Obstacles in Data Distribution Service Middleware: A Systematic Review

Köksal, Ömer; Tekinerdoğan, Bedir

doi:10.1016/j.future.2016.09.020

Cited by 28 publications

(11 citation statements)

References 6 publications

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“…), which are physically attached to medical devices to provide network capabilities [ 18 ]. On the other hand, the communications between the interfaces and the supervisor are managed by the external DDS middleware [ 19 ], which covers partially the cybersecurity of OpenICE.…”

Section: Related Workmentioning

confidence: 99%

Intelligent and Dynamic Ransomware Spread Detection and Mitigation in Integrated Clinical Environments

Maimó

Celdrán

Gómez

et al. 2019

Sensors

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Medical Cyber-Physical Systems (MCPS) hold the promise of reducing human errors and optimizing healthcare by delivering new ways to monitor, diagnose and treat patients through integrated clinical environments (ICE). Despite the benefits provided by MCPS, many of the ICE medical devices have not been designed to satisfy cybersecurity requirements and, consequently, are vulnerable to recent attacks. Nowadays, ransomware attacks account for 85% of all malware in healthcare, and more than 70% of attacks confirmed data disclosure. With the goal of improving this situation, the main contribution of this paper is an automatic, intelligent and real-time system to detect, classify, and mitigate ransomware in ICE. The proposed solution is fully integrated with the ICE++ architecture, our previous work, and makes use of Machine Learning (ML) techniques to detect and classify the spreading phase of ransomware attacks affecting ICE. Additionally, Network Function Virtualization (NFV) and Software Defined Networking (SDN)paradigms are considered to mitigate the ransomware spreading by isolating and replacing infected devices. Different experiments returned a precision/recall of 92.32%/99.97% in anomaly detection, an accuracy of 99.99% in ransomware classification, and promising detection and mitigation times. Finally, different labelled ransomware datasets in ICE have been created and made publicly available.

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Section: Related Workmentioning

confidence: 99%

Intelligent and Dynamic Ransomware Spread Detection and Mitigation in Integrated Clinical Environments

Maimó

Celdrán

Gómez

et al. 2019

Sensors

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“…The allocation of software units on computing systems has applications in different computing domains such as embedded systems, local/wide area distributed systems, parallel and distributed simulations, etc. In our earlier work, we have carried out a systematic review to identify the obstacles of DDS based systems [12]. One of the identified key obstacles that we derived from the systematic review was indeed the task allocation problem.…”

Section: Related Workmentioning

confidence: 99%

Generation of feasible deployment configuration alternatives for Data Distribution Service based systems

Tekinerdoğan

Çelik²,

Köksal

2018

Computer Standards & Interfaces

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(DDS) has been defined by the OMG to provide a standard data-centric publish-subscribe programming model and specification for distributed systems. DDS has been applied for the development of high performance distributed systems such as in the defense, finance, automotive, and simulation domains. To support the analysis and design of a DDS-based distributed system, the OMG has proposed the DDS UML Profile. A DDS-based system usually consists of multiple participant applications each of which has different responsibilities in the system. These participants can be allocated in different ways to the available resources, which leads to different configuration alternatives. Usually, each configuration alternative will perform differently with respect to the execution and communication cost of the overall system. In general, the deployment configuration is selected manually based on expert knowledge. This approach is suitable for small to medium scale applications but for larger applications this is not tractable. In this paper, we provide a systematic approach for deriving feasible deployment alternatives based on the system design and the available physical resources. The system design is supported by the DDS UML profile that we have extended to support the generation of feasible deployment alternatives. Based on the modeled system design and physical resources, the feasible deployment alternatives can be algorithmically derived and automatically generated using the developed tools. We illustrate the approach for deriving feasible deployment alternatives of smart city parking system.

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“…DDS might get/send enormous data from many simultaneous publishers/subscribers. On the other hand, DDS, from the IoT perspective, has some obstacles in wide area network communication, wireless communication and mobile computing domains (Köksal & Tekinerdogan, 2017b).…”

Section: ) Ddsmentioning

confidence: 99%

“…In fact, one of the powerful features of the DDS is supporting multicast UDP that enables high performance Machine-to-machine communication. On the other hand, since multicast and UDP transports are not supported by many Wide Area Networks (WAN), some additional concepts like Interconnection Services or Routers shall be used in DDS systems to assure end-to-end QoS in WANs (Köksal & Tekinerdogan, 2017b). For further details about these specifications we refer to OMG DDS Specifications (OMG, 2015b).…”

Section: Layered Viewmentioning

confidence: 99%

“…The allocation of software units on computing systems has applications in different computing domains such as embedded systems, local/wide area distributed systems, parallel and distributed simulations, etc. In our earlier work, we have carried out a systematic review to identify the obstacles of DDS based systems (Köksal & Tekinerdogan, 2017b). One of the identified key obstacles that we derived from the systematic review was indeed the task allocation problem.…”

Section: Related Workmentioning

confidence: 99%

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Architecting integrated internet of things systems

Köksal¹

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The Internet of Things (IoT) architecture is defined as a layered structure in which each layer represents a coherent set of services. For supporting the communication among the different IoT entities many different communication protocols are now available in practice. For practitioners, it is often not clear which communication protocol is suitable for the various conditions in which the IoT systems need to be operated. In this chapter, we focus on the session layer which is responsible for setting up and taking down of the association between the IoT connection points. We adopt a feature-driven domain analysis whereby we define the common and variant features that are related to communication protocols in the session layer. Based on the resulting feature diagram we explicitly characterize the existing session layer communication protocols. Further we define the criteria for selecting the identified communication protocols for the different conditions.

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Obstacles in Data Distribution Service Middleware: A Systematic Review

Cited by 28 publications

References 6 publications

Intelligent and Dynamic Ransomware Spread Detection and Mitigation in Integrated Clinical Environments

Intelligent and Dynamic Ransomware Spread Detection and Mitigation in Integrated Clinical Environments

Generation of feasible deployment configuration alternatives for Data Distribution Service based systems

Architecting integrated internet of things systems

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