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Jan Bauer

Publications and source records attributed to Jan Bauer.

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Discrete signaling mediates chaotic regularization in recurrent neural networks

Cortical circuits operate in a regime of intrinsic chaos, where even tiny changes in input can lead to divergent neural responses. Yet, remarkably, population codes in the brain vary smoothly with sensory stimuli, forming coherent representational manifolds. How can chaotic networks sustain such stable coding? Here, we develop a theoretical framework that links the microscopic chaos of recurrent networks to the macroscopic geometry of neural representations. Combining kernel methods with dynamical mean-field theory, we show that chaotic dynamics induce local roughness (introducing sharp distortions at small scales) while preserving global smoothness across larger stimulus variations. This structural property acts as an intrinsic regularizer, enhancing generalization while maintaining expressivity. Moreover, we show how chaotic networks naturally produce power-law spectral signatures, closely matching experimental observations in cortical recordings. These results explain how chaotic spiking networks can sustain smooth, differentiable population codes and establish a theoretical framework linking network dynamics, computational structure, and recorded neural activity.

q-bio.NC

Building Better Activation Oracles

Activation Oracles (AOs) are promising methods for interpreting residual stream activations. However, current AOs face important issues, such as hallucinations and vagueness. Additionally, text-inversion confounds make them hard to evaluate. To this end, we improve the Activation Oracle (AO) training regime in four ways: training on on-policy rollouts, improving the conversational dataset, feeding more layers and an improvement to the injection formula. The capability improvements are marginal, but quality of life improvements are quite substantial. In addition, we open source the first comprehensive evaluation suite for AO quality, which we call AObench. Overall, we hope that our work sets a foundation that helps improve AOs and other models in the paradigm of scalable, end-to-end interpretability.

cs.LG

MAC Aggregation over Lossy Channels in DTLS 1.3

Aggregating Message Authentication Codes (MACs) promises to save valuable bandwidth in resource-constrained environments. The idea is simple: Instead of appending an authentication tag to each message in a communication stream, the integrity protection of multiple messages is aggregated into a single tag. Recent studies postulate, e.g., based on simulations, that these benefits also spread to wireless, and thus lossy, scenarios despite each lost packet typically resulting in the loss of integrity protection information for multiple messages. In this paper, we investigate these claims in a real deployment. Therefore, we first design a MAC aggregation extension for the Datagram Transport Layer Security (DTLS) 1.3 protocol. Afterward, we extensively evaluate the performance of MAC aggregation on a complete communication protocol stack on embedded hardware. We find that MAC aggregation can indeed increase goodput by up to 50% and save up to 17% of energy expenditure for the transmission of short messages, even in lossy channels.

cs.CR

CAIBA: Multicast Source Authentication for CAN Through Reactive Bit Flipping

Controller Area Networks (CANs) are the backbone for reliable intra-vehicular communication. Recent cyberattacks have, however, exposed the weaknesses of CAN, which was designed without any security considerations in the 1980s. Current efforts to retrofit security via intrusion detection or message authentication codes are insufficient to fully secure CAN as they cannot adequately protect against masquerading attacks, where a compromised communication device, a so-called electronic control units, imitates another device. To remedy this situation, multicast source authentication is required to reliably identify the senders of messages. In this paper, we present CAIBA, a novel multicast source authentication scheme specifically designed for communication buses like CAN. CAIBA relies on an authenticator overwriting authentication tags on-the-fly, such that a receiver only reads a valid tag if not only the integrity of a message but also its source can be verified. To integrate CAIBA into CAN, we devise a special message authentication scheme and a reactive bit overwriting mechanism. We achieve interoperability with legacy CAN devices, while protecting receivers implementing the AUTOSAR SecOC standard against masquerading attacks without communication overhead or verification delays.

cs.CR

SoK: Evaluations in Industrial Intrusion Detection Research

Industrial systems are increasingly threatened by cyberattacks with potentially disastrous consequences. To counter such attacks, industrial intrusion detection systems strive to timely uncover even the most sophisticated breaches. Due to its criticality for society, this fast-growing field attracts researchers from diverse backgrounds, resulting in 130 new detection approaches in 2021 alone. This huge momentum facilitates the exploration of diverse promising paths but likewise risks fragmenting the research landscape and burying promising progress. Consequently, it needs sound and comprehensible evaluations to mitigate this risk and catalyze efforts into sustainable scientific progress with real-world applicability. In this paper, we therefore systematically analyze the evaluation methodologies of this field to understand the current state of industrial intrusion detection research. Our analysis of 609 publications shows that the rapid growth of this research field has positive and negative consequences. While we observe an increased use of public datasets, publications still only evaluate 1.3 datasets on average, and frequently used benchmarking metrics are ambiguous. At the same time, the adoption of newly developed benchmarking metrics sees little advancement. Finally, our systematic analysis enables us to provide actionable recommendations for all actors involved and thus bring the entire research field forward.

cs.CR

Take a Bite of the Reality Sandwich: Revisiting the Security of Progressive Message Authentication Codes

Message authentication guarantees the integrity of messages exchanged over untrusted channels. However, to achieve this goal, message authentication considerably expands packet sizes, which is especially problematic in constrained wireless environments. To address this issue, progressive message authentication provides initially reduced integrity protection that is often sufficient to process messages upon reception. This reduced security is then successively improved with subsequent messages to uphold the strong guarantees of traditional integrity protection. However, contrary to previous claims, we show in this paper that existing progressive message authentication schemes are highly susceptible to packet loss induced by poor channel conditions or jamming attacks. Thus, we consider it imperative to rethink how authentication tags depend on the successful reception of surrounding packets. To this end, we propose R2-D2, which uses randomized dependencies with parameterized security guarantees to increase the resilience of progressive authentication against packet loss. To deploy our approach to resource-constrained devices, we introduce SP-MAC, which implements R2-D2 using efficient XOR operations. Our evaluation shows that SP-MAC is resilient to sophisticated network-level attacks and operates as resources-conscious and fast as existing, yet insecure, progressive message authentication schemes.

cs.CR

CD2 : Combined Distances of Contrast Distributions for the Assessment of Perceptual Quality of Image Processing

The quality of visual input is very important for both human and machine perception. Consequently many processing techniques exist that deal with different distortions. Usually image processing is applied freely and lacks redundancy regarding safety. We propose a novel image comparison method called the Combined Distances of Contrast Distributions (CD2) to protect against errors that arise during processing. Based on the distribution of image contrasts a new reduced-reference image quality assessment (IQA) method is introduced. By combining various distance functions excellent performance on IQA benchmarks is achieved with only a small data and computation overhead.

eess.IV