CP-ABE encryption over MQTT for an IoT system with Raspberry Pi

Mendoza-Cardenas, Fredy; Leon-Aguilar, Rai Stiv; Quiroz-Arroyo, Jose Luis

doi:10.1109/ciss53076.2022.9751194

Cited by 6 publications

(3 citation statements)

References 3 publications

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“…A new Raspberry Pi kit, recently introduced, is used to invoke recent AI models at small scalability, power consuming, speed, and cost [21]. This new version is Raspberry Pi 4 model B, with 8 GB memory shown in Figure 2.…”

Section: Hardware Components 251 Raspberry Pi 4 Model B and Secure Di...mentioning

confidence: 99%

Real-time multiple face mask and fever detection using YOLOv3 and TensorFlow lite platforms

Abed

Al-Ibadi²,

Abed³

2023

Bulletin EEI

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COVID-19 has caused disruptions to many aspects of everyday life. To reduce the impact of this pandemic, its spreading must be controlled via face mask wearing. Manually mask-checking for everybody is embarrassing and uncontrollable. Hence, the proposed technique is used to help for automatic mask-checking based on deep learning platforms with real-time surveillance live infra-red (IR) camera. In this paper, two recent object detection platforms, named, you only look once version 3 (YOLOv3) and TensorFlow lite are adopted to accomplish this task. The two models are trained with a dataset consisting of images of persons with/without masks. This work is simulated with Google Colab then tested in real-time on an embedded device mated with fast GPU called Raspberry Pi 4 model B, 8 GB RAM. A comparison is made between the two models to verify their performance in relation to their precision rate and processing time. The work of this paper is also succeeded to realize multiple face masks real-time detection up to 10 facemasks in a single scene with high inference speed. Temperature is also measured using IR touchless sensor for each person with sound alarming to alert fever. The presented detector is cheap, light, small, and fast, with 99% accuracy rate during training and testing.

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Section: Hardware Components 251 Raspberry Pi 4 Model B and Secure Di...mentioning

confidence: 99%

Real-time multiple face mask and fever detection using YOLOv3 and TensorFlow lite platforms

Abed

Al-Ibadi²,

Abed³

2023

Bulletin EEI

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“…Additionally, as the number of attributes increases, the private key's length and the communication delay increase significantly. Mendoza-Cardenas et al [17] intended to evaluate the performance of MQTT with CP-ABE to its adoption in an IoT environment. Wang et al [29] developed a Dual-Policy-Attribute-Based Encryption model (DP-ABE) that allows two access control strategies and ensures high security in cloud scenarios.…”

Section: Imdad Et Al [26]mentioning

confidence: 99%

“…Attribute-Based Encryption (ABE) [15] is commonly used in IoT solutions. However, traditional access control solutions require encryption of IoT data using the Ciphertext Policy-Attribute-Based Encryption (CP-ABE) scheme, and only users who conform to the access control policy can decrypt the encrypted information received [16,17]. ABE schemes usually involve high computational complexity and are challenging to implement in resource-limited wireless sensors with limited power and computational capacity.…”

Section: Introductionmentioning

confidence: 99%

On the Efficiency of a Lightweight Authentication and Privacy Preservation Scheme for MQTT

2023

Electronics

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The Internet of Things (IoT) deployment in emerging markets has increased dramatically, making security a prominent issue in IoT communication. Several protocols are available for IoT communication; among them, Message Queuing Telemetry Transport (MQTT) is pervasive in intelligent applications. However, MQTT is designed for resource-constrained IoT devices and, by default, does not have a security scheme, necessitating an additional security scheme to overcome its weaknesses. The security vulnerabilities in MQTT inherently lead to overhead and poor communication performance. Adding a lightweight security framework for MQTT is essential to overcome these problems in a resource-constrained environment. The conventional MQTT security schemes present a single trusted scheme and perform attribute verification and key generation, which tend to be a bottleneck at the server and pave the way for various security attacks. In addition to that, using the same secret key for an extended period and a flawed key revocation system can affect the security of MQTT. To address these issues, we propose an Improved Ciphertext Policy-Attribute-Based Encryption (ICP-ABE) integrated with a lightweight symmetric encryption scheme, PRESENT, to improve the security of MQTT. In this work, the PRESENT algorithm enables the secure sharing of blind keys among clients. We evaluated a previously proposed ICP-ABE scheme from the perspective of energy consumption and communication overhead. Furthermore, we evaluated the efficiency of the scheme using provable security and formal methods. The simulation results showed that the proposed scheme consumes less energy in standard and attack scenarios than the simple PRESENT, Key Schedule Algorithm (KSA)-PRESENT Secure Message Queue Telemetry Transport (SMQTT), and ECC-RSA frameworks, with a topology of 30 nodes. In general, the proposed lightweight security framework for MQTT addresses the vulnerabilities of MQTT and ensures secure communication in a resource-constrained environment, making it a promising solution for IoT applications in emerging markets.

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