Healthcare Technology
Lightweight signcryption scheme for Securing wearable sensor observed health data sharing in internet of medical things paradigm
The Internet of Medical Things (IoMT) plays a crucial role in enabling precision diagnosis and optimal recommendations for patients monitored remotely. However, conventional encryption-signature mechanisms introduce significant computational and communication overhead, making them unsuitable for resource-constrained IoMT devices that require secure and real-time transmission of health vitals. To address this gap, this article proposes a lightweight signcryption scheme tailored explicitly for IoMT data security.
Executive Impact
Our proposed lightweight signcryption scheme offers tangible benefits for IoMT data security and operational efficiency.
0%
Improved Detection Accuracy
0%
Reduced Service Failures
0ms
Computational Time Savings (Avg.)
Deep Analysis & Enterprise Applications
Select a topic to dive deeper, then explore the specific findings from the research, rebuilt as interactive, enterprise-focused modules.
Problem Statement
The Internet of Medical Things (IoMT) enables real-time health monitoring and remote diagnosis via networked devices. Still, it introduces a significant challenge regarding data confidentiality, integrity, and availability in resource-constrained settings. Traditional cryptographic and authentication approaches consume excessive latency and processing overhead, which is inappropriate for IoMT platforms where lightweight processing and efficiency are paramount. Secondly, attacks such as replay attacks, tampering, and unauthorized access compromise patient safety and system reliability. Thus, an adaptive, lightweight, and privacy-preserving security architecture is required that maximizes simplicity while providing adequate security for sensitive medical information during real-time transmission and sharing.
Research Methodology
This work proposes a lightweight triple-truncated DES signcryption scheme with CNN-activated verification for IoMT applications. The procedure consists of three key steps: (i) observation filtering and structuring into continuous sequences of sensor observations using preparation, (ii) embracing an advanced triple-DES-based signcryption with truncation to facilitate secure yet low-complexity signing and sharing, and (iii) decryption with truncated keys and CNN-enabled integrity verification. The suggested approach is empirically evaluated on a synthetic health-monitoring data set, comparing data extraction efficiency, computational complexity, and accuracy with those of existing state-of-the-art methods. The main contributions of this research can be summarized as follows:
- To design an efficient and lightweight signcryption scheme for IoMT healthcare data security, utilizing triple-truncated DES.
- To incorporate CNN-based verification for anomaly detection and integrity checking with negligible overhead.
- To minimize computational complexity using the transformation of traditional triple DES to a truncated form to make it easier for key management.
- To provide better performance, with improved detection accuracy, reduced service failures, and enhanced processing speed compared to the current ones.
- To extend the scheme's applicability to broader resource-constrained cyber-physical domains beyond IoMT.
Related Works
To address healthcare data security challenges, Ali et al. proposed a lightweight, secure IoMT authentication scheme. The algorithm used multi-factor authentication based on a secure algorithm to be implemented in healthcare monitoring systems. The solution offers more security against impersonation and man-in-the-middle attacks. The approach has minimal processing and transmission overheads, promoting data security and privacy in smart health systems. Chen et al. proposed a certificate-less encryption scheme for healthcare use. The method uses Schnorr signatures to secure IoMT data delivery. The technique provides confidentiality, authenticity, and unforgeability, while also saving computing costs. The process is more secure and efficient compared to other systems.
95.6%
Highest Accuracy Achieved (Proposed ECOA + MSBi-GRU + attention)
The proposed ECOA + MSBi-GRU with self-attention model achieved the highest accuracy on the UCI IoT/IoMT intrusion detection dataset, demonstrating superior performance over baseline deep learning models.
Lightweight Signcryption Scheme Process Flow
The proposed scheme involves a three-stage process to ensure secure and efficient data sharing in IoMT environments.
Data Preparation (Observation Filtering & Structuring)
→
Triple-DES Signcryption (Truncated Keys)
→
Decryption & CNN-Enabled Integrity Verification
| Method | Signing/Decryption Complexity (ms) | Detection Accuracy (%) | Key Limitations |
|---|---|---|---|
| Certificateless signcryption | ~29 | 91.8 |
|
| Chaotic mapping + blockchain | 40+ | 92.1 |
|
| AutoPro-RHC (FHE) | 31-41 | 90.5 |
|
| Blockchain + FL | 36-44 | 92.3 |
|
| Lightweight signcryption (Proposed) | 24-32 | 94.4 |
|
Real-world Application: Secure Remote Patient Monitoring
The proposed scheme is designed to address critical security and efficiency challenges in real-world IoMT applications like remote patient monitoring.
Challenge: Resource-constrained wearable sensors in IoMT require secure, real-time data transmission without significant computational or communication overhead.
Solution: Implementation of a lightweight triple-truncated DES signcryption scheme with CNN-based verification for anomaly detection and integrity checking.
Result: Improved detection accuracy by 14.12%, reduced service failures by 13.67%, and significant computational time savings compared to baseline schemes, ensuring robust data protection in adversarial environments.
Calculate Your Potential AI-Driven ROI
Estimate the cost savings and efficiency gains your organization could achieve by implementing intelligent automation and secure data handling systems.
Estimated Annual Cost Savings
$0
Estimated Annual Hours Reclaimed
0 Hours
Your AI Implementation Roadmap
A typical phased approach to integrate our lightweight signcryption solutions into your enterprise IoMT infrastructure.
Phase 1: Assessment & Strategy
Detailed analysis of existing IoMT infrastructure, security needs, and data flow. Development of a tailored implementation strategy and security policy.
Phase 2: Pilot Deployment & Integration
Deployment of the lightweight signcryption scheme in a controlled environment, integrating with a subset of IoMT devices and health systems. Initial performance tuning.
Phase 3: Full-Scale Rollout & Optimization
Phased rollout across the entire IoMT network. Continuous monitoring, performance optimization, and advanced threat detection tuning with CNN verification.
Phase 4: Ongoing Support & Evolution
Provision of continuous support, regular security audits, and adaptation to evolving threats and new IoMT device integrations.
Ready to Secure Your IoMT Data?
Safeguard sensitive medical information, reduce operational overhead, and ensure compliance with our state-of-the-art lightweight signcryption. Schedule a free consultation to discuss how our solution can be tailored for your enterprise.
Ready to Get Started?
Book Your Free Consultation.
Let's Discuss Your AI Strategy!
Lets Discuss Your Needs
Select a Date
Sun
Mon
Tue
Wed
Thu
Fri
Sat