When making decisions in a network, it is important to have up-to-date knowledge of the current state of the system. Obtaining this information, however, comes at a cost. In this paper, we determine the optimal finite-time update policy for monitoring the binary states of remote sources with a reporting rate constraint. We first prove an upper and lower bound of the minimal probability of error before solving the problem analytically. The error probability is defined as the probability that the system performs differently than it would with full system knowledge. More specifically, an error occurs when the destination node incorrectly determines which top- K priority sources are in the “free” state. We find that the optimal policy follows a specific ordered 3-stage update pattern. We then provide the optimal transition points for each stage for each source.

We present a new threat model enabling a passive adversary to infer which overheard packets belong to which transmitters. We call this threat model unsupervised wireless diarization (UWD) where the adversary assigns transmitter identity (label) to received packets in an encrypted wireless network without access to the MAC headers. To demonstrate the feasibility of such an attack, we develop UWDNet, a wireless diarization pipeline comprised of a Siamese neural network to extract embeddings from received packets, a similarity metric to compare embeddings, and unsupervised clustering. We evaluate UWDNet on both synthetic datasets and datasets of real wireless transmissions collected using Rice University's configurable massive MIMO testbed RENEW. Via various experimentation scenarios, our initial results show that UWDNet achieves a diarization accuracy of above 90% on synthetic data of transmitters it has never seen. To push the limits of performance evaluation, we collected a real radio transmissions dataset representing a worst-case (almost pathological) setting where all nodes are co-located. Even in this near-pathological case, UWDNet accuracy is > 60% – well above a random label assignment, indicating the feasibility of unsupervised wireless diarization in real-life scenarios. We also analyzed different factors such as the spatial channel and transmit parameters, which impact diarization accuracy in real-world scenarios.

This work establishes that the physical layer can be used to perform information-theoretic authentication in additive white Gaussian noise (AWGN) channels, as long as the adversary is not omniscient. The model considered consists of an encoder, decoder, and adversary, where the adversary knows the message given to the encoder, has a non-causal noisy observation of the encoder’s transmission and may use unlimited transmission power, while the decoder observes a noisy version of the sum of the encoder and adversary’s outputs. A method to modify a generic existing channel code to enable authentication is presented. This method relies on injecting message-dependent noise into the transmission and accepting the transmission as authentic only if the correct noise levels for the decoded message are observed. One drawback to this method is that the encoder must still transmit a low-power signal in the case where there is no message to send. It is shown that this modification costs an asymptotically negligible amount of the coding rate, while still enabling authentication as long as the adversary’s observation is not noiseless. Also notable is that this modification is not (asymptotically) a function of the statistical characterization of the adversary’s channel and no secret key is required. We believe these features will pave the way for a robust practical implementation. Using these results, the channel-authenticated capacity is calculated and shown to be equal to the non-adversarial channel capacity. As our results will show, information-theoretic authentication in AWGN channels is possible without the need for the legitimate party to have a model-based advantage over the adversary. While this modular scheme is designed for use in the given channel model, it is applicable to a wide range of settings.

Estimation of transmission rates by a malicious user can serve as a stepping stone to further attacks on the network. In this paper, we aim to investigate the general problem of estimating traffic transmission rates in a CSMA/CA network using a class of passive eavesdropping methods. We consider the case where a single eavesdropper passively monitors all active network nodes but cannot observe all packet transmissions due to spatial-reuse collisions. To enable tractable analysis, we first propose an approximate statistical model that can help the eavesdropper estimate transmission rates with partial measurements under spatial reuse. We next consider a class of eavesdroppers that become increasingly more capable, and develop a framework to demonstrate that two classes of eavesdropper capabilities are sufficient to achieve a consistent transmission rate estimator. We provide numerical tests of our proposed estimators under practical network cases using the NS-3 simulator that validate the theoretical results.

This paper investigates the secret key-authenticated-capacity region, where information-theoretic authentication is defined by the ability of the decoder to accept and decode messages originating from a valid encoder while rejecting messages from other invalid sources. The model considered here consists of a valid encoder-decoder pairing that can communicate through a channel controlled by an adversary who is also able to eavesdrop on the encoder’s transmissions. Prior to the encoder’s transmission, the adversary decides whether or not to replace the decoder’s observation with an arbitrary one of the adversary’s choosing, with the adversary’s objective being to have the decoder accept and decode their observation to a valid message (different from that of the encoder). To combat the adversary, the encoder and decoder share a secret key. The secret key-authenticated-capacity region is defined as the region of jointly achievable message rate, authentication rate (a to be defined per symbol measure that will generally represent the likelihood that an adversary can fool the decoder), and the key-consumption rate (how many bits of secret key are needed per symbol sent). This is the second of a two-part study, with the parts differing in their measure of the authentication rate. For this second study, the probability of false authentication is considered as a function of the system state, where the system state is defined by the message being transmitted, the value of the secret key, the adversary’s channel observations, and the adversary’s (possibly stochastic) choice for the decoder’s observation. Termed the typical-authentication rate, the authentication measure considered here corresponds to an upper bound on the probability of false authentication for the majority of system states. For this measure, we derive matching inner and outer bounds for the secret key-enabled authenticated capacity region in terms of traditional information-theoretic measures. In doing so, it is shown that the typical-authentication rate and the message rate exhibit a one-to-one trade-off in the capacity region.

This paper investigates the secret-key-authenticated-capacity region, where information-theoretic authentication is defined by the ability of the decoder to accept and decode messages originating from a valid encoder while rejecting messages from other invalid sources. The model considered here consists of a valid encoder-decoder pairing that can communicate through a channel controlled by an adversary who is also able to eavesdrop on the encoder’s transmissions. Over multiple rounds of communication, the adversary first decides whether or not to replace the decoder’s observation with an arbitrary one of the adversary’s choosing, with the goal of the adversary being to have the decoder accept and decode their observation as a valid message (different from that of the encoder). To combat the adversary, the encoder and decoder share a secret key. The secret-key-authenticated-capacity region here is then defined as the region of jointly achievable message rate, authentication rate (a to be defined per symbol measure that will generally represent the likelihood that an adversary can fool the decoder), and the key-consumption rate (how many bits of secret key are needed per symbol sent). This is the first of a two-part study, with the parts differing in their measure of the authentication rate. In this first study, the authentication rate is the exponent of blocklength-normalized exponent of the expected probability of false authentication. For this metric, we provide an inner bound which improves on those existing in the literature. This is achieved by adopting and merging different classical techniques in novel ways. Within these classical secret-key-based authentication techniques, one technique derives authentication capability from secure channel coding to send the secret key with the message, and the other technique derives its authentication capability directly from obscuring the source.

We take the first step towards understanding the fundamental limits of blind wireless network inference performed by a distributed network of single-antenna adversary nodes. The distributed adversary nodes are assumed to be blind to the protocol parameters as well as the modulation, coding and encryption schemes used by the network being monitored. Focusing on the special case of inferring the channel access probabilities of the monitored nodes, we derive minimax bounds for blind inference. We show that blind inference is possible with similar sample complexity (asymptotically) as non-blind inference given certain network connectivity conditions are satisfied.

In unsecured communications settings, ascertaining the trustworthiness of received information, called authentication, is paramount. We consider keyless authentication over an arbitrarily-varying channel, where channel states are chosen by a malicious adversary with access to noisy versions of transmitted sequences. We have shown previously that a channel condition termed U-overwritability is a sufficient condition for zero authentication capacity over such a channel, and also that with a deterministic encoder, a sufficiently clear-eyed adversary is essentially omniscient. In this paper, we show that even if the authentication capacity with a deterministic encoder and an essentially omniscient adversary is zero, allowing a stochastic encoder can result in a positive authentication capacity. Furthermore, the authentication capacity with a stochastic encoder can be equal to the no-adversary capacity of the underlying channel in this case. We illustrate this for a binary channel model, which provides insight into the more general case.

This work presents a new methodology for obtaining information theoretic necessary conditions directly from general operational requirements. This methodology is based on the construction of a discrete random variable that, when conditioned upon, ensures information stability of quasi-images. The induced information stability allows a more direct way to develop information theoretic necessary conditions from operational requirements beyond using Fano's inequality. That is, while Fano's inequality uses the probability of error to establish an upper bound on the entropy of a random variable given its estimator, the proposed new methodology can be applied to arbitrary operational requirements to obtain corresponding conditions on information theoretic quantities. To demonstrate its power, this new methodology is employed, to derive new necessary conditions for keyed authentication over a discrete memoryless channels and to establish the capacity region subject to finite leakage and finite error of the wiretap channel under two different secrecy metrics. These examples establish the usefulness of the proposed methodology.

Authentication in the presence of a malicious adversary consists of either recovering the legitimate transmission or declaring that the adversary has interfered with the transmission. In this work, we present a structured coding scheme for keyless authentication over a discrete memoryless binary-input, symmetric adversarial channel. Our scheme allows for coding rates up to the non-adversarial capacity of the underlying channel, as well as bounded-complexity decoding.

A basic information theoretic model for summarization is formulated. Here summarization is considered as the process of taking a report of v binary objects, and producing from it a j element subset that captures most of the important features of the original report, with importance being defined via an arbitrary set function endemic to the model. The loss of information is measured by a weight average of variational distances, which we term the semantic loss.Our results include both cases where the probability distribution generating the v-length reports are known and unknown. In the case where the generating distribution is known, our results demonstrate how to construct minimal semantic loss summarizers. For the case where the probability distribution is unknown, we show how to construct summarizers which minimize the semantic loss averaged uniformly over all possible distribution converges to the minimum.

We construct a modular scheme which extends codes for wiretap channels of type I for use in wiretap channels of type II. This is done by using a concatenate and permute strategy, wherein multiple uses of the wiretap type I code are concatenated and then the joint sequence of symbols permuted. The choice of permutation is then encoded with a short code and appended to the transmitted sequence. Analysis shows essentially no degradation in operational parameters (rate, error rate, leakage) for the new code over the wiretap type II channel when compared to those of multiple uses of the original code over the wiretap type I channel.

In this paper we classify what arbitrary sources can be transmitted over a discrete memoryless broadcast channel with confidential communications (DM-BCC). Despite allowing completely arbitrary sources and finite error, we show that necessary and sufficient conditions can be expressed in terms of traditional channel capacity regions. As a by-product we also determine the (ε, δ) -capacity region, and show that even in this more general setting source-channel separation is optimal for the DM-BCC as originally defined.

The rate regions of many variations of the standard and wire-tap channels have been thoroughly explored. Secrecy capacity characterizes the loss of rate required to ensure that the adversary gains no information about the transmissions. Authentication does not have a standard metric, despite being an important counterpart to secrecy. While some results have taken an information-theoretic approach to the problem of authentication coding, the full rate region and accompanying trade-offs have yet to be characterized. In this paper, we provide an inner bound of achievable rates with an average authentication and reliability constraint. The bound is established by combining and analyzing two existing authentication schemes for both noisy and noiseless channels. We find that our coding scheme improves upon existing schemes.

This paper employs equal-image-size source partitioning techniques to derive the capacities of the general discrete memoryless wiretap channel (DM-WTC) under four different secrecy criteria. These criteria respectively specify requirements on the expected values and tail probabilities of the differences, in absolute value and in exponent, between the joint probability of the secret message and the eavesdropper's observation and the corresponding probability if they were independent. Some of these criteria reduce back to the standard leakage and variation distance constraints that have been previously considered in the literature. The capacities under these secrecy criteria are found to be different when non-vanishing error and secrecy tolerances are allowed. Based on these new results, we are able to conclude that the strong converse property generally holds for the DM-WTC only under the two secrecy criteria based on constraining the tail probabilities. Under the secrecy criteria based on the expected values, an interesting phase change phenomenon is observed as the tolerance values vary.

This paper investigates the problem of information stabilization of the images of source sets over discrete memoryless channels (DMCs). It is shown that if the minimum image cardinality of a source set over a DMC has a specific entropy characterization, then the image of this source set will be information stable. In many applications, this requirement on the source set can be satisfied using the method of equal-image-size source partitioning. A construction of a strong secrecy subcode from a weak secrecy code for the wiretap channel is provided as an example to illustrate the use of the information stabilization technique.

If Alice must communicate with Bob over a channel shared with the adversarial Eve, then Bob must be able to validate the authenticity of the message. In particular we consider the model where Alice and Eve share a discrete memoryless multiple access channel with Bob, thus allowing simultaneous transmissions from Alice and Eve. By traditional random coding arguments, we demonstrate an inner bound on the rate at which Alice may transmit, while still granting Bob the ability to authenticate. Furthermore this is accomplished in spite of Alice and Bob lacking a pre-shared key, as well as allowing Eve prior knowledge of both the codebook Alice and Bob share and the messages Alice transmits.

In this paper we investigate the image size characterization problem. We show that any arbitrary source set may be decomposed into sets whose image size characterization is the same as its entropy characterization. We also show that the number of these sets required is small enough that one may consider that from a coding perspective the achievable entropy region and achievable exponent region are equal. This has an impact on many source networks and network problems whose solution heretofore could not have the image size characterization applied to them.

The goal of this paper is to obtain the channel conditions (if exist) under which substitution attacks performed by relay node(s) in a relay network can be detected. The network model considered consists of a source node and a destination node. There are two independent transmission paths from the source to the destination, each via a potentially malicious relay which may perform substitution attacks by forwarding altered symbols to the destination. The destination attempts to detect any such malicious act of the relays by comparing the joint empirical distribution of the symbols received from the relays with known channel statistics along the two paths. Note that every symbol received by the destination may be altered, and hence no clean reference observation is available to the node. It is demonstrated that maliciousness of the relays can be asymptotically detected with sufficient channel observations if and only if the two relays do not collude and the network satisfies a non-manipulability condition.

This paper presents a random coding scheme with which two nodes can exchange information with guaranteed integrity over a two-way Byzantine relay. This coding scheme is employed to obtain an inner bound on the capacity region with information integrity. No pre-shared secret or secret transmission is needed for the proposed scheme. Hence the inner bound obtained is generally larger than those achieved based on secret transmission schemes. This approach advocates the separation of supporting information integrity and secrecy.

We consider the problem of two sources wanting to share information through a potentially untrustworthy intermediary node. We assume that the two sources transmit random symbols simultaneously and that the intermediary node relays the information in the amplify-and-forward manner. We show that under a certain sufficient condition on the channel, it is possible to asymptotically detect whether or not the intermediary node is degrading the channel by sending out manipulated symbols. This can be done solely by each source examining its received distribution conditioned on what it transmitted; thus allowing for a minimally invasive approach to determining if the intermediary node is acting maliciously. More specifically, we model the potential malicious action of the intermediate node by an “attack” channel. An estimate of the attack channel is obtained from the received conditional distribution empirically observed by a source node. We show that the estimated attack channel converges in probability to the true attack channel if the intermediate node is not acting maliciously. Otherwise there is a separation between the estimated and true attacking channels with high probability. This result provides us a clear-cut criterion to determine whether the intermediate node is malicious or not.