Synergizing Measurement Science and Artificial Intelligence in Smart Agriculture

Lamonaca, Francesco; Carnì, Domenico Luca

doi:10.1109/bigdata59044.2023.10386623

Cited by 1 publication

(1 citation statement)

References 71 publications

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“…With the proliferation of Internet of Things (IoT) devices, safeguarding sensitive data has become paramount. As highlighted by the recent literature [1], many of these data are measurements, and the IoT paradigm is the basis of modern distributed measurement systems (DMSs), used for the monitoring of many heterogeneous physical quantities, crucial for wellness [2,3], industrial automation, education, power generation and distribution, smart agriculture, and farming [4,5], but also for the safety of people [6][7][8] and structures [9]. The cyber security company Check Point Research has reported a significant surge in cyber attacks targeting IoT devices during the current calendar year.…”

Section: Introductionmentioning

confidence: 99%

A Performance Analysis of Security Protocols for Distributed Measurement Systems Based on Internet of Things with Constrained Hardware and Open Source Infrastructures

Gentile,

Macrì,

Carnì

et al. 2024

Sensors

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The widespread adoption of Internet of Things (IoT) devices in home, industrial, and business environments has made available the deployment of innovative distributed measurement systems (DMS). This paper takes into account constrained hardware and a security-oriented virtual local area network (VLAN) approach that utilizes local message queuing telemetry transport (MQTT) brokers, transport layer security (TLS) tunnels for local sensor data, and secure socket layer (SSL) tunnels to transmit TLS-encrypted data to a cloud-based central broker. On the other hand, the recent literature has shown a correlated exponential increase in cyber attacks, mainly devoted to destroying critical infrastructure and creating hazards or retrieving sensitive data about individuals, industrial or business companies, and many other entities. Much progress has been made to develop security protocols and guarantee quality of service (QoS), but they are prone to reducing the network throughput. From a measurement science perspective, lower throughput can lead to a reduced frequency with which the phenomena can be observed, generating, again, misevaluation. This paper does not give a new approach to protect measurement data but tests the network performance of the typically used ones that can run on constrained hardware. This is a more general scenario typical for IoT-based DMS. The proposal takes into account a security-oriented VLAN approach for hardware-constrained solutions. Since it is a worst-case scenario, this permits the generalization of the achieved results. In particular, in the paper, all OpenSSL cipher suites are considered for compatibility with the Mosquitto server. The most used key metrics are evaluated for each cipher suite and QoS level, such as the total ratio, total runtime, average runtime, message time, average bandwidth, and total bandwidth. Numerical and experimental results confirm the proposal’s effectiveness in foreseeing the minimum network throughput concerning the selected QoS and security. Operating systems yield diverse performance metric values based on various configurations. The primary objective is identifying algorithms to ensure suitable data transmission and encryption ratios. Another aim is to explore algorithms that ensure wider compatibility with existing infrastructures supporting MQTT technology, facilitating secure connections for geographically dispersed DMS IoT networks, particularly in challenging environments like suburban or rural areas. Additionally, leveraging open firmware on constrained devices compatible with various MQTT protocols enables the customization of the software components, a crucial necessity for DMS.

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