Journal of Intelligent Systems and Internet of Things
JISIoT
2690-6791
2769-786X
10.54216/JISIoT
https://www.americaspg.com/journals/show/3705
2019
2019
Deep Learning-based sensitive data detection with optimization-enabled secure encryption model for data privacy preservation in IoT
University Institute of Computing, Department of Computer Applications, Chandigarh University, Punjab, India
Mathias
Mathias
University Institute of Computing, Department of Computer Applications, Chandigarh University, Punjab, India
Disha
Handa
The express expansion of the Internet of Things (IoT) has led to an exponential increase for data being generated and transmitted from various connected devices. This poses significant challenges in terms of data privacy and security, as unauthorized access to such sensitive information can have severe consequences like identity theft or financial fraud. This research proposes a model for sensitive data detection and protection in IoT, based on deep learning and optimization-enabled secure encryption. By combining deep learning-based sensitive data detection and optimization-enabled secure encryption, this model offers a comprehensive solution to preserve data privacy in IoT. The proposed model uses a novel and secure encryption algorithm, ensuring the privacy of the data. An algorithm, Improved Skill Optimization Algorithm (ISOA), which enhances the performance of existing optimization algorithms by incorporating the concept of Double Exponential Smoothing (DES), is proposed for the secure key generation for the data encryption. Data Encryption Standard (DES) is a block cipher algorithm that encrypts and decrypts data using a 56-bit key and 64-bit blocks. The proposed model provides a robust solution for data privacy preservation in IoT networks, which is crucial for protecting sensitive information from unauthorized access and data breaches. The proposed algorithm's performance analysis is evaluated using metrics, like computation time, memory, and fitness function. Results indicate that proposed ISOA based encryption model succeeded a greater performance, with a memory of 0.5170 MB, computational time of 1126.47 sec and fitness value of 1.3630.
2025
2025
142
157
10.54216/JISIoT.160211
https://www.americaspg.com/articleinfo/18/show/3705