Study detects spoofing in high-frequency trading using micro-structural analysis.
problem Challenges in detecting spoofing due to complex electronic platforms and high-frequency trading.
method Micro-structural study in a simplified setting, optimization of spoofing strategy, monitoring with Wasserstein distance.
result Optimal spoofing strategy and its impact on market imbalance quantified.
This research aims to develop robust audio spoofing detection methods that work across various spoofing techniques.
problem Detecting audio spoofing attacks in speaker verification systems.
method Examined traditional and machine learned audio features for robust spoofing detection.
result Fused models based on both known and machine learned features achieve comparable performance with an EER of 12.
Improved speaker verification system detects replay attacks.
problem Detecting replay attacks in speaker verification systems.
method Multi-task learning of noise classes (replay noise, recording environment, recording device noises) and spoofing detection.
result Performance improved by 30% on ASVspoof2017 datasets.
Growing interest in automatic speaker verification (ASV)systems has lead to significant quality improvement of spoofing attackson them. Many research works confirm that despite the low equal er-ror rate (EER) ASV systems are still vulnerable to spoofing attacks. Inthis work we overview different acoustic feature spaces…
New CNN architecture detects face spoofing with deep local features.
problem Face recognition systems are vulnerable to face spoofing attacks.
method Two-step CNN architecture: first learns features from facial regions, then fine-tunes on whole images.
result Improves face spoofing detection performance and convergence speed.
Real-time detection of spoofing in cryptocurrency exchanges using neural networks.
problem Detecting and mitigating spoofing activity in limit order books.
method Novel order flow variables based on multi-scale Hawkes processes and a probabilistic market manipulation gain model.
result 31% of large orders could spoof the market, highlighting the importance of posting distance in price formation.
Paper proposes a GRU model to detect spoofing in retail investors.
problem Spoofing in unregulated markets with retail investors.
method GRU-based detection model using market variables.
result Model performs well in early detection of spoofing attempts.
Visual spoofing bypasses spam filters and plagiarism detection.
problem Vulnerability in spam filters that can be exploited by visually similar but differently encoded characters.
method Replaces characters with visually similar but differently encoded characters from a different alphabet.
result Spammers can create messages that bypass existing spam filters.
It is well known that speaker verification systems are subject to spoofing attacks. The Automatic Speaker Verification Spoofing and Countermeasures Challenge -- ASVSpoof2015 -- provides a standard spoofing database, containing attacks based on synthetic speech, along with a protocol for experiments. This paper describe…
Self-supervised method detects replay spoofing using acoustic configurations.
problem Challenges in collecting large-scale datasets for replay spoofing detection.
method Self-supervised pretraining of acoustic configurations using existing datasets.
result The method outperforms baseline by 30% on ASVspoof 2019 physical access dataset.
New metric t-DCF improves ASVspoof challenge results by considering spoofing attack prior.
problem Shortcomings of EER metric in assessing CMs and ASV together.
method Developed t-DCF metric with 6 parameters to assess ASV and CMs together.
result t-DCF shows different rankings for higher spoofing attack priors.
New algorithm localizes spoofing attackers using tropical geometry.
problem Localizing spoofing attackers in digital systems.
method Adaptive pruning algorithm based on tropical geometry.
result Adaptive pruning improves localisation accuracy.
STC systems improved deep learning for ASVspoof2019 challenge.
problem Detecting spoofing attacks in speech recognition.
method Deep learning, Light CNN architecture, angular margin based softmax activation.
result Achieved EER of 1.86% in logical access and 0.54% in physical access scenarios.
Paper proposes D3M to improve anti-spoofing detection by balancing loss function and using complementary features.
problem Improving automatic speaker verification systems against high-quality playback attacks.
method D3M uses a balanced focal loss function to dynamically scale loss based on sample traits, and combines three feature types for robust detection.
result D3M systems outperform conventional methods significantly, achieving min-tDCF of 0.0124 and EER of 0.55%.
This paper presents the Speech Technology Center (STC) replay attack detection systems proposed for Automatic Speaker Verification Spoofing and Countermeasures Challenge 2017. In this study we focused on comparison of different spoofing detection approaches. These were GMM based methods, high level features extraction …
This study examines LiDAR spoofing attacks on autonomous vehicle perception.
problem Security vulnerabilities in LiDAR-based perception systems in autonomous driving.
method Formulated as an optimization problem, designed input perturbation and objective functions, combined optimization and global sampling.
result Attack success rates improved to around 75% through strategic input perturbation.
This paper presents the Speech Technology Center (STC) systems submitted to Automatic Speaker Verification Spoofing and Countermeasures (ASVspoof) Challenge 2015. In this work we investigate different acoustic feature spaces to determine reliable and robust countermeasures against spoofing attacks. In addition to the c…
New method uses statistical physics to detect financial market manipulation.
problem Detecting financial market manipulation activities like spoofing and layering.
method Modeling order book dynamics as particle motion and using momentum measure.
result Method outperforms conventional Z-score-based anomaly detection.
Framework detects covert financial market manipulation using LOB representations.
problem Detecting covert financial market manipulation (spoofing) from complex anomaly patterns in multilevel prices.
method Cascaded contrastive representation learning of LOB data.
result Transformer-based architectures achieve state-of-the-art results in detection performance.
A new system detects audio replay attacks with high accuracy.
problem Detecting and preventing audio replay attacks in speaker verification systems.
method Proposes Attentive Filtering Network combining attention-based filtering and ResNet classifier.
result Achieves EER of 8.99% on ASVspoof 2017 Version 2.0 dataset.
GAN-based spoofing attacks improve wireless signal authentication.
problem Improving wireless signal authentication against sophisticated spoofing attacks.
method Generative Adversarial Network (GAN) for generating synthetic signals.
result GAN-based spoofing attacks significantly increase the success probability of wireless signal spoofing.
Study uses spoofing countermeasures to assess speech processing artifacts in voice conversion.
problem Difficulty in objectively assessing speech processing artifacts in voice conversion.
method Configured a constant-Q cepstral coefficient (CQC) model to measure artifact extent.
result Identified two clusters of VCC'18 entries: low-quality with detectable artifacts and higher quality with less artifacts.
Physics-informed diffusion model detects anomalous trajectories in GPS data.
problem Detecting fake GPS trajectories in international waters.
method Physics-informed diffusion model integrating kinematic constraints.
result Higher prediction accuracy and lower error rate for anomaly detection.
RL agent learns to avoid market spoofing.
problem Avoiding subtle non-normative behavior in trading agents.
method Learned recognizer incorporated into RL agent's reward function.
result RL agent avoids spoofing while remaining profitable.
Framework detects and ranks suspicious market manipulation using temporal convolutions and expert assessment.
problem Detecting and deterring rogue agents in financial markets.
method Weakly supervised learning, expert assessment, similarity search.
result Promising preliminary results in detecting and ranking suspicious market manipulation.
Market manipulation is a strategy used by traders to alter the price of financial securities. One type of manipulation is based on the process of buying or selling assets by using several trading strategies, among them spoofing is a popular strategy and is considered illegal by market regulators. Some promising tools h…
Study improves low-quality speech data for voice cloning.
problem Feasibility of training spoofing systems with low-quality data.
method Developed a GAN-based speech enhancement system, trained TTS and voice conversion models.
result Significant improvement in SNR and perceptual cleanliness of low-quality data.
This study combines ASV and CM systems for better performance using reinforcement learning.
problem Improving the combined performance of ASV and CM systems for better t-DCF measure.
method Training ASV and CM components together using reinforcement learning.
result Training ASV and CM components together improves the performance of the combined system.
Machine learning enhances physical layer attacks on IoT devices using OFDM.
problem Machine learning improves physical layer attacks on IoT devices using OFDM.
method Investigates supervised and unsupervised machine learning approaches to exploit non-contiguous OFDM systems.
result Variational autoencoders can learn PHY characteristics from NC-OFDM signals, enabling spoofing.
A tree-based IDS detects cyber-attacks in AV networks.
problem Cyber-attacks in AV and IoV networks.
method Tree-structure machine learning models, ensemble learning, feature selection.
result High detection rate and low computational cost achieved.
New spoofing strategies show PoL verification is more vulnerable than previously thought.
problem Vulnerability of Proof-of-Learning verification mechanisms.
method Developed new spoofing strategies that can be reproduced across different configurations and are more cost-effective.
result Current PoL verification is not robust to adversaries and requires further understanding of optimization in deep learning.
TinyML models detect RF and cyber threats in spacecraft with low latency.
problem Detecting cyber-RF threats in autonomous spacecraft with low latency.
method Analysis of classical models (RF, LR, SVM, MLP) for latency-accuracy trade-offs.
result Logistic Regression achieves microsecond-level inference with minimal accuracy loss.
Enhances 2D face recognition with 3D features using active illumination.
problem Improving robustness of 2D face recognition to spoofing attacks and low-light conditions.
method Projecting a high spatial frequency pattern onto the face to recover 3D information and a 2D image simultaneously.
result Significantly boosts face recognition performance and dramatically improves robustness to spoofing attacks.
Complex-valued neural networks improve wireless fingerprinting robustness.
problem Distinguish between devices sending the same message, robust against spoofing.
method Used complex-valued neural networks for supervised learning of fingerprints from wireless signals.
result Noise augmentation by adding white Gaussian noise leads to significant performance gains.
New attack tricks certifiably robust models into mislabeling images.
problem Defeating certified defenses against adversarial examples.
method Spoofed robustness certificates and large perturbations.
result Certifiably robust models can be fooled by large perturbations.
Study uses agent-based simulation to analyze impact of OBI strategy on financial markets.
problem Improving execution in markets with supply-demand imbalance.
method Built an execution algorithm that accounts for OBI, tested it in artificial markets.
result OBI strategy can improve execution, especially in volatile markets.
Machine learning enhances wireless network authentication for diverse devices.
problem Complex dynamic wireless environments challenge conventional authentication methods.
method Intelligent authentication using machine learning for diverse physical layer attributes.
result Machine learning-based authentication provides cost-effective, reliable, and situation-aware security.
The paper analyzes algorithmic trading in cryptocurrency exchanges, finding a profitable strategy involving indirect conversions.
problem Lack of empirical analysis of algorithmic trading in cryptocurrency exchanges.
method Empirical analysis using historical trades data from Binance.
result A triangular arbitrage strategy yields a 14.4 basis point advantage over direct exchanges.
Study shows mimicry attacks fail even with ASV-assisted target selection.
problem Can mimicry attacks be successful with ASV-assisted target selection?
method Used ASV to select target speakers for mimicry attacks and tested with x-vector system.
result Mimics did not succeed in spoofing the x-vector system, but relative ordering of targets was consistent.
This study examines non-retail trading on Polymarket, revealing unique behavior patterns and structural limitations.
problem Lack of address-level quote-lifecycle data in Polymarket prediction markets.
method Empirical analysis of 13 million order-filled events using DBSCAN clustering on a six-feature fill-side vector.
result Non-retail behavior is uni-modal, contradicting previous archetypal hypotheses.
ECGID research focuses on rest but not exercise, this study evaluates both.
problem ECGID performance under exercise is insufficiently studied.
method Various learning methods applied to ECG dataset.
result Current ECGID methods fail under exercise conditions.
Quantum Proof-of-Work uses boson sampling to secure blockchain consensus.
problem Ensuring secure and efficient blockchain consensus.
method Proposes using quantum boson sampling as a Proof-of-Work scheme for blockchain.
result Demonstrates a robust and energy-efficient PoW scheme.
Study provides long-term EMG data for multi-day biometric authentication.
problem Limited long-term EMG data for multi-day biometric authentication.
method Collected EMG data from 43 participants over three days.
result Multi-day biometric authentication results in low error rates.
New AI governance framework tackles risks in finance.
problem Risks from evolving AI models in finance.
method Agent-based framework with modular governance architecture.
result Controls quarantine harmful behavior in real time.
Study examines cyber losses across sectors, finds high severity and frequency.
problem Understanding the nature of cyber losses and their variability across sectors.
method Analysis of a leading industry dataset of cyber events, focusing on frequency and severity.
result Cyber risks are heavy-tailed, with high probability of extreme losses.
New link detection results using closures of 3-braids.
problem Link detection using homology theories.
method Closure operations on 3-braids and homology theories.
result Detection of specific links using link Floer homology, Khovanov homology, and annular Khovanov homology.
Deep learning improves anomaly detection across various fields.
problem Detecting anomalies in data with advanced approaches.
method Survey of deep learning methods for anomaly detection.
result Advancements in deep anomaly detection address unique challenges.
Flexible pipeline for 3D vehicle detection from 2D images.
problem Current methods lack 3D perception of vehicles and other objects.
method Adopt any 2D detection network, fuse with 3D point cloud, develop model fitting algorithm, refine with CNN.
result 3D detection results rank second among algorithms, demonstrating competencies.