Joint Secrecy Rate Achieving and Authentication Enhancement via Tag-based Encoding in Chaotic UAV Communication Environment

TL;DR

This work tackles secure downlink UAV communications in chaotic LoS-dominated environments by introducing Tag-based Encoding (TBE), which jointly enables authentication and secrecy. A novel dual-reference tag generation mechanism uses a stable encoding-insensitive feature alongside a secret key to regenerate an accurate reference tag for decoding, while the wiretapped tag at eavesdroppers yields limited information. The authors formulate two optimization problems—ergodic sum secrecy rate maximization and authentication fail probability minimization—and solve them via DC programming and the Lagrange method, respectively. Numerical results show that TBE considerably improves secrecy performance compared to prior AN-aided tag embedding, reducing authentication failures and boosting secrecy rates, especially in high-risk scenarios where channel similarities hinder traditional AN-based secrecy. The proposed framework provides a practical path toward reliable, low-overhead integration of authentication and confidentiality in UAV networks, with rigorous quasi-convex/concave analyses underpinning the optimization methods.

Abstract

Secure communication is crucial in many emerging systems enabled by unmanned aerial vehicle (UAV) communication networks. To protect legitimate communication in a chaotic UAV environment, where both eavesdropping and jamming become straightforward from multiple adversaries with line-of-sight signal propagation, a new reliable and integrated physical layer security mechanism is proposed in this paper for a massive multiple-input-multiple-output (MIMO) UAV system. Particularly, a physical layer fingerprint, also called a tag, is first embedded into each message for authentication purpose. We then propose to reuse the tag additionally as a reference to encode each message to ensure secrecy for confidentiality enhancement at a low cost. Specifically, we create a new dual-reference symmetric tag generation mechanism by inputting an encoding-insensitive feature of plaintext along with the key into a hash function. At a legitimate receiver, an expected tag, reliable for decoding, can be symmetrically regenerated based on the received ciphertext, and authentication can be performed by comparing the regenerated reference tag to the received tag. However, an illegitimate receiver can only receive the fuzzy tag which can not be used to decode the received message. Additionally, we introduce artificial noise (AN) to degrade eavesdropping to further decrease message leakage. To verify the efficiency of our proposed tag-based encoding (TBE) scheme, we formulate two optimization problems including ergodic sum secrecy rate maximization and authentication fail probability minimization. The power allocation solutions are derived by difference-of-convex (DC) programming and the Lagrange method, respectively. The simulation results demonstrate the superior performance of the proposed TBE approach compared to the prior AN-aided tag embedding scheme.

Figures (8)

• Figure 1: Downlink communications from BS toward multiple UAV users with the presence of UAV adversaries.
• Figure 2: Average SERs of message and tag at UAV-UEs and UAV-EVEs versus $\rho$ when AN is not injected ( e.g., the curve "Mes,SIM,EVE-80m,$1^{\circ}$" indicates the simulation of messages' average SER at UAV-EVEs with $h_{\rm{EVE}}=\text{80 m}$ and $\Delta\theta=1^{\circ}$. Specifically, "Mes/Tag" indicates message/tag, "SIM/THR" indicates simulation/theory, "EVE/UE" indicates eavesdropper/user, "80 m/60 m" is the value of $h_{\rm{EVE}}$, and $0^{\circ}/1^{\circ}$ is the value of $\Delta\theta$).
• Figure 3: Average SERs of message and tag at UAV-UEs and UAV-EVEs versus $\phi$ with $\rho=0.95$. Low-risk scenario is with $h_{\rm{EVE}}=80$ m and $\Delta\theta=1^{\circ}$, where AN injection works (able to degrade EVE's SER to be worse than user's SER as circled). Other scenarios are high-risk scenarios where AN injection fails.
• Figure 4: ROC at different $\rho$ with $\phi=1$ ("THR,Prior" indicates the prior $P_{\rm f}$ expression given in SIMO, which considers $P_{u,\rm b}$ in (\ref{['pf']}) as $0$). Authentication performance increases as more power is allocated to the tag. Every three lines ("SIM", "THR", and "THR,Prior") with the same $\rho$ are consistent.
• Figure 5: Ergodic sum secrecy rate varying with $\rho$ and $\phi$ at different wiretap scenarios, where the threshold of $P_{\rm f}$ is set to 0.001. The special characteristic of DC programming can be observed as the one or two stationary points from ($0.9,1$) varying towards ($1,1$).