Main Article Content

pradeepaananthan1973 pradeepa
Dr.M.Parveen Parveen


The idea of the Internet of Things (IoT) has recently received a lot of attention from both businesses and academics. In the IoT, a base station receives data from millions of sensor devices and processes it before using it to build various smart systems, such as the smart grid, smart city, and smart healthcare. To ensure the accuracy of the data gathered, a secure link must be established between base station and sensor devices. The findings of the data analysis will be erroneous and cause much more severe harm if the data that was collected is corrupt. Additionally, due to their extremely low-power computational processors, these IoT devices have a very low level of interactivity. These devices perceive their surroundings, produce data, and transmit the data to the base station through intermediary devices. Using some routing algorithms with the aim of low power consumption, the data is delivered to the base station. Energy efficiency should be taken into account as a crucial performance metric when utilizing low-power IoT devices to create a routing algorithm. Therefore, this paper proposed a secure and energy-efficient data transmission framework (SE-DTF) for IoT. This framework consists of three phases. The first phase is a public and secret key with a token sharing (IoT-PSKTS) algorithm which is used to prevent key leakages in the IoT. The second phase focuses on low power consumption using the Hierarchical Fuzzy Logic Clustering (HFLC) algorithm and Minimum Power Consumption Routing (MPCR) algorithm. The third phase focuses on safe data transfer employing two-tier cryptography with ciphertext shifting and token-based access control, together with HMAC-SHA1 signature. The experimental findings demonstrate how securely the IoT-PSKTS algorithm can share both a public and a secret key with a token. It also demonstrates that the MPCR with the HFLC algorithm outperforms other existing algorithms in terms of throughput, packet delivery ratio, and power utilization. Additionally, it demonstrates that the two-tier cryptography technique uses less energy and requires less computation time for encryption and decryption than other cryptography techniques now in use.

Keywords: Key sharing, clustering, routing, cryptography, access control, signature, and ciphertext shifting

Article Details

How to Cite
pradeepa, pradeepaananthan1973, & Parveen, D. (2024). A SECURE AND ENERGY-EFFICIENT DATA TRANSMISSION FRAMEWORK FOR THE INTERNET OF THINGS. INFOCOMP Journal of Computer Science, 23(1). Retrieved from https://infocomp.dcc.ufla.br/index.php/infocomp/article/view/2449
Network, Communication, Operating Systems, Parallel and Distributed Computing


Affonso, E. T., Nunes, R. D., Rosa, R. L., Pivaro,

G. F., and Rodriguez, D. Z. Speech quality assessment

in wireless voip communication using deep

belief network. IEEE Access, 6:77022–77032,

Affonso, E. T., Rosa, R. L., and Rodriguez, D. Z.

Speech quality assessment over lossy transmission

channels using deep belief networks. IEEE

Signal Processing Letters, 25(1):70–74, 2017.

Amini, S. M. and Karimi, A. Two-level distributed

clustering routing algorithm based on unequal

clusters for large-scale internet of things networks.

The Journal of Supercomputing, 76(3):2158–

, 2020.

Aranzazu-Suescun, C. and Cardei, M. Anchorbased

routing protocol with dynamic clustering

INFOCOMP, v. 23, no. 1, p. pp-pp, June, 2024.

Pradeepa et al.



for internet of things wsns. EURASIP Journal

on Wireless Communications and Networking,

(1):1–12, 2019.

Arshad, M., Almufarreh, A., Jilani, M. T., and

Siddiqu, F. A. A three-tier cluster-based routing

protocol for mobile wireless sensor networks.

Indian Journal of Science and Technology,

(33):3409–3424, 2020.

Asad, M., Aslam, M., Nianmin, Y., Ayoub, N.,

Qureshi, K. I., and Munir, E. U. Iot enabled adaptive

clustering based energy efficient routing protocol

for wireless sensor networks. International

Journal of Ad Hoc and Ubiquitous Computing,

(2):133–145, 2019.

Dantas Nunes, R., Lopes Rosa, R., and Zegarra

Rodríguez, D. Performance improvement of

a non-intrusive voice quality metric in lossy networks.

IET Communications, 13(20):3401–3408,

de Almeida, F. L., Rosa, R. L., and Rodriguez,

D. Z. Voice quality assessment in communication

services using deep learning. In 2018 15th International

Symposium on Wireless Communication

Systems (ISWCS), pages 1–6. IEEE, 2018.

Du, X., Zhou, Z., Zhang, Y., and Rahman, T.

Energy-efficient sensory data gathering based on

compressed sensing in iot networks. Journal of

Cloud Computing, 9(1):1–16, 2020.

Li, J., Silva, B. N., Diyan, M., Cao, Z., and Han,

K. A clustering based routing algorithm in iot

aware wireless mesh networks. Sustainable Cities

and Society, 40:657–666, 2018.

Maheswar, R., Jayarajan, P., Sampathkumar, A.,

Kanagachidambaresan, G., Hindia, M., Tilwari,

V., Dimyati, K., Ojukwu, H., and Amiri, I. S.

Cbpr: A cluster-based backpressure routing for

the internet of things. Wireless Personal Communications,

(4):3167–3185, 2021.

Preeth, S., Dhanalakshmi, R., Kumar, R., and Shakeel,

P. M. An adaptive fuzzy rule based energy

efficient clustering and immune-inspired routing

protocol for wsn-assisted iot system. Journal of

Ambient Intelligence and Humanized Computing,

pages 1–13, 2018.

Raj, K. and Gnanadhas, J. B. Cluster centroidbased

energy efficient routing protocol for wsnassisted

iot. Adv. Sci. Technol. Eng. Syst. J, 5:296–

, 2020.

Rodriguez, D. Z. and Bressan, G. Video quality

assessments on digital tv and video streaming services

using objective metrics. IEEE Latin America

Transactions, 10(1):1184–1189, 2012.

Rodriguez, D. Z. and Junior, L. C. B. Determining

a non-intrusive voice quality model using machine

learning and signal analysis in time. INFOCOMP

Journal of Computer Science, 18(2), 2019.

Rodríguez, D. Z., Rosa, R. L., Almeida, F. L., Mittag,

G., and Möller, S. Speech quality assessment

in wireless communications with mimo systems

using a parametric model. IEEE Access, 7:35719–

, 2019.

Sankar, S. and Srinivasan, P. Multi-layer cluster

based energy aware routing protocol for internet

of things. Cybern. Inf. Technol, 18(3):75–92,

Shukla, A. and Tripathi, S. A multi-tier based

clustering framework for scalable and energy efficient

wsn-assisted iot network. Wireless Networks,

(5):3471–3493, 2020.

Sujanthi, S. and Nithya Kalyani, S. Secdl: Qosaware

secure deep learning approach for dynamic

cluster-based routing in wsn assisted iot. Wireless

Personal Communications,