Angeles Vazquez-Castro

Selen Gecgel Cetin, Gunes Karabulut Kurt, Angeles Vazquez-Castro

There is no doubt that the Moon has become the center of interest for commercial and international actors. Over the past decade, the number of planned long-term missions has increased dramatically. This makes the establishment of cislunar space networks (CSNs) crucial to orchestrate uninterrupted communications between the Moon and Earth. However, there are numerous challenges, unknowns, and uncertainties associated with cislunar communications that may pose various risks to lunar missions. In this study, we aim to address these challenges for cislunar communications by proposing a machine learning-based cislunar space domain awareness (SDA) capability that enables robust and secure communications. To this end, we first propose a detailed channel model for selected cislunar scenarios. Secondly, we propose two types of interference that could model anomalies that occur in cislunar space and are so far known only to a limited extent. Finally, we discuss our cislunar SDA to work in conjunction with the spacecraft communication system. Our proposed cislunar SDA, involving heuristic learning capabilities with machine learning algorithms, detects interference models with over 96% accuracy. The results demonstrate the promising performance of our cislunar SDA approach for secure and robust cislunar communication.

Angeles Vazquez-Castro, Faheem Dustin Quazi, Zhu Han

In generative communication, the transmitter sends a compact generative description, such as model parameters or a latent representation, rather than raw data. The receiver uses this description to form a posterior belief over the underlying state and to resolve semantic ambiguity: which interpretation, decision, or action is supported by the received representation? Inspired by Shannon's geometric view of communication as uncertainty resolution, we introduce resolution information as the minimum information update, measured in nats, required to move the receiver's posterior belief into a low-ambiguity semantic region. Our work yields three main results. First, when the receiver can form any posterior belief, corresponding to the ideal unconstrained case, resolution information reduces to a binary divergence that depends only on each region's prior probability. In this case, the shape of the regions is irrelevant. Under repeated sampling, ambiguity decays exponentially with an exponent equal to the resolution information, giving it an operational meaning as an ambiguity exponent. Second, when the generative representation constrains the posterior family, as in practice, geometry becomes operational and can create irreducible ambiguity floors: half-spaces remain resolvable, whereas polytope-type regions can exhibit residual ambiguity that no amount of additional information can remove. These results reveal a fundamental departure from classical channel coding. In Shannon theory, codes can be designed so that decoding regions separate messages and error probability vanishes below capacity. In generative communication, the model itself induces a constrained posterior geometry that may prevent asymptotic ambiguity resolution. The resulting limit is not on rate, but on resolvability itself.

Masahito Hayashi, Angeles Vazquez-Castro

In this work, we focus on the classical optical channel having Poissonian statistical behavior and propose a novel secrecy coding-based physical layer protocol. Our protocol is different but complementary to both (computationally secure) quantum immune cryptographic protocols and (information theoretically secure) quantum cryptographic protocols. Specifically, our (information theoretical) secrecy coding protocol secures classical digital information bits at photonic level exploiting the random nature of the Poisson channel. It is known that secrecy coding techniques for the Poisson channel based on the classical one-way wiretap channel (introduced by Wyner in 1975) ensure secret communication only if the mutual information to the eavesdropper is smaller than that to the legitimate receiver. In order to overcome such a strong limitation, we introduce a two-way protocol that always ensures secret communication independently of the conditions of legitimate and eavesdropper channels. We prove this claim showing rigorous comparative derivation and analysis of the information theoretical secrecy capacity of the classical one-way and of the proposed two-way protocols. We also show numerical calculations that prove drastic gains and strong practical potential of our proposed two-way protocol to secure information transmission over optical channels.

Angeles Vazquez-Castro, Masahito Hayashi

Shannon introduced the classic model of a cryptosystem in 1949, where Eve has access to an identical copy of the cyphertext that Alice sends to Bob. Shannon defined perfect secrecy to be the case when the mutual information between the plaintext and the cyphertext is zero. Perfect secrecy is motivated by error-free transmission and requires that Bob and Alice share a secret key. Wyner in 1975 and later I.~Csiszár and J.~Körner in 1978 modified the Shannon model assuming that the channels are noisy and proved that secrecy can be achieved without sharing a secret key. This model is called wiretap channel model and secrecy capacity is known when Eve's channel is noisier than Bob's channel. In this paper we review the concept of wiretap coding from the satellite channel viewpoint. We also review subsequently introduced stronger secrecy levels which can be numerically quantified and are keyless unconditionally secure under certain assumptions. We introduce the general construction of wiretap coding and analyse its applicability for a typical satellite channel. From our analysis we discuss the potential of keyless information theoretic physical layer security for satellite channels based on wiretap coding. We also identify system design implications for enabling simultaneous operation with additional information theoretic security protocols.