS

Ferry¹,

Song²,

Dautov³

et al. 2021

DevOps for Trustworthy Smart IoT Systems

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Section: On the Deployment At The Fleet Layermentioning

confidence: 99%

“…In this section, we briefly describe the mechanisms and the corresponding tools we developed to automatically generate the diverse protocols. Technical details and the experiment results can be found in our conference paper [29].…”

Section: Software Diversity Within Iot Fleetmentioning

confidence: 99%

4. Model-based Continuous Deployment of SIS

Ferry¹,

Song²,

Dautov³

et al. 2021

DevOps for Trustworthy Smart IoT Systems

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Model-based fleet deployment in the IoT–edge–cloud continuum

et al. 2022

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With the increasing computing and networking capabilities, IoT devices and edge gateways have become part of a larger IoT–edge–cloud computing continuum, where processing and storage tasks are distributed across the whole network hierarchy, not concentrated only in the cloud. At the same time, this also introduced continuous delivery practices to the development of software components for network-connected gateways and sensing/actuating nodes. These devices are placed on end users’ premises and are characterized by continuously changing cyber-physical contexts, forcing software developers to maintain multiple application versions and frequently redeploy them on a distributed fleet of devices with respect to their current contexts. Doing this correctly and efficiently goes beyond manual capabilities and requires an intelligent and reliable automated solution. This paper describes a model-based approach to automatically assigning multiple software deployment plans to hundreds of edge gateways and connected IoT devices implemented in collaboration with a smart healthcare application provider. From a platform-specific model of an existing edge computing platform, we extract a platform-independent model that describes a list of target devices and a pool of available deployment plans. Next, we use constraint solving to automatically assign deployment plans to devices at once with respect to their specific contexts. The result is transformed back into the platform-specific model and includes a suitable deployment plan for each device, which is then consumed by our engine to deploy software components not only on edge gateways but also on their downstream IoT devices with constrained resources and connectivity. We validate the approach with a fleet deployment prototype integrated into a DevOps toolchain used by the partner application provider. Initial experiments demonstrate the viability of the approach and its usefulness in supporting DevOps for edge and IoT software development.

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MTD, Where Art Thou? A Systematic Review of Moving Target Defense Techniques for IoT

Navas

Cuppens

et al. 2021

IEEE Internet Things J.

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Internet of Things (IoT) systems are increasingly deployed in the real world, but their security lags behind the state of the art of non-IoT systems. Moving Target Defense (MTD) is a cyberdefense paradigm, successfully implemented in conventional systems, that could improve IoT security. Objective: Identify and synthesize existing MTD techniques for IoT and validate the feasibility of MTD as a cybersecurity paradigm suitable for IoT systems. Method: We use a systematic literature review method to search and analyze existing MTD for IoT techniques up to July 2020. We evaluated the existing techniques in terms of security foundations and real-world deployability using the evidence they provide. We define and use entropy-related metrics to categorize them. This is the first MTD survey to use Shannon's entropy metric empirically. Results: Thirty-two distinct MTD for IoT techniques exist: 54% are Network-layer-based, 50% present strong evidence about their real-world deployment, and 64% have weak security foundations. Conclusion: MTD for IoT is a feasible cyberdefense approach. A variety of proposals exist, with evidence about their implementation and evaluation. Nevertheless, the MTD for IoT state of the art is still immature: the security foundations of most existing proposals are weak. Novel techniques should prioritize providing convincing security foundations and realworld deployment evidence.

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Engineering Software Diversity

Cited by 3 publications

References 22 publications

4. Model-based Continuous Deployment of SIS

4. Model-based Continuous Deployment of SIS

Model-based fleet deployment in the IoT–edge–cloud continuum

MTD, Where Art Thou? A Systematic Review of Moving Target Defense Techniques for IoT

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