TY  - EJOU
AU  - Kebache, Romaissa 
AU  - Laouid, Abdelkader 
AU  - Bounceur, Ahcene 
AU  - Kara, Mostefa 
AU  - Karampidis, Konstantinos 
AU  - Papadourakis, Giorgos 
AU  - Hammoudeh, Mohammad 

TI  - Reducing the Encrypted Data Size: Healthcare with IoT-Cloud Computing Applications
T2  - Computer Systems Science and Engineering

PY  - 2024
VL  - 48
IS  - 4
SN  - 

AB  - Internet cloud services come at a price, especially when they provide top-tier security measures. The cost incurred by cloud utilization is directly proportional to the storage requirements. Companies are always looking to increase profits and reduce costs while preserving the security of their data by encrypting them. One of the offered solutions is to find an efficient encryption method that can store data in a much smaller space than traditional encryption techniques. This article introduces a novel encryption approach centered on consolidating information into a single ciphertext by implementing Multi-Key Embedded Encryption (MKEE). The effectiveness of MKEE scales in tandem with the volume of information encapsulated within the ciphertext. MKEE substantially reduced the size of the ciphertext, achieving an 88% decrease when incorporating ten plaintext values. To further reduce the size of the ciphertext in our proposal, a Modular Multiplicative Inverse method (MMI) is introduced. MMI experiments were conducted, demonstrating that we achieved a commendable 50% reduction in the ciphertext size. To validate the practicality of the proposed method, a case study was conducted on a diabetes dataset. By integrating MKEE and MMI, this study showed a data storage reduction of 94%.
KW  - Encryption; ciphertext size; security; privacy; patient data

DO  - 10.32604/csse.2024.048738