A lightweight physical-layer based security strategy for Internet of things

Jiang, Yu; Hu, Aiqun; Huang, Jie

doi:10.1007/s10586-018-1820-0

Cited by 8 publications

(7 citation statements)

References 38 publications

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“…The nodes mobility problem has been scrutinized so that the recommended solution has an appropriate performance in portable environments [14]. Their security mechanism is founded on the reliance concept.…”

Section: Detection Schemesmentioning

confidence: 99%

Securing Internet of Things against Physical Layer Attacks Using Hybrid Security Algorithm (HSA)

M¹

2020

Preprint

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Through the Internet of Things (IoT) the internet scope is established by the aid of physical objects integration to classify themselves to mutual things. A physical object can be created by this inventive perception to signify itself in the digital world. Regarding the physical objects that are related to the internet, it is worth to mention that considering numerous theories and upcoming predictions, they mostly require protected structures, moreover, they are at risk of several attacks. IoTs are endangered by particular routing disobedience called physical layer attack owing to their distributed features. The physical layer attack as a security warning makes possible for the invader to abuse the resources and bandwidth of the network through overloading the network via unimportant packets. This protocol is called LSFA-IoT consisting of two key sections of the physical layer detection system and misbehavior detection system. The first section is utilized in stabilizing the status of the network. The second section is in charge of discovering the misbehavior sources within the IoT network through , the Average Packet Transmission RREQ. By detecting a malicious node, the status of the node is checked by LSFA-IoT prior to sending a data packet and in case detecting the node as malicious, no packet is sent to that node and that node is added to the detention list. Here, the technique is assessed through wide simulations performed within the NS-3 environment. Based on the results of the simulation, it is indicated that the IoT network behaviour metrics are enhanced based on the detection rate, false-negative rate, false-positive rate, and packet delivery rate.

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Section: Detection Schemesmentioning

confidence: 99%

Securing Internet of Things against Physical Layer Attacks Using Hybrid Security Algorithm (HSA)

M¹

2020

Preprint

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“…The other studies use a key generation system consisting of four phases [40,41,42]. These phases include the measurement of channel characteristics, quantization, error-correcting, and privacy amplification.…”

Section: Key Generation System Overviewmentioning

confidence: 99%

“…We propose the SSE system as a key generation system that consists of three phases, i.e., measurement of channel characteristics, quantization, and privacy amplification as shown in Figure 3. The system is simpler when compared to existing systems [24,25,26,27,28,29,32,40,41,42], so it is expected to be able to reduce computing time, communication overhead and suitable for IoT devices with limited computing resources. We claim that our proposed key generation system is simpler in terms of the number of phases that must be passed.…”

Section: Sse Systemmentioning

confidence: 99%

An Efficient Key Generation for the Internet of Things Based Synchronized Quantization

Yuliana

Wirawan

Suwadi

2019

Sensors

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One solution to ensure secrecy in the Internet of Things (IoT) is cryptography. However, classical cryptographic systems require high computational complexity that is not appropriate for IoT devices with restricted computing resources, energy, and memory. Physical layer security that utilizes channel characteristics is an often used solution because it is simpler and more efficient than classical cryptographic systems. In this paper, we propose a signal strength exchange (SSE) system as an efficient key generation system and a synchronized quantization (SQ) method as a part of the SSE system that synchronizes data blocks in the quantization phase. The SQ method eliminates the signal pre-processing phase by performing a multi-bit conversion directly from the channel characteristics of the measurement results. Synchronization is carried out between the two authorized nodes to ensure sameness of the produced keys so it can eliminate the error-correcting phase. The test results at the IoT devices equipped with IEEE 802.11 radio show that SSE system is more efficient in terms of computing time and communication overhead than existing systems.

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“…Learn from lightweight encryption in cryptography, some researches about lightweight security have been from upper‐layer to physical layer recently. Jiang et al [22] have discussed the lightweight PLS techniques for IoT, which emphasised authentication and secrete key generation. Meucci et al [23] proposed a lightweight security mechanism by a dynamic subcarrier permutation in the cognitive orthogonal frequency division multiple access system.…”

Section: Introductionmentioning

confidence: 99%