Skip to main content
AkademIndex

Products

For developers

AkademBasesoonOpen API for the ecosystem
Latin
English
Article

Lightweight ECC-Based Cryptographic Protocol Using Montgomery Ladder for Wearable Health Devices

Muhidinov Ayubbek NuritdinovichTuran International University,Namangan,UzbekistanZainab Ali NasirAl-Nisour University College,Nisour Seq. Karkh,Baghdad,IraqM S M HashimAl-Manara College For Medical Sciences,Department of Sciences,Maysan,IraqRuhab Abd AlhusseinAl-Zahrawi University College,Karbala,IraqSarah Salah JalalNational University of Science and Technology,Collage of Nursing,Dhi Qar, 64001,IraqHassan Mohammed AbedComputer Techniques Engineering Mazaya University College,Iraq
2025en
ABI

Abstract

Wearable health devices are becoming more popular for constant health tracking and real-time data transmission, which requires lightweight and secure cryptographic solutions. Traditional security protocols are not always viable due to the constrained computational power and limited battery life of such devices. Most cryptographic schemes used in wearable devices have poor computational efficiency, high energy consumption, and susceptibility to side-channel attacks, particularly the scalar multiplication step in elliptic curve operations. To overcome these challenges, this paper introduces the Montgomery Ladder Optimized ECC (MLO-ECC) Protocol for Secure Health Data Transmission. This light-weight cryptographic scheme combines Elliptic Curve Cryptography (ECC) with the Montgomery Ladder method to achieve constant-time and efficient scalar multiplication, which substantially minimizes the vulnerability to timing and power analysis attacks. The introduced MLO-ECC technique is implemented in secure data transmission between wearable health devices and remote healthcare servers. Analysis of the new MLO-ECC protocol reveals an improvement in performance and security compared to traditional ECC-based solutions. The technique exhibits lower processing time, energy consumption, and resistance to side-channel attacks, making it well-suited for implementation in future wearable healthcare systems.

Topics

Identifiers

Citations and references

Cited by 013 references
Metrics — AkademScholar · Coming soon