Miracle-dz/UniFAR-FTUs huggingface dataset:
Poster: A WiFi Vision-based Approach to Person Re-identification

In this work, we propose a WiFi vision-based approach to person re-identification (Re-ID) indoors. Our approach leverages the advances of WiFi to visualize a person and utilizes deep learning to help WiFi devices identify and recognize people. Specifically, we leverage multiple antennas on WiFi devices to estimate the two-dimensional angle of arrival (2D AoA) of the WiFi signal reflections to enable WiFi devices to "see'' a person. We then utilize deep learning techniques to extract a 3D mesh representation of a person and extract the body shape and walking patterns for person Re-ID. Our preliminary study shows that our system achieves high overall ranking accuracies. It also works under non-line-of-sight and different person appearance conditions, where the traditional camera vision-based systems do not work well.
QuerySnout: Automating the Discovery of Attribute Inference Attacks against Query-Based Systems

Although query-based systems (QBS) have become one of the main solutions to share data anonymously, building QBSes that robustly protect the privacy of individuals contributing to the dataset is a hard problem. Theoretical solutions relying on differential privacy guarantees are difficult to implement correctly with reasonable accuracy, while ad-hoc solutions might contain unknown vulnerabilities. Evaluating the privacy provided by QBSes must thus be done by evaluating the accuracy of a wide range of privacy attacks. However, existing attacks against QBSes require time and expertise to develop, need to be manually tailored to the specific systems attacked, and are limited in scope. In this paper, we develop QuerySnout, the first method to automatically discover vulnerabilities in query-based systems. QuerySnout takes as input a target record and the QBS as a black box, analyzes its behavior on one or more datasets, and outputs a multiset of queries together with a rule to combine answers to them in order to reveal the sensitive attribute of the target record. QuerySnout uses evolutionary search techniques based on a novel mutation operator to find a multiset of queries susceptible to lead to an attack, and a machine learning classifier to infer the sensitive attribute from answers to the queries selected. We showcase the versatility of QuerySnout by applying it to two attack scenarios (assuming access to either the private dataset or to a different dataset from the same distribution), three real-world datasets, and a variety of protection mechanisms. We show the attacks found by QuerySnout to consistently equate or outperform, sometimes by a large margin, the best attacks from the literature. We finally show how QuerySnout can be extended to QBSes that require a budget, and apply QuerySnout to a simple QBS based on the Laplace mechanism. Taken together, our results show how powerful and accurate attacks against QBSes can already be found by an automated system, allowing for highly complex QBSes to be automatically tested "at the pressing of a button". We believe this line of research to be crucial to improve the robustness of systems providing privacy-preserving access to personal data in theory and in practice.
PSI from Ring-OLE

Private set intersection (PSI) is one of the most extensively studied instances of secure computation. PSI allows two parties to compute the intersection of their input sets without revealing anything else. Other useful variants include PSI-Payload, where the output includes payloads associated with members of the intersection, and PSI-Sum, where the output includes the sum of the payloads instead of individual ones. In this work, we make two related contributions. First, we construct simple and efficient protocols for PSI and PSI-Payload from a ring version of oblivious linear function evaluation (ring-OLE) that can be efficiently realized using recent ring-LPN based protocols. A standard OLE over a field F allows a sender with a,b F to deliver ax + b to a receiver who holds x F. Ring-OLE generalizes this to a ring F, in particular, a polynomial ring over F. Our second contribution is an efficient general reduction of a variant of PSI-Sum to PSI-Payload and secure inner product. Our protocols have better communication cost than state-of-the-art PSI protocols, especially when requiring security against malicious parties and when allowing input-independent preprocessing. Compared to previous maliciously secure PSI protocols that have a similar computational cost, our online communication is 2x better for small sets (28-212 elements) and 20% better for large sets (220 -224). Our protocol is also simpler to describe and implement. We obtain even bigger improvements over the state of the art (4-5x better running time) for our variant of PSI-Sum.
Repeated interactions in open quantum systems

Analyzing the dynamics of open quantum systems has a long history in mathematics and physics. Depending on the system at hand, basic physical phenomena that one would like to explain are, for example, convergence to equilibrium, the dynamics of quantum coherences (decoherence) and quantum correlations (entanglement), or the emergence of heat and particle fluxes in non-equilibrium situations. From the mathematical physics perspective, one of the main challenges is to derive the irreversible dynamics of the open system, starting from a unitary dynamics of the system and its environment. The repeated interactions systems considered in these notes are models of non-equilibrium quantum statistical mechanics. They are relevant in quantum optics, and more generally, serve as a relatively well treatable approximation of a more difficult quantum dynamics. In particular, the repeated interaction models allow to determine the large time (stationary) asymptotics of quantum systems out of equilibrium.
How to Hide MetaData in MLS-Like Secure Group Messaging: Simple, Modular, and Post-Quantum

Secure group messaging (SGM) protocols allow large groups of users to communicate in a secure and asynchronous manner. In recent years, continuous group key agreements (CGKAs) have provided a powerful abstraction to reason on the security properties we expect from SGM protocols. While robust techniques have been developed to protect the contents of conversations in this context, it is in general more challenging to protect metadata (e.g. the identity and social relationships of group members), since their knowledge is often needed by the server in order to ensure the proper function of the SGM protocol. In this work, we provide a simple and generic wrapper protocol that upgrades non-metadata-hiding CGKAs into metadata-hiding CGKAs. Our key insight is to leverage the existence of a unique continuously evolving group secret key shared among the group members. We use this key to perform a group membership authentication protocol that convinces the server in an anonymous manner that a user is a legitimate group member. Our technique only uses a standard signature scheme, and thus, the wrapper protocol can be instantiated from a wide range of assumptions, including post-quantum ones. It is also very efficient, as it increases the bandwidth cost of the underlying CGKA operations by at most a factor of two. To formally prove the security of our protocol, we use the universal composability (UC) framework and model a new ideal functionality ℱmhCGKA capturing the correctness and security guarantee of metadata-hiding CGKA. To capture the above intuition of a "wrapper'' protocol, we also define a restricted ideal functionality ℱctxt CGKA, which roughly captures a non-metadata-hiding CGKA. We then show that our wrapper protocol UC-realizes ℱmhCGKA in the ℱctxtCGKA -hybrid model, which in particular formalizes the intuition that any non-metadata-hiding CGKA can be modularly bootstrapped into metadata-hiding CGKA.
EchoHand: High Accuracy and Presentation Attack Resistant Hand Authentication on Commodity Mobile Devices

Biometric authentication schemes, i.e., fingerprint and face authentication, raise serious privacy concerns. To alleviate such concerns, hand authentication has been proposed recently. However, existing hand authentication schemes use dedicated hardware, such as infrared or depth cameras, which are not available on commodity mobile devices. In this paper, we present EchoHand, a high accuracy and presentation attack resistant authentication scheme that complements camera-based 2-dimensional hand geometry recognition of one hand with active acoustic sensing of the other holding hand. EchoHand plays an inaudible acoustic signal using the speaker to actively sense the holding hand and collects the echoes using the microphone. EchoHand does not rely on any specialized hardware but uses the built-in speaker, microphone and camera. Moreover, EchoHand does not place more burdens on users than existing hand authentication methods. We conduct comprehensive experiments to evaluate the reliability and security of EchoHand. The results show that EchoHand has a low equal error rate of 2.45% with as few as 10 training data points and it defeats presentation attacks.
Poster: Adversarial Defense with Deep Learning Coverage on MagNet's Purification

MagNet is a defense method that adopts autoencoders to detect and purify adversarial examples. Although MagNet is robust against grey-box and black-box attacks, it is vulnerable to white-box attacks. Despite this prior knowledge, the fundamental reason for and mitigation of the vulnerability of MagNet have not been discussed. We suggest that the challenge of MagNet is the generalization of the data manifold. To explain this, in this work, we leverage deep learning coverage for the reformer of MagNet. We mutate training images through image transformation algorithms and then train the reformer using mutants with new coverage information. The selected mutants provide an interesting data manifold, that cannot be handled by the random noise of MagNet, to the reformer. In grey-box settings, our defense method classified adversarial examples for various perturbation sizes much more accurately than MagNet even with the same architecture. Based on the preliminary result of this work, we consider future work to identify whether the generalization power of deep learning coverage is effective for stronger adversaries and different architectures.
Poster: Inaudible Acoustic Noise from Silicon Capacitors for Voice-Command Injection

Multi-layer ceramic capacitors (MLCCs), commonly used in electronics products, can generate acoustic noise driven by electrical deviation. Such acoustic noise has been exploited to attack systems' security. In particular, CapSpeaker silently delivers voice commands to voice-controllable systems using inaudible acoustic noise and intermodulation distortion (IMD). Silicon capacitor is an emerging technology that achieves a larger capacitance with a smaller footprint fabricated with semiconductor manufacturing processes using different structures and materials. Do silicon capacitors still generate acoustic noise despite the differences? We positively answer the question by experimentally showing that an off-the-shelf silicon capacitor generates audible acoustic noise through IMD; CapSpeaker is still feasible with the new capacitor
WINK: Wireless Inference of Numerical Keystrokes via Zero-Training Spatiotemporal Analysis

Sensitive numbers play an unparalleled role in identification and authentication. Recent research has revealed plenty of side-channel attacks to infer keystrokes, which require either a training phase or a dictionary to build the relationship between an observed signal disturbance and a keystroke. However, training-based methods are unpractical as the training data about the victim are hard to obtain, while dictionary-based methods cannot infer numbers, which are not combined according to linguistic rules like letters are. We observe that typing a number creates not only a number of observed disturbances in space (each corresponding to a digit), but also a sequence of periods between each disturbance. Based upon existing work that utilizes inter-keystroke timing to infer keystrokes, we build a novel technique called WINK that combines the spatial and time domain information into a spatiotemporal feature of keystroke-disturbed wireless signals. With this spatiotemporal feature, WINK can infer typed numbers without the aid of any training. Experimental results on top of software-defined radio platforms show that WINK can vastly reduce the guesses required for breaking certain 6-digit PINs from 1 million to as low as 16, and can infer over 52% of user-chosen 6-digit PINs with less than 100 attempts.
Distinct feedforward and feedback pathways for cell-type specific attention effects

Spatial attention selectively enhances neural responses to visual stimuli. There are two long-standing hypotheses about how top-down feedback enhances sensory responses in areas like V4: First, by amplifying V1-to-V4 feedforward communication via 30-80Hz gamma-coherence. Second, via top-down feedback to V4 supra- and infra-granular layers. To test these hypotheses, we recorded distinct cell-types across macaque V1 and V4 layers. Attention increased both V1-V4 gamma-coherence and V4 spike-rates, yet with distinct laminar and cell-type profiles. Surprisingly, V1 gamma did not engage V4 excitatory neurons, but only Layer-4 fast-spiking interneurons. Similar observations were made in mouse visual-cortex, where feedforward gamma-influences preferentially recruit optogenetically-tagged PV+ and narrowwaveform SSt+ interneurons. By contrast, attention enhanced V4 spike-rates in both excitatory neurons and fast-spiking interneurons, with the strongest and earliest modulation in Layer-2/3, consistent with a feedback influence. These findings reveal distinct feedforward and feedback pathways for the attentional modulation of inter-areal coherence and spike rates, respectively.
Identification of NAD-RNAs and ADPR-RNA decapping in the archaeal model organisms Sulfolobus acidocaldarius and Haloferax volcanii

NAD is a coenzyme central to metabolism that was also found to serve as a 5’-terminal cap of bacterial and eukaryotic RNA species. The presence and functionality of NAD-capped RNAs (NAD-RNAs) in the archaeal domain remain to be characterized in detail. Here, by combining LC-MS and NAD captureSeq methodology, we quantified the total levels of NAD-RNAs and determined the identity of NAD-RNAs in the two model archaea, Sulfolobus acidocaldarius and Haloferax volcanii. A complementary differential RNA-Seq (dRNA-Seq) analysis revealed that NAD transcription start sites (NAD-TSS) correlate with well-defined promoter regions and often overlap with primary transcription start sites (pTSS). The population of NAD-RNAs in the two archaeal organisms shows clear differences, with S. acidocaldarius possessing more capped small non-coding RNAs (sncRNAs) and leader sequences. The NAD-cap did not prevent 5’→3’ exonucleolytic activity by the RNase Saci-aCPSF2. To investigate enzymes that facilitate the removal of the NAD-cap, four Nudix proteins of S. acidocaldarius were screened. None of the recombinant proteins showed NAD decapping activity. Instead, the Nudix protein Saci_NudT5 showed activity after incubating NAD-RNAs at elevated temperatures. Hyperthermophilic environments promote the thermal degradation of NAD into the toxic product ADPR. Incorporating NAD into RNAs and the regulation of ADPR-RNA decapping by Saci_NudT5 is proposed to provide additional layers of maintaining stable NAD levels in archaeal cells. Importance This study reports the first characterization of 5’-terminally modified RNA molecules in Archaea and establishes that NAD-RNA modifications, previously only identified in the other two domains of life, are also prevalent in the archaeal model organisms Sulfolobus acidocaldarius and Haloferax volcanii. We screened for NUDIX hydrolases that could remove the NAD-RNA cap and showed that none of these enzymes removed NAD modifications, but we discovered an enzyme that hydrolyzes ADPR-RNA. We propose that these activities influence the stabilization of NAD and its thermal degradation to potentially toxic ADPR products at elevated growth temperatures.
Dissecting the chain of information processing and its interplay with neurochemicals and fluid intelligence across development

Previous research has highlighted the role of glutamate and gamma-aminobutyric acid (GABA) in perceptual, cognitive, and motor tasks. However, the exact involvement of these neurochemical mechanisms in the chain of information processing, and across human development, are unclear. In a cross-sectional longitudinal design, we used a computational approach to dissociate cognitive, decision, and visuomotor processing in 293 individuals spanning early childhood to adulthood. We found that glutamate and GABA within the intraparietal sulcus (IPS) explained unique variance in visuomotor processing, with higher glutamate predicting poorer visuomotor processing in younger participants but better visuomotor processing in mature participants, while GABA showed the opposite pattern. These findings were functionally, neuroanatomically, and neurochemically specific, and were replicated ~1.5 years later and were generalized in two further different behavioral tasks. Using resting fMRI, we revealed that the relationship between IPS neurochemicals and visuomotor processing is mediated by functional connectivity in the visuomotor network. We then extended our findings to high-level cognitive behavior by predicting fluid intelligence performance. We showed that fluid intelligence performance is explained by IPS GABA and glutamate and is mediated by visuomotor processing, and moderated by the developmental stage. These results provide an integrative biological and psychological mechanistic explanation that links cognitive processes and neurotransmitters across human development and establishes their involvement in intelligent behavior.
The conserved protein WhiA influences branched-chain fatty acid precursors in Bacillus subtilis

The conserved WhiA protein family is present in most Gram-positive bacteria and plays a role in cell division. WhiA contains a DNA-binding motive and has been identified as a transcription factor in actinomycetes. In Bacillus subtilis, the absence of WhiA influences cell division and chromosome segregation, however, it is still unclear how WhiA influences these processes, but the protein does not seem to function as transcription factor in this organism. To further investigate the function of WhiA in B. subtilis, we performed a yeast two-hybrid screen to find interaction partners, and a Hi-C experiment to reveal possible changes in chromosome conformation. The latter experiment indicated a reduction in short range chromosome interactions, but how this would affect either cell division or chromosome segregation is unclear. Based on adjacent genes, a role in carbon metabolism was put forward. To study this, we measured exometabolome fluxes during growth on different carbon sources. This revealed that in ΔwhiA cells the pool of branched-chain fatty acid precursors is lower. However, the effect on the membrane fatty acid composition was minimal. Transcriptome data could not link the metabolome effects to gene regulatory differences. IMPORTANCE WhiA is a conserved DNA binding protein that influences cell division and chromosome segregation in the Gram-positive model bacterium B. subtilis. The molecular function of WhiA is still unclear, but a previous study has suggested that the protein does not function as a transcription factor. In this study, we used yeast two-hybrid screening, chromosome conformation capture analysis, metabolomics, transcriptomics and fatty acid analysis to obtain more information about the workings of this enigmatic protein.
Using the subspace theorem to bound unit distances

We prove a special case of Erd\H{o}s' unit distance problem using a corollary of the subspace theorem bounding the number of solutions of linear equations from a multiplicative group. We restrict our attention to unit distances coming from a multiplicative group of rank $r$ not too large. Specifically, given $\varepsilon>0$ and $n$ points in the plane, we construct the unit distance graph from these points and distances and use the corollary above to bound certain paths of length $k$ in the graph giving at most $n^{1+\varepsilon}$ unit distances from the group above. We require that the rank $r\le c\log n$ for some $c>0$ depending on $\varepsilon$. This extends a result of J\'ozsef Solymosi, Frank de Zeeuw and the author where we only considered unit distances that are roots of unity. Lastly we show that the lower bound configuration for the unit distance problem of Erd\H{o}s consists of unit distances from a multiplicative subgroup of the form above.
Symmetry preserving numerical schemes for partial differential equations and their numerical tests

The method of equivariant moving frames is used to construct symmetry preserving finite difference schemes of partial differential equations invariant under finite-dimensional symmetry groups. Invariant numerical schemes for a heat equation with logarithmic source and the spherical Burgers' equation are obtained. Numerical tests show how invariant schemes can be more accurate than standard discretizations.
Fine structure of the local pseudogap and Fano effect for superconducting electrons near a zigzag graphene edge

Motivated by recent scanning tunneling experiments on zigzag-terminated graphene, this paper investigates an interplay of evanescent and extended quasiparticle states in the local density of states near a zigzag edge using the Green's function of the Dirac equation. A model system is considered where the local electronic structure near the edge influences transport of both normal and superconducting electrons via a Fano resonance. In particular, the temperature enhancement of the critical Josephson current and $0\text{\ensuremath{-}}\ensuremath{\pi}$ transitions are predicted.
n-ary algebras: a review with applications

This paper reviews the properties and applications of certain n-ary generalizations of Lie algebras in a self-contained and unified way. These generalizations are algebraic structures in which the two-entry Lie bracket has been replaced by a bracket with n entries. Each type of n-ary bracket satisfies a specific characteristic identity which plays the role of the Jacobi identity for Lie algebras. Particular attention will be paid to generalized Lie algebras, which are defined by even multibrackets obtained by antisymmetrizing the associative products of its n components and that satisfy the generalized Jacobi identity, and to Filippov (or n-Lie) algebras, which are defined by fully antisymmetric n-brackets that satisfy the Filippov identity. 3-Lie algebras have surfaced recently in multi-brane theory in the context of the Bagger–Lambert–Gustavsson model. As a result, Filippov algebras will be discussed at length, including the cohomology complexes that govern their central extensions and their deformations (it turns out that Whitehead's lemma extends to all semisimple n-Lie algebras). When the skewsymmetry of the Lie or n-Lie algebra bracket is relaxed, one is led to a more general type of n-algebras, the n-Leibniz algebras. These will be discussed as well, since they underlie the cohomological properties of n-Lie algebras. The standard Poisson structure may also be extended to the n-ary case. We shall review here the even generalized Poisson structures, whose generalized Jacobi identity reproduces the pattern of the generalized Lie algebras, and the Nambu–Poisson structures, which satisfy the Filippov identity and determine Filippov algebras. Finally, the recent work of Bagger–Lambert and Gustavsson on superconformal Chern–Simons theory will be briefly discussed. Emphasis will be made on the appearance of the 3-Lie algebra structure and on why the A4 model may be formulated in terms of an ordinary Lie algebra, and on its Nambu bracket generalization.