Study on impact of adding security in a 6LoWPAN based network

Carlier, Matthias; Steenhaut, Kris; Braeken, An; Ruben, Smeets; Mentens, Nele; Aerts, Kris

doi:10.1109/cns.2015.7346871

Cited by 5 publications

(6 citation statements)

References 17 publications

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“…The Device Grader extracts the available battery and memory of the IoT device so an appropriate decision can be made to select an encryption algorithm. For the power trace, the kinetic battery model [15] (KiBaM) was used to calculate the state of battery charge. Its energy-harvesting module reads the data-trace having the harvested energy per minute.…”

Section: Device Gradermentioning

confidence: 99%

“…In dynamic environments, IoT devices generate data of varying confidentiality levels, therefore, it is not suitable to deploy the same encryption algorithm for different pieces of data which either leads to heavy utilization of resources or compromised security. In this regard, context-aware encryption techniques can play an important role to finalize the encryption algorithm for different confidentiality levels of data generated by the device [15]. Moreover, for the effective utilization of context information, it is essential to present it unambiguously while considering the dynamics of IoT system, the capability of the device, and the confidentiality level of the information.…”

Section: Introductionmentioning

confidence: 99%

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A Fuzzy Ontology-based Context-aware Encryption approach in IoT through Device and Information Classification

Dar

Awada

Zeshan

et al. 2023

Preprint

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IoT devices produce a vast amount of data ranging from personal to sensitive information. Usually, these devices remain connected to the internet so protecting the information produced by them is crucial. Since most of the IoT devices are resource-constrained, they must be supported with light-weight encryption standards to protect information. Recent research has used the concept of context awareness to select the most suitable data encryption standard based on the device resources along with the required information confidentiality level. However, to effectively use the context information, it is required to be organized explicitly while considering the dynamic nature of IoT systems. In this regard, ontology-based systems effectively reduce the volume of manual work while recommending solutions. Currently, these systems cannot work with precision due to multiple uncertain factors of IoT sensory data,. To overcome this challenge, this research proposes a fuzzy ontology-based context-aware system to protect IoT device information with the help of an encryption algorithm that considers device capabilities and user priorities regarding the data confidentiality. In-order to automate the recommendation process, Semantic Web Rule Language (SWRL) rules and fuzzy logic are used, whereas, Description Logic and RDF Query Language is used to evaluate the results. The evaluation results confirm that the proposed method can produce results according to human perception by significantly increasing the accuracy of prediction.

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Section: Device Gradermentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Fuzzy Ontology-based Context-aware Encryption approach in IoT through Device and Information Classification

Dar

Awada

Zeshan

et al. 2023

Preprint

View full text Add to dashboard Cite

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“…A performance study of end-to-end security available for 6LoWPAN based networks is presented by Matthias et al [43]. The performance analysis covered battery consumption, network latency and memory utilization, while did not measure the impact of information or device classification on the resources.…”

Section: Encryption In 6lowpanmentioning

confidence: 99%

A context-aware encryption protocol suite for edge computing-based IoT devices

et al. 2019

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Heterogeneous devices are connected with each other through wireless links within a Cyber Physical System. These devices undergo resource constraints such as battery, bandwidth, memory, and computing power. Moreover, the massive interconnections of these devices result in network latency and reduced speed. Edge computing offers a solution to this problem in which devices transmit the preprocessed actionable data in a formal way resulting in reduced data traffic and improved speed. However, to provide the same level of security to each piece of information is not feasible due to limited resources. In addition, not all the data generated by Internet of Things (IoT) devices require a high level of security. Context-awareness principles can be employed to select an optimal algorithm based on device specifications and required information confidentiality level. For context-awareness, it is essential to consider the dynamic requirements of data confidentiality as well as device available resources. This paper presents a context-aware encryption protocol suite that selects optimal encryption algorithm according to device specifications and the level of data confidentiality. The results presented herein clearly exhibit that the devices were able to save 79% memory consumption, 56% battery consumption and 68% execution time by employing the proposed context-aware encryption protocol suite.

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“…This method uses a Secure Service Manager (SSM) protected against spoofing, provides semi end to end security, DoS resilience as DTLS handshakes can be resource intensive and are in this method delegated, and remove single points of failures. In [54], the researchers investigate the impact of including low cost security solutions into the communication scheme on latency, power, and memory management. The security solution they benchmark makes use of AES-CCM which is one of the favourites encryption mechanisms in WSN accordingly to our study, along with RC4 in some cases for its performances and low computational cost.…”

Section: Cryptography-based Defencesmentioning

confidence: 99%

The Security of Smart Buildings: a Systematic Literature Review

Ciholas,

Lennie,

Sadigova

et al. 2019

Preprint

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Smart Buildings are networks of connected devices and software in charge of automatically managing and controlling several building functions such as HVAC, fire alarms, lighting, shading and more. These systems evolved from mostly electronic and mechanical elements to complex systems relying on IT and wireless technologies and networks. This exposes smart buildings to new risks and threats that need to be enumerated and addressed. Research efforts have been done in several areas related to security in smart buildings but a clear overview of the research field is missing. In this paper, we present the results of a systematic literature review that provides a thorough understanding of the state of the art in research on the security of smart buildings. We found that the field of smart buildings security is growing significantly in complexity due to the many protocols introduced recently and that the research community is already studying. We also found an important lack of empirical evaluations, though evaluations on testbeds and real systems seems to be growing. Finally, we found an almost complete lack of consideration of non-technical aspects, such as social, organisational, and human factors, which are crucial in this type of systems, where ownership and liability is not always clear.

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Study on impact of adding security in a 6LoWPAN based network

Cited by 5 publications

References 17 publications

A Fuzzy Ontology-based Context-aware Encryption approach in IoT through Device and Information Classification

A Fuzzy Ontology-based Context-aware Encryption approach in IoT through Device and Information Classification

A context-aware encryption protocol suite for edge computing-based IoT devices

The Security of Smart Buildings: a Systematic Literature Review

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