In the ever-evolving landscape of wireless communication, security remains a paramount concern. A recent study published in Engineering delves into the realm of intelligent covert communication, exploring its latest advancements and future research trends.
Covert communication, also known as low probability of detection (LPD) communication, is a technique that aims to conceal the existence of communication, thereby safeguarding private information. As the volume of private data transmitted via wireless systems continues to soar in the big data era, the need for robust security measures has become more pressing than ever. Unlike traditional encryption and physical layer security techniques, covert communication focuses on hiding the communication behavior itself, adding an extra layer of protection.
The researchers first introduced the basic concepts and performance metrics of covert communication. A typical system model involves a sender (Alice) transmitting data to a recipient (Bob) without being detected by an adversary (Willie). Performance is measured through metrics such as error detection probability, detection probability, covert outage probability, and effective covert rate. These metrics help in evaluating the effectiveness of covert communication systems and designing better strategies.
The paper then reviewed existing covert communication techniques across different domains. In the time domain, random time-slot selection and time-hopping techniques add an element of randomness to evade detection, although they come with issues like increased transmission delay. Frequency domain techniques, such as spread spectrum and frequency-hopping, reduce the signal power density, making it harder for eavesdroppers to detect the signal. However, they face limitations due to spectrum resources and receiver sensitivity.
Spatial domain technologies, including beamforming, millimeter wave, terahertz communication, and frequency diverse array (FDA), enhance covertness by controlling signal propagation direction and leveraging the unique properties of high-frequency waves. In the power domain, power adaption and artificial noise methods introduce uncertainty to prevent detection, but they pose challenges for legitimate receivers. In the modulation domain, random modulation schemes and waveform overlay techniques improve covertness, with optimal probabilistic constellation shaping further enhancing the covert rate.
Looking ahead, the study identified several future research directions. Intelligent cooperative covert communication, which uses generative adversarial networks (GANs) and deep reinforcement learning (DRL), aims to adapt to complex and dynamic wireless environments. However, it faces challenges in terms of computational complexity. Intelligent parasitic covert communication, which involves spectral superposition, requires careful management of inter-system interference. Multidimensional covert waveform design holds promise in meeting the demands of complex electromagnetic environments but is hampered by high transceiver complexity.
The development of active detection by adversaries also calls for enhanced cognitive capabilities in covert communication systems. Additionally, integrating sensing and communication (ISAC) in covert communication shows potential, but it needs to address issues related to information leakage and mutual interference.
This research provides a comprehensive overview of intelligent covert communication, highlighting its significance in securing future wireless networks. As technology continues to advance, these findings will guide the development of more secure and efficient covert communication methods.
