Security and Privacy in IoT: A Survey

Chanal, Poornima M.; Kakkasageri, Mahabaleshwar S.

doi:10.1007/s11277-020-07649-9

Cited by 160 publications

(55 citation statements)

References 65 publications

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“…In [17] an extensive survey on the security, privacy and authentication challenges in internet of things confirmed the fact that although there have been. improvement in the design and development of cryptographic solutions tailored for the individual elements within IoT, there is equally an increase in the number of exploitation of attacks in recent times.…”

Section: Internet-of-things Securitymentioning

confidence: 93%

Node-Node Data Exchange in IoT Devices Using Twofish and DHE

Asare¹,

Kester²,

Nana³

2021

Adv. sci. technol. eng. syst. j.

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Internet of Things provides the support for devices, people and things to collaborate in collecting, analyzing and sharing sensitive information from one device onto the other through the internet. The internet of things is thriving largely due to access, connectivity, artificial intelligence and machine learning approaches that it supports. The stability and enhanced speed of the internet is also attributable to the huge adoption rate that IoT continues to enjoy from Governments, industry and academia in recent times. The increased incidences of cyber-attacks on connected systems in recent times, has inspired the heightened efforts from Governments, industry practitioners and the research world towards improving existing approaches and the engineering of new innovative schemes of securing devices, the software or the platforms for the deployment of IoT. Security solution for Internet of things includes the use of secure ciphers and key exchange algorithms that ensures the provisioning of a security layer for the: devices or hardware, communication channels, cloud, and the life cycle management constituting the Internet of things. The use of key exchange algorithms in resilient cryptographic solution that have less computational requirements without compromising the security efficiency in the encryption of messages for IoT continues to be the preferred approach in securing messages in a node-node exchange of data. This paper aims at providing a cryptographic solution that uses a key exchange cryptographic primitive and a strong cipher in encrypting messages for exchange between nodes in an IoT. Towards achieving this goal, the Diffie-Hellman key exchange (DHE) protocol was used to provide a secure key exchange between the communicating nodes, whiles the Twofish block cipher was used in the encryption and decryption of messages, assuring the security, privacy and integrity of messages in a node-node IoT data exchange. The cryptographic solution has a high throughput.

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Section: Internet-of-things Securitymentioning

confidence: 93%

Node-Node Data Exchange in IoT Devices Using Twofish and DHE

Asare¹,

Kester²,

Nana³

2021

Adv. sci. technol. eng. syst. j.

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“…The ranking algorithms for sensors with sensory feedback mechanisms present in IoT are CAS-SARAM in which the user selects the sensor attributes and inputs the weights of each sensor attribute to ensure that their sum is 1, and then, the Euclidean distance algorithm is used for the ranking calculation, which is ranked according to the distance; the algorithm is simple but loses some accuracy; in literature [16], AHP is used for the weighting of relatively several sensor attributes for normalized calculation of weighted scores for dependencies among sensor nodes, etc., in the underlying IoT and ranking according to the size of the scores; literature [17] proposed a similarity comparison ranking algorithm to compare the similarity of the output data of a given sensor over some time with the user search output data for ranking. The literature [18] proposed a prediction using statistical data from the past period, and the search and prediction model helps to find the matching sensors retrieved with the minimum number of sensor data.…”

Section: Application Of Sensor Technologymentioning

confidence: 99%

Perceptual Feedback Mechanism Sensor Technology in e‐Commerce IoT Application Research

Guo

Liang

2021

Journal of Sensors

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With the development of sensor technology and the Internet of Things (IoT) technology, the trend of miniaturization of sensors has prompted the inclusion of more sensors in IoT, and the perceptual feedback mechanism among these sensors has become particularly important, thus promoting the development of multiple sensor data fusion technologies. This paper deeply analyzes and summarizes the characteristics of sensory data and the new problems faced by the processing of sensory data under the new trend of IoT, deeply studies the acquisition, storage, and query of sensory data from the sensors of IoT in e-commerce, and proposes a ubiquitous storage method for massive sensory data by combining the sensory feedback mechanism of sensors, which makes full use of the storage resources of IoT storage network elements and maximally meets the massive. In this paper, we propose a ubiquitous storage method for massive sensing data, which makes full use of the storage resources of IoT storage network elements to maximize the storage requirements of massive sensing data and achieve load-balanced data storage. In this paper, starting from the overall development of IoT in recent years, the weak link of intelligent information processing is reinforced based on the sensory feedback mechanism of sensor technology.

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“…Apparent temperature (AT) is calculated based on temperature (T), relative humidity (RH), water pressure (e) and wind speed (V) according to formulas (4-1) and (4-2) [31]. 8 User interface in App-3…”

Section: Fig 6 Uart Connectionmentioning

confidence: 99%

Development and Verification of an IoT-Enabled Air Quality Monitoring System Based on Petri Nets

Lin

Wang

Chiou

et al. 2021

Preprint

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An IoT (Internet of Things) system for monitoring campus environmental parameters was successfully developed in this study. Various sensors were adopted in the front of IoT system for sensing air pollutants. The architecture of LongRange (LoRa) in Class C uses low-power and long-distance transmission technologies, which has been set up on the large campus, so that the terminal equipment can reach a balance between downlink latency and battery life, making it the best transmission communication protocol. In addition, this monitoring system uses the Petri net software tool to build a correct IoT platform based on the fundamental working processes, and to demonstrate the feasibility of the IoT system through simulation-based verification. Finally, the experimental results have shown that the IoT system for monitoring the campus environmental parameters achieves the goal of an acceptable data transmission success rate of more than 95%. Thus, it can facilitate the air quality trends for policy making as well as the hazardous prediction and prevention.

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Security and Privacy in IoT: A Survey

Cited by 160 publications

References 65 publications

Node-Node Data Exchange in IoT Devices Using Twofish and DHE

Node-Node Data Exchange in IoT Devices Using Twofish and DHE

Perceptual Feedback Mechanism Sensor Technology in e‐Commerce IoT Application Research

Development and Verification of an IoT-Enabled Air Quality Monitoring System Based on Petri Nets

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