Security Protocols and Privacy Issues into 6LoWPAN Stack: A Synthesis

Hennebert, Christine; Santos, Jessye Dos

doi:10.1109/jiot.2014.2359538

Cited by 125 publications

(57 citation statements)

References 12 publications

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“…But, the Maximum Transferrable Unit (MTU) of IPV6 is 1280 bytes. 6LoWPAN adaptation layer provides fragmentation and re‐ordering, and compression of the protocol stack headers of IPv6 packets to maintain the communication compatibility between IEEE 802.15.4 frame and the legacy Internet message packet . LAUP works on transport layer of the 6LoWPAN protocol.…”

Section: Proposed Workmentioning

confidence: 99%

Testbed evaluation of Lightweight Authentication Protocol (LAUP) for 6LoWPAN wireless sensor networks

Baskaran

Nanda

Nepal

et al. 2018

Concurrency and Computation

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Summary 6LoWPAN networks involving wireless sensors consist of resource starving miniature sensor nodes. Since secured authentication is one of the important considerations, the use of asymmetric key distribution scheme may not be a perfect choice. Recent research shows that Lucky Thirteen attack has compromised Datagram Transport Layer Security (DTLS) with Cipher Block Chaining (CBC) mode for key establishment. Even though EAKES6Lo and S3 K techniques for key establishment follow the symmetric key establishment method, they strongly rely on a remote server and trust anchor. Our proposed Lightweight Authentication Protocol (LAUP) used a symmetric key method with no preshared keys and comprised of four flights to establish authentication and session key distribution between sensors and Edge Router in a 6LoWPAN environment. Each flight uses freshly derived keys from existing information such as PAN ID (Personal Area Network IDentification) and device identities. We formally verified our scheme using the Scyther security protocol verification tool. We simulated and evaluated the proposed LAUP protocol using COOJA simulator and achieved less computational time and low power consumption compared to existing authentication protocols such as the EAKES6Lo and SAKES. LAUP is evaluated using real‐time testbed and achieved less computational time, which is supportive of our simulated results.

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Section: Proposed Workmentioning

confidence: 99%

Testbed evaluation of Lightweight Authentication Protocol (LAUP) for 6LoWPAN wireless sensor networks

Baskaran

Nanda

Nepal

et al. 2018

Concurrency and Computation

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show abstract

“…The study of Hennerbert and Santos [24] shows the application of IoT on the internet to send the data, private information over the web. It is essential to have a security protocol for the transferred data and the unique identities that might be disclosed for them to be made the function with the population of the citizens.…”

Section: Communications On Applied Electronics (Cae) -Issn : 2394-471mentioning

confidence: 99%

Review of Research Approaches for Securing Communication in Internet of Things

Shamshekhar¹,

R.²

2018

CAE

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With the advent of Internet-of-Things (IoT), the communication has become very much ubiquitous with a faster response by supporting pervasive application demands. However, its resistivity towards adversary is still flawed with its existing security techniques. Owing to the novel nature of IoT, there have been various initiating attempts to introduce secure communication schemes for offering better security features to a diverse range of applications in IoT. This paper contributes to discuss existing research trend towards secure communication among the devices in IoT. The discussion present in the paper is anticipated to assists a snapshot of existing methods and approaches to research-based techniques in IoT.

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“…This combination is implemented in the layer 3 of OSI layer. Hennebert and Dos Santos (2014) address the security features of constrained devices. Uses the inbuilt TSCH, DTLS and IP security mode of IEEE 802.15.43 and embedded into 6LoWPAN of OSI Layer.…”

Section: Literature Surveymentioning

confidence: 99%

Power modelling of sensors for IoT using reinforcement learning

Kumar

Krishna

2018

IJAIP

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Internet of things (IoT) is a technology where all things like household equipments, industrial elements, etc. are monitored by sensors and controlled by actuators. For a large scale IoT application, sensors are needed in huge numbers and all these sensors are powered by small battery. Hence, these miniature devices' lifetime can be improved by means of optimising the power and hence modelling of these sensors is a must for such application. This paper models the sensors for IoT application in the multi-layered IoT network. Reinforcement learning is used for modelling the sensors that model in the physical, routing and network layer. EEIT framework is used to model the nodes that optimise energy consumption in physical, routing and network layer. Physical layer modelling deals with the hardware aspects like transmission power, radio, etc. of the sensors. Routing and networking layer deals with the communication (transmitting and receiving data, dissemination, routing, etc.) capabilities of the sensors. We conduct numerical simulations and emulations using EEIT framework for IoT systems that are helpful for the design for complex IoT systems. Our results are quantified empirically based on the facts lifetime of the sensors, energy usage and communication costs.

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Security Protocols and Privacy Issues into 6LoWPAN Stack: A Synthesis

Cited by 125 publications

References 12 publications

Testbed evaluation of Lightweight Authentication Protocol (LAUP) for 6LoWPAN wireless sensor networks

Testbed evaluation of Lightweight Authentication Protocol (LAUP) for 6LoWPAN wireless sensor networks

Review of Research Approaches for Securing Communication in Internet of Things

Power modelling of sensors for IoT using reinforcement learning

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