Secure Event-triggered MolecularvCommunication - Information Theoretic Perspective and Optimal Performance

2025-12-18

AI Summary

This paper addresses two critical challenges in in vivo molecular communication (MC): energy inefficiency and security vulnerabilities under event-driven scenarios. To overcome hardware and energy limitations of the Shannon transmission paradigm at the nanoscale, we propose Randomized Identification (RI) and Secure Randomized Identification (SRI) paradigms based on the discrete-time Poisson channel. We establish, for the first time, the capacity theory of SRI in MC, revealing its double-exponential coding gain. Closed-form analytical expressions for the capacities of both RI and SRI are derived. We prove that high-reliability event detection is achievable with an extremely low number of emitted molecules, and rigorously quantify the eavesdropping-resilient security boundary. This work bridges information-theoretic identification frameworks with bio-information security, laying a theoretical foundation for ultra-low-power, high-security in vivo nanonetworks.

Technology Category

• Machine Learning: Information Theory
• Multiagent Systems: Agent Communication
• Cognitive Modeling & Cognitive Systems: Neural Spike Coding

Application Category

• Security and Privacy: Large-scale security measurements
• Systems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environments
• User Modeling, Personalization and Recommendation: Attacks and countermeasures in recommendation systems

Abstract

Molecular Communication (MC) is an emerging field of research focused on understanding how cells in the human body communicate and exploring potential medical applications. In theoretical analysis, the goal is to investigate cellular communication mechanisms and develop nanomachine-assisted therapies to combat diseases. Since cells transmit information by releasing molecules at varying intensities, this process is commonly modeled using Poisson channels. In our study, we consider a discrete-time Poisson channel (DTPC). MC is often event-driven, making traditional Shannon communication an unsuitable performance metric. Instead, we adopt the identification framework introduced by Ahlswede and Dueck. In this approach, the receiver is only concerned with detecting whether a specific message of interest has been transmitted. Unlike Shannon transmission codes, the size of identification (ID) codes for a discrete memoryless channel (DMC) increases doubly exponentially with blocklength when using randomized encoding. This remarkable property makes the ID paradigm significantly more efficient than classical Shannon transmission in terms of energy consumption and hardware requirements. Another critical aspect of MC, influenced by the concept of the Internet of Bio-NanoThings, is security. In-body communication must be protected against potential eavesdroppers. To address this, we first analyze the DTPC for randomized identification (RI) and then extend our study to secure randomized identification (SRI). We derive capacity formulas for both RI and SRI, providing a comprehensive understanding of their performance and security implications.

Problem

• Analyzes secure event-triggered molecular communication using identification frameworks.
• Derives capacity formulas for randomized and secure randomized identification in Poisson channels.
• Addresses energy efficiency and security against eavesdroppers in in-body nanomachine communication.

Innovation

• Using identification codes for event-driven molecular communication
• Applying randomized encoding for secure in-body communication
• Deriving capacity formulas for secure randomized identification