Vol.:(0123456789) Wireless Networks https://doi.org/10.1007/s11276-024-03783-5 ORIGINAL PAPER An adaptive secure internet of things and cloud based disease classification strategy for smart healthcare industry Ankit Verma 1,2  · Gaurav Agarwal 2  · Amit Kumar Gupta 3  · Vipin Kumar 3  · Shweta Singh 3 Accepted: 24 May 2024 © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024 Abstract Hospital facilities were limited in rural areas and there is no awareness about disease infection and so on. Hence, the Internet of Things (IoT) technology was designed in the health care industry to treat and save illiterate people from the harmful dis- eases. Recently, the health care system based on IoT technology became a huge demand in the online and medical industry. However, offering the protection frame for gathered data in cloud becomes a challenging task, because the cloud contains a lot of different patient data. To overcome this issue, the current research has designed a novel Elapid Encryption in cloud frame to secure the gathered data. Moreover, the security function is executed by encrypting the collected information in the cloud storage. Also, a novel generalized fuzzy intelligence and ant lion optimization model was developed for disease prediction and severity calculation. Hence, the developed design is implemented using MATLAB and its efficiency is compared with the existing approaches such as H-DT, DNN, and DTNNN. From the comparison, proposed model has fin- est and highest performance like high accuracy, precision, recall and confidential rate then lower error rate and processing time. Consequently, AUC value by the developed model is 89.8%, sensitivity rate as 99% and specificity rate as 97.8%, less error rate as 0.08, accuracy rate as 99.92% and 99.9% of precision, high recall measure as 99.92%, time consumption of the proposed model is 10 s. Keywords Healthcare system · IoT · Cloud storage · Disease classification · Severity analysis Abbreviations IoT Internet of Things EE Elapid encryption GFI-ALO Generalized fuzzy intelligence and ant lion optimization DoS Denial of service ALO Ant lion optimization AUC Area under curve H-DT Hybrid–decision tree DNN Deep neural network DTNNN Deep trained neocognitron neural network DESRP Data encryption standard based register permutation ESV-AES Enhanced-Small Scale Variant with Advanced Encryption Standard EBA Enhanced Blowfish Algorithm 1 Introduction The great success of IoT technology is successfully appli- cable in all application namely consumer appliance [1], enterprise applications, infrastructure [2], smart home, manufacturing, agriculture, energy management [3, 4], environmental observing, home automation building, cos- mopolitan dispositions [5], old age care, medicinal health care tenders and so on. Considering these all application, health care and medicinal scheme [6, 7] is the vital part in IoT because it assists to screen the people strength and spare the warning procedure such as blood pressure varia- tions [8], heart rate fluctuations, hearing aids and so on [9, 10]. Thus IoT gadgets are effectively utilized to observing the people health; also, it is more helpful for the people who lived in rural areas [11] because, in rural areas, the peoples are not aware about the medical and healthcare * Ankit Verma ankit.mca4u@gmail.com 1 Department of Computer Applications, KIET Group of Institutions, Ghaziabad, Uttar Pradesh 201206, India 2 Department of Computer Science & Engineering, Invertis University, Bareilly, Uttar Pradesh 243123, India 3 Department of Computer Applications, KIET Group of Institutions, Delhi-NCR, Ghaziabad, India