Monday, 03 April 2023

02:26 AM

Generating Adversarial Samples in Mini-Batches May Be Detrimental To Adversarial Robustness. (arXiv:2303.17720v1 [cs.LG]) [cs.CR updates on arXiv.org]

Neural networks have been proven to be both highly effective within computer vision, and highly vulnerable to adversarial attacks. Consequently, as the use of neural networks increases due to their unrivaled performance, so too does the threat posed by adversarial attacks. In this work, we build towards addressing the challenge of adversarial robustness by exploring the relationship between the mini-batch size used during adversarial sample generation and the strength of the adversarial samples produced. We demonstrate that an increase in mini-batch size results in a decrease in the efficacy of the samples produced, and we draw connections between these observations and the phenomenon of vanishing gradients. Next, we formulate loss functions such that adversarial sample strength is not degraded by mini-batch size. Our findings highlight a potential risk for underestimating the true (practical) strength of adversarial attacks, and a risk of overestimating a model's robustness. We share our codes to let others replicate our experiments and to facilitate further exploration of the connections between batch size and adversarial sample strength.

Pentimento: Data Remanence in Cloud FPGAs. (arXiv:2303.17881v1 [cs.CR]) [cs.CR updates on arXiv.org]

Cloud FPGAs strike an alluring balance between computational efficiency, energy efficiency, and cost. It is the flexibility of the FPGA architecture that enables these benefits, but that very same flexibility that exposes new security vulnerabilities. We show that a remote attacker can recover "FPGA pentimenti" - long-removed secret data belonging to a prior user of a cloud FPGA. The sensitive data constituting an FPGA pentimento is an analog imprint from bias temperature instability (BTI) effects on the underlying transistors. We demonstrate how this slight degradation can be measured using a time-to-digital (TDC) converter when an adversary programs one into the target cloud FPGA.

This technique allows an attacker to ascertain previously safe information on cloud FPGAs, even after it is no longer explicitly present. Notably, it can allow an attacker who knows a non-secret "skeleton" (the physical structure, but not the contents) of the victim's design to (1) extract proprietary details from an encrypted FPGA design image available on the AWS marketplace and (2) recover data loaded at runtime by a previous user of a cloud FPGA using a known design. Our experiments show that BTI degradation (burn-in) and recovery are measurable and constitute a security threat to commercial cloud FPGAs.

Social Honeypot for Humans: Luring People through Self-managed Instagram Pages. (arXiv:2303.17946v1 [cs.SI]) [cs.CR updates on arXiv.org]

Social Honeypots are tools deployed in Online Social Networks (OSN) to attract malevolent activities performed by spammers and bots. To this end, their content is designed to be of maximum interest to malicious users. However, by choosing an appropriate content topic, this attractive mechanism could be extended to any OSN users, rather than only luring malicious actors. As a result, honeypots can be used to attract individuals interested in a wide range of topics, from sports and hobbies to more sensitive subjects like political views and conspiracies. With all these individuals gathered in one place, honeypot owners can conduct many analyses, from social to marketing studies.

In this work, we introduce a novel concept of social honeypot for attracting OSN users interested in a generic target topic. We propose a framework based on fully-automated content generation strategies and engagement plans to mimic legit Instagram pages. To validate our framework, we created 21 self-managed social honeypots (i.e., pages) on Instagram, covering three topics, four content generation strategies, and three engaging plans. In nine weeks, our honeypots gathered a total of 753 followers, 5387 comments, and 15739 likes. These results demonstrate the validity of our approach, and through statistical analysis, we examine the characteristics of effective social honeypots.

Robust and IP-Protecting Vertical Federated Learning against Unexpected Quitting of Parties. (arXiv:2303.18178v1 [cs.CR]) [cs.CR updates on arXiv.org]

Vertical federated learning (VFL) enables a service provider (i.e., active party) who owns labeled features to collaborate with passive parties who possess auxiliary features to improve model performance. Existing VFL approaches, however, have two major vulnerabilities when passive parties unexpectedly quit in the deployment phase of VFL - severe performance degradation and intellectual property (IP) leakage of the active party's labels. In this paper, we propose \textbf{Party-wise Dropout} to improve the VFL model's robustness against the unexpected exit of passive parties and a defense method called \textbf{DIMIP} to protect the active party's IP in the deployment phase. We evaluate our proposed methods on multiple datasets against different inference attacks. The results show that Party-wise Dropout effectively maintains model performance after the passive party quits, and DIMIP successfully disguises label information from the passive party's feature extractor, thereby mitigating IP leakage.

Detecting Backdoors During the Inference Stage Based on Corruption Robustness Consistency. (arXiv:2303.18191v1 [cs.CR]) [cs.CR updates on arXiv.org]

Deep neural networks are proven to be vulnerable to backdoor attacks. Detecting the trigger samples during the inference stage, i.e., the test-time trigger sample detection, can prevent the backdoor from being triggered. However, existing detection methods often require the defenders to have high accessibility to victim models, extra clean data, or knowledge about the appearance of backdoor triggers, limiting their practicality. In this paper, we propose the test-time corruption robustness consistency evaluation (TeCo), a novel test-time trigger sample detection method that only needs the hard-label outputs of the victim models without any extra information. Our journey begins with the intriguing observation that the backdoor-infected models have similar performance across different image corruptions for the clean images, but perform discrepantly for the trigger samples. Based on this phenomenon, we design TeCo to evaluate test-time robustness consistency by calculating the deviation of severity that leads to predictions' transition across different corruptions. Extensive experiments demonstrate that compared with state-of-the-art defenses, which even require either certain information about the trigger types or accessibility of clean data, TeCo outperforms them on different backdoor attacks, datasets, and model architectures, enjoying a higher AUROC by 10% and 5 times of stability.

Saturday, 01 April 2023

Friday, 31 March 2023

02:35 AM

[Comment] Effect of a nationwide intervention of electronic letters with behavioural nudges on influenza vaccination in older adults in Denmark [The Lancet]

Worldwide influenza epidemics result in an estimated 3–5 million cases of severe illness, and 290 000–650 000 respiratory deaths annually.1 Influenza also leads to high costs from direct medical expenses and lost productivity.2 Influenza vaccination is the single most important preventive measure against influenza, and as such is recommended worldwide.1 Adults aged 65 years or older are at particularly high risk for severe outcomes related to influenza.1 However, annual vaccination rates of older adults vary globally from less than 10% up to 80%.

[Comment] Offline: Here is how we avoid collapse [The Lancet]

WHO is celebrating health for all on World Health Day (April 7). The agency's messages are important and familiar—that all people deserve good health in a peaceful, prosperous, and sustainable world; that health is an essential human right; and that universal health coverage is the means to that end. No one could argue with WHO's intentions. But there is an important missing truth. The planet and the life it nurtures are under threat from our own greed, exploitation, and mendacity. Unless the dangers humans have created are addressed, health for all will be nothing more than whimsical fantasy.

[Correspondence] Japanese medical workers' sacrifice for universal health coverage [The Lancet]

As a Japanese clinician working under universal health coverage in Japan, I feel great discomfort with regard to Prime Minister Fumio Kishida's Comment.1

[Correspondence] Intersectional inequities in academia [The Lancet]

Gender equality in academia still faces enduring challenges globally, with under-representation of women in leadership and decision-making positions. However, most universities and research institutions actively implement gender equality plans and undertake activities aimed at increasing it. Despite this remarkable progress, intersectionality lags behind. This term, first coined by Kimberlé Crenshaw, corresponds to the “lens through which you can see where power comes and collides, where it interlocks and intersects”.

[Articles] Electronic nudges to increase influenza vaccination uptake in Denmark: a nationwide, pragmatic, registry-based, randomised implementation trial [The Lancet]

Electronically delivered letters highlighting potential cardiovascular benefits of influenza vaccination or sent again as a reminder significantly increased vaccination uptake across Denmark. Although the magnitude of effectiveness was modest, the low-touch, inexpensive, and highly scalable nature of these electronic letters might be informative for future public health campaigns.

Wednesday, 29 March 2023

06:22 PM

All-perovskite tandem 1 cm2 cells with improved interface quality [Nature]

Nature, Published online: 29 March 2023; doi:10.1038/s41586-023-05992-y

All-perovskite tandem 1 cm2 cells with improved interface quality

Thousands of conductance levels in memristors integrated on CMOS [Nature]

Nature, Published online: 29 March 2023; doi:10.1038/s41586-023-05759-5

Chips with 256 × 256 memristor arrays that were monolithically integrated on complementary metal–oxide–semiconductor (CMOS) circuits in a commercial foundry achieved 2,048 conductance levels in individual memristors.

Mechanistic formulation of inorganic membranes at the air–liquid interface [Nature]

Nature, Published online: 29 March 2023; doi:10.1038/s41586-023-05809-y

By switching the nucleation preferences in aqueous systems of inorganic precursors to bias formation and growth at the air–liquid interface, the mechanistic formation of inorganic membranes from the floating-particle system is demonstrated.

‘Astonishing’ molecular syringe ferries proteins into human cells [Nature]

Nature, Published online: 29 March 2023; doi:10.1038/d41586-023-00922-4

Technique borrowed from nature, and honed using artificial intelligence, could spur the development of better drug-delivery systems.

02:40 AM

Suppressed phase segregation for triple-junction perovskite solar cells [Nature]

Nature, Published online: 28 March 2023; doi:10.1038/s41586-023-06006-7

Suppressed phase segregation for triple-junction perovskite solar cells

Selective Decontamination of the Digestive Tract and Hospital Mortality in Critically Ill Patients Receiving Mechanical Ventilation [JAMA Current Issue]

To the Editor A recent trial of critically ill patients in Australia found that SDD had no statistically significant effect on mortality. We question whether SDD was actually delivered in this study.

Human Mpox Virus Infection After Receipt of Modified Vaccinia Ankara Vaccine [JAMA Current Issue]

To the Editor I have some concerns about a recent Research Letter that presented data about human mpox (formerly monkeypox) virus infection after patients received the modified vaccinia Ankara–Bavarian Nordic vaccine (MVA-BN [JYNNEOS]).

Human Mpox Virus Infection After Receipt of Modified Vaccinia Ankara Vaccine—Reply [JAMA Current Issue]

In Reply In response to our Research Letter on mpox infection in the immediate period following vaccination with MVA-BN, Dr Zhou raises 2 important concerns about how to better assess vaccine effectiveness of MVA-BN against mpox.

Preserving Pancreatic Beta Cell Function in Recent-Onset Type 1 Diabetes [JAMA Current Issue]

Type 1 diabetes is a common autoimmune disease in which progressive loss of pancreatic beta cells results in lifelong dependence on insulin. Despite rapid advances in the technology for insulin delivery and glucose monitoring, it remains challenging for patients to reach optimal glycemic control to prevent the serious long-term complications associated with type 1 diabetes. Even modest amounts of endogenous insulin production provide substantial benefits by improving glycemic control and reducing the risk of hypoglycemia and vascular complications. Effective interventions that preserve beta cell function both before and after the diagnosis of type 1 diabetes are therefore enormously welcome.

Tuesday, 28 March 2023

02:32 AM

Glass Segmentation With RGB-Thermal Image Pairs [IEEE Transactions on Image Processing - new TOC]

This paper proposes a new glass segmentation method utilizing paired RGB and thermal images. Due to the large difference between the transmission property of visible light and that of the thermal energy through the glass where most glass is transparent to the visible light but opaque to thermal energy, glass regions of a scene are made more distinguishable with a pair of RGB and thermal images than solely with an RGB image. To exploit such a unique property, we propose a neural network architecture that effectively combines an RGB-thermal image pair with a new multi-modal fusion module based on attention, and integrate CNN and transformer to extract local features and non-local dependencies, respectively. As well, we have collected a new dataset containing 5551 RGB-thermal image pairs with ground-truth segmentation annotations. The qualitative and quantitative evaluations demonstrate the effectiveness of the proposed approach on fusing RGB and thermal data for glass segmentation. Our code and data are available at https://github.com/Dong-Huo/RGB-T-Glass-Segmentation.

Accumulated Error Reduction of Linear Motor Mover Position Measurement Based on SKLM [IEEE Transactions on Industrial Informatics - new TOC]

Cumulative measurement error is the most critical factor affecting the accuracy of long-stroke displacement measurement. Based on the 1-D image gradient method and smooth Kalman filter algorithm, this article proposes a long-stroke linear motor displacement cumulative error reduction and high-precision measurement methods. First, according to the motion characteristics of the linear motor and the principle of image measurement, a 1-D speckle target image is generated, and the 1-D Barron gradient algorithm is used to calculate the displacement of adjacent frames quickly. Second, according to the reasons for the accumulated error of long-stroke displacement measurement, the smooth Kalman algorithm for optimized autoregressive data processing is introduced to optimally estimate the measured displacement of adjacent frames to realize the reduction of accumulated error. To improve the robustness of the measurement system, a wavelet soft-threshold image filter is introduced to perform noise reduction and restoration processing on the collected signal and further realize the high-precision displacement measurement of the long-stroke linear motor. Simulations and experiments show that the method presented in this article not only improves the measurement accuracy of adjacent frames but also reduces the cumulative error of long-stroke displacement measurement. And under different working conditions, compared with other methods, it has higher accuracy and anti-interference.

Characterization of Angular RCF Cracks in a Railway Using Modified Topology of WPT-Based Eddy Current Testing [IEEE Transactions on Industrial Informatics - new TOC]

Unavoidably, rolling contact fatigue (RCF) causes natural crack formation in the railhead, leading to rupture. Eddy current testing (ECT) is commonly used to quantify RCF cracks because of its higher sensitivity to a surface flaw, though with limited feature points. This article aims to characterize inclined angular RCF crack parameters in a rail-line material via a modified topology of Wireless Power Transfer (WPT)-based ECT (WPTECT) due to its magnetically coupled resonant for excitation and sensing circuits and utilize multiple resonance responses compared to other ECT. We experimentally designed and evaluated WPTECT and extracted multiple resonances and principal components analysis features to characterize inclined angular RCF cracks. The response minima point feature quantified the crack parameters incomparably; however, the second resonance feature is better than the first resonance. The reconstructed depth, opening width, and angle of the RCF cracks have a maximum correlation, R2 value of 96.4%, 93.1%, and 79.1%, respectively, and root mean square error of 0.05 mm, 0.08 mm, and 6.6°, respectively.

Cyber-Resilient Control of an Islanded Microgrid Under Latency Attacks and Random DoS Attacks [IEEE Transactions on Industrial Informatics - new TOC]

The information exchange among distributed energy resources (DERs) in microgrids (MGs) is through sensing and communication systems, which are prone to expose cyber-attack threats. This article investigates the stability issue of MG systems with distributed secondary control under latency attacks and random denial-of-service (DoS) attacks. Considering these two kinds of attack modes, the corresponding attack consequences including network jamming and time-varying latency in the communication network are simultaneously studied. First, a new metric is defined to quantify the DoS attacks by considering different network jamming choices. Then, the time-domain stability study is conducted considering both attack consequences. Next, a cyber-resilient control strategy is proposed with two control modes: 1) An adaptive-gain resilient controller to sustain the fast stabilization of MG systems under nonuniform time-varying latency attacks, which is proved by the stochastic stability analysis using Lyapunov–Krasovskii functional method. 2) An event-trigger topology reconfiguration controller against excessive latency and damaged cyber connectivity caused by DoS attacks. A switching mechanism for coordinating the above control modes is also designed to guarantee the secondary control functions of MG systems. A modified IEEE 13-bus MG system with five DERs is tested and the effectiveness of the proposed controller under different attack scenarios is verified by OPAL-RT real-time tests.

Design of Broad Learning-Based Self-Healing Predictive Control for Sludge Bulking in Wastewater Treatment Process [IEEE Transactions on Industrial Informatics - new TOC]

Self-healing control plays a crucial role in taking remedial action to minimize the adverse impacts of sludge bulking in wastewater treatment process (WWTP). However, since sludge bulking is a strong nonlinear and complex process with multiple fault conditions, the conventional self-healing control is difficult to obtain reliable performance. Thus, the purpose of this article is to design a broad learning-based self-healing predictive controller (BL-SHPC) for sludge bulking in WWTP. The main innovations of the proposed controller are threefold. First, a dynamic fuzzy broad learning system with an adaptive expansion strategy is used to identify the fault conditions of sludge bulking. Then, the fault features of sludge bulking can be comprehensively extracted with desirable performance. Second, a prioritized multiobjective optimization algorithm-based predictive control, which considers the objective correlation and preference of fault conditions, is presented to obtain the optimal solutions to achieve self-healing. Then, the proposed controller can feasibly and precisely readjust manipulated variables to eliminate the sludge bulking. Third, the stability of the developed controller is proved by the Lyapunov stability theorem. Then, the stability analysis can ensure the successful application of BL-SHPC. Finally, the proposed BL-SHPC is tested on the Benchmark Simulation Model No.2 to validate its merits. The simulation results indicate that the proposed controller can obtain superior self-healing ability for sludge bulking in WWTP.

Tuesday, 21 March 2023

02:28 AM

Simple Predictive Current Control of Asymmetrical Six-Phase Induction Motor With Improved Performance [IEEE Transactions on Industrial Electronics - new TOC]

Despite the intensive research work on the application of model predictive control for multiphase machines, there are many challenges still to be handled such as high circulating currents, variable switching frequency, and high computation burden. This article proposes a simple, yet efficient predictive current control (PCC) for a six-phase induction motor that reduces considerably circulating current, computation cost, and switching frequency. In the proposed method, a group of four candidate voltage vectors (VVs) is formed in each control sample. Unlike similar methods reported in the literature, these candidate vectors are generated based on a simple lookup table and the previous optimal VV. The lookup table is designed such that it allows only one commutation in each control sample. The performance of the proposed method is assessed experimentally using a 1-kW asymmetrical six-phase induction motor. Different performance indices are investigated to compare the proposed method against two different PCC methods in literature at different operating conditions. The experimental results confirm that about a 50% reduction in average switching frequency and 15% in current total harmonic distortion at different speed ranges are observed with the proposed method compared to the conventional one.

Torque-Ripple Reduction of Permanent Magnet Synchronous Machine Drives Based on Novel Speed Harmonic Control at Low-Speed Operation [IEEE Transactions on Industrial Electronics - new TOC]

Torque-ripple reduction methods based on harmonic current injection for permanent magnet synchronous machine (PMSM) drives have been widely discussed, while the performance of torque-ripple-model-based methods is limited due to model accuracy as well as the rotor position errors, and the speed harmonic control-based methods still cannot get rid of the impact of the phase information of speed harmonics, which results in remaining torque ripples and the difficulty in designing speed harmonic controller. In this article, the unique relationships between the quadrature magnitudes of speed harmonics and harmonic currents are derived considering the minimal conduction copper loss by the harmonic currents. Based on that, a novel torque-ripple reduction method based on the speed harmonic control is proposed, wherein a novel speed harmonic controller is presented to regulate the quadrature magnitudes of speed harmonics so that the phase of speed harmonics is avoided in the speed harmonic controller. Also, the proposed speed harmonic controller aims to generate harmonic current references. The proposed methodology is evaluated by experiments and is verified to reduce torque ripples of PMSM drives effectively.

An Efficient Online Loop Closure Detection System With Local Spatial Co-Occurrence Information [IEEE Transactions on Industrial Electronics - new TOC]

As a vital component in simultaneous localization and mapping techniques, appearance-based loop closure detection (LCD) plays important roles in bounding the long-term drift errors. In this article, an online LCD system based on the mutual co-occurrence information among visual features is proposed. First, a feature tracker module is designed to generate distinctive visual words, exploiting tracked words tool to improve efficiency. Then, an incrementally built vocabulary is organized by a hierarchical navigable small world graph, where the visual words are indexed. To merge a homologous word into the existing one, the vocabulary applies an improved high-dimensional online clustering method, which regards individual cluster as a normal distribution form. At the query phase, a list of candidate frames is located due to the co-occurrence constraint. Ultimately, the loop closure is specified by passing the temporal and similarity check, which avoids the memory consumption of historic image data. Validation tests based on public datasets and experimental sequences demonstrate the merit of low running time and memory cost while the high-precision performance is retained in the system.

TICBot: Development of a Tensegrity-Based In-Pipe Crawling Robot [IEEE Transactions on Industrial Electronics - new TOC]

This article presents the development of a novel tensegrity-based robot, TICBot, which is capable of crawling in tubular environments. Based on the concept of tensegrity, a deformable robotic module consisted of discrete rigid struts and a continuous net of elastic springs is proposed. Then, the in-pipe crawling robot is designed by serially cascading three uniform modules. The mechanical structure of the robotic module is determined using force density method on the basis of kinematic and static analysis. Performance of the robot in aspects of shape changeability, mobility, load capacity, and adaptability are tested on the prototype. Experimental results show that the robot has the abilities to crawl in pipes with different inner diameters and shapes, and to pass through elbow pipes adaptively under the control of a simple actuation sequence. Compared with existing robots, this proposed approach enables more compact structures along with enhanced mobility and adaptability. This article validates the effectiveness of our proposal and provides a new approach for developing in-pipe crawling robots and other bioinspired robots.

Analytical Method to Calculate Inductances of Spoke-Type Permanent-Magnet Synchronous Motors With Damping Bars [IEEE Transactions on Industrial Electronics - new TOC]

This article proposes an analytical method to calculate inductances and resistances related to damping circuits of spoke-type permanent-magnet synchronous motor (PMSM) with damping bars. Harmonics of inductances are taken into account analytically in order to obtained the performance of line-start PMSM. Damping bars of spoke-type PMSM are divided into direct-axis and quadrature-axis damping circuits. The magnetic field, self-inductances, and resistances of damping circuits and mutual inductances between damping circuits and stator winding are predicted analytically. The calculating results show that the inductances and resistances of spoke-type PMSM with damping bars by the proposed analytical method are well agreement with that predicted by the finite-element method. The line-start process of spoke-type PMSM with the multidamping circuit model in which the inductances and resistances are calculated analytically is also similar with the experimental results. The finite-element and experimental results confirm that the developed analytical method has high accuracy for predicting inductances, resistances, and performance of spoke-type PMSM.

Tuesday, 07 March 2023

02:57 AM

Fine-Grained Feature Generation for Generalized Zero-Shot Video Classification [IEEE Transactions on Image Processing - new TOC]

Generalized zero-shot video classification aims to train a classifier to classify videos including both seen and unseen classes. Since the unseen videos have no visual information during training, most existing methods rely on the generative adversarial networks to synthesize visual features for unseen classes through the class embedding of category names. However, most category names only describe the content of the video, ignoring other relational information. As a rich information carrier, videos include actions, performers, environments, etc., and the semantic description of the videos also express the events from different levels of actions. In order to use fully explore the video information, we propose a fine-grained feature generation model based on video category name and its corresponding description texts for generalized zero-shot video classification. To obtain comprehensive information, we first extract content information from coarse-grained semantic information (category names) and motion information from fine-grained semantic information (description texts) as the base for feature synthesis. Then, we subdivide motion into hierarchical constraints on the fine-grained correlation between event and action from the feature level. In addition, we propose a loss that can avoid the imbalance of positive and negative examples to constrain the consistency of features at each level. In order to prove the validity of our proposed framework, we perform extensive quantitative and qualitative evaluations on two challenging datasets: UCF101 and HMDB51, and obtain a positive gain for the task of generalized zero-shot video classification.

Friday, 03 March 2023

04:10 AM

Multi-Exposure Image Fusion via Deformable Self-Attention [IEEE Transactions on Image Processing - new TOC]

Most multi-exposure image fusion (MEF) methods perform unidirectional alignment within limited and local regions, which ignore the effects of augmented locations and preserve deficient global features. In this work, we propose a multi-scale bidirectional alignment network via deformable self-attention to perform adaptive image fusion. The proposed network exploits differently exposed images and aligns them to the normal exposure in varying degrees. Specifically, we design a novel deformable self-attention module that considers variant long-distance attention and interaction and implements the bidirectional alignment for image fusion. To realize adaptive feature alignment, we employ a learnable weighted summation of different inputs and predict the offsets in the deformable self-attention module, which facilitates that the model generalizes well in various scenes. In addition, the multi-scale feature extraction strategy makes the features across different scales complementary and provides fine details and contextual features. Extensive experiments demonstrate that our proposed algorithm performs favorably against state-of-the-art MEF methods.

Saturday, 11 February 2023

Friday, 10 February 2023

02:53 AM

RTrap: Trapping and Containing Ransomware With Machine Learning [IEEE Transactions on Information Forensics and Security - new TOC]

With advances in social engineering tricks and other technical shortcomings, ransomware attacks have become a severe cybercrime affecting organizations of all shapes and sizes. Although the security teams are making plenty of ransomware detection tools, the ransomware incident report shows they are ineffective in detecting emerging ransomware attacks. This work presents “RTrap,” a systematic framework to detect and contain ransomware efficiently and effectively via machine learning-generated deceptive files. Using a data-driven decoy file selection and generation strategy, RTrap plants deceptive decoy files across the directory to lure the ransomware to access it. RTrap also introduced a lightweight decoy watcher to monitor generated decoy files in real time. As the timing of the ransomware attack is not known to the victim in advance, and the ransomware encryption process is speedy, the proposed decoy-watcher executes an automatic/automated response after the detection promptly. The experiment shows that RTrap can detect ransomware with an average 18 file loss per 10311 legitimate user files.

PolarPose: Single-Stage Multi-Person Pose Estimation in Polar Coordinates [IEEE Transactions on Image Processing - new TOC]

Regression based multi-person pose estimation receives increasing attention because of its promising potential in achieving realtime inference. However, the challenges in long-range 2D offset regression have restricted the regression accuracy, leading to a considerable performance gap compared with heatmap based methods. This paper tackles the challenge of long-range regression through simplifying the 2D offset regression to a classification task. We present a simple yet effective method, named PolarPose, to perform 2D regression in Polar coordinate. Through transforming the 2D offset regression in Cartesian coordinate to quantized orientation classification and 1D length estimation in the Polar coordinate, PolarPose effectively simplifies the regression task, making the framework easier to optimize. Moreover, to further boost the keypoint localization accuracy in PolarPose, we propose a multi-center regression to relieve the quantization error during orientation quantization. The resulting PolarPose framework is able to regress the keypoint offsets in a more reliable way, and achieves more accurate keypoint localization. Tested with the single-model and single-scale setting, PolarPose achieves the AP of 70.2% on COCO test-dev dataset, outperforming the state-of-the-art regression based methods. PolarPose also achieves promising efficiency, e.g., 71.5% AP at 21.5FPS and 68.5%AP at 24.2FPS and 65.5%AP at 27.2FPS on COCO val2017 dataset, faster than current state-of-the-art.

Tuesday, 24 January 2023

02:36 AM

TxT: Real-Time Transaction Encapsulation for Ethereum Smart Contracts [IEEE Transactions on Information Forensics and Security - new TOC]

Ethereum is a permissionless blockchain ecosystem that supports execution of smart contracts, the key enablers of decentralized finance (DeFi) and non-fungible tokens (NFT). However, the expressiveness of Ethereum smart contracts is a double-edged sword: while it enables blockchain programmability, it also introduces security vulnerabilities, i.e., the exploitable discrepancies between expected and actual behaviors of the contract code. To address these discrepancies and increase the vulnerability coverage, we propose a new smart contract security testing approach called transaction encapsulation. The core idea lies in the local execution of transactions on a fully-synchronized yet isolated Ethereum node, which creates a preview of outcomes of transaction sequences on the current state of blockchain. This approach poses a critical technical challenge — the well-known time-of-check/time-of-use (TOCTOU) problem, i.e., the assurance that the final transactions will exhibit the same execution paths as the encapsulated test transactions. In this work, we determine the exact conditions for guaranteed execution path replicability of the tested transactions. To demonstrate the transaction encapsulation, we implement a transaction testing tool, TxT, which reveals the actual outcomes (either benign or malicious) of Ethereum transactions. To ensure the correctness of testing, TxT deterministically verifies whether a given sequence of transactions ensues an identical execution path on the current state of blockchain. We analyze over 1.3 billion Ethereum transactions and determine that 96.5% of them can be verified by TxT. We further show that TxT successfully reveals the suspicious behaviors associated with 31 out of 37 vulnerabilities (83.8% coverage) in the smart contract weakness classification (SWC) registry. In comparison, the vulnerability coverage of all the existing defense approaches combined only reaches 40.5&#- 0025;.

Friday, 13 January 2023

02:43 AM

Resilient Load Frequency Control of Multi-Area Power Systems Under DoS Attacks [IEEE Transactions on Information Forensics and Security - new TOC]

Cyber security of modern power systems has become increasingly significant due to their open communication architecture and expanding network connectivity exposed to malicious cyber attacks. Resilient control represents an effective means to preserve the survivability of the power system under cyber attacks. In this paper, we address the resilient load frequency control (LFC) design for multi-area power systems under a new class of time-constrained denial-of-service (DoS) attacks. First, different from the widely-explored duration- and frequency-constrained DoS attack models, we consider a general time-constrained DoS attack model where only the attack durations are confined into some bounds, which represents less a priori knowledge of an attacker’s actions. Second, instead of using a traditional yet conservative time-invariant Lyapunov function (TILF), we develop an attack-parameter-dependent time-varying Lyapunov function (TVLF) approach to enable a resilient LFC design without jeopardizing the desired closed-loop system stability and performance. Furthermore, we provide a formal stability and performance analysis condition as well as a design criterion for the desired DoS-resilient output feedback LFC controller. We also show that the minimum allowable sleeping period and the maximum allowable active period of the attacked LFC system can be explicitly disclosed. Finally, we present two simulation case studies on a two-area LFC system and a three-area LFC system to demonstrate the effectiveness of the obtained results.

Thursday, 05 January 2023

06:17 PM

Separatism and identity: a comparative analysis of the Basque and Catalan cases [European Political Science Review]

This paper explores the potential of elections to change our emotions and modify the relevance that voters assign to self-interest and group-identity issues. We examine this question by analyzing the 1998–2016 period of the Catalan and Basque regional elections. The analysis exploits that Basques pushed to leave Spain in the early 2000s, and Catalans pursued independence about fifteen years later. When the separatist goal emerges, two issues gain relevance. First, there is a significant rise of identity politics, associated with the territory’s culture and language, to the detriment of other issues that traditionally explain vote choice, such as the left-right ideology, the degree of regional autonomy, or the economic discontent. Second, the territory becomes more divisive, big cities align against dominant separatist parties, and rural areas align with independentists. We conclude that material self-interests dilute and group-identity factors emerge to determine vote decisions in times of national dissolution.

Unequal inequalities? How participatory inequalities affect democratic legitimacy [European Political Science Review]

Democratic theorists have long emphasized the importance of participatory equality, that is, that all citizens should have an equal right to participate. It is still unclear, however, whether ordinary citizens view this principle as central to democracy and how different violations of this principle affect subjective democratic legitimacy. The attitudes of citizens are imperative when it comes to the subjective legitimacy of democratic systems, and it is therefore important to examine how participatory inequalities affect these attitudes. We here contribute to this research agenda with survey experiments embedded in two surveys (n = 324, n = 840). We here examine (1) whether citizens consider participatory inequality to be an important democratic principle, and (2) how gender and educational inequalities affect subjective legitimacy and the perceived usefulness of the participatory input. The results show that citizens generally consider participatory inequalities to be important, but only gender inequalities affect subjective legitimacy and usefulness. Hence it is important to consider the type of inequality to understand the implications.

Once they are seated: the impact of radical right parties’ political representation on attitudes of trust and solidarity [European Political Science Review]

A close reading of the literature on radical right parties (RRPs) suggests that these parties erode trust and solidarity in European democracies when they pit ‘the pure people’ against political and legal institutions, elites, and immigrants. I propose the conjecture that RRPs with seats in the national parliament have better conditions for spreading nativist and populist messages that may erode trust and solidarity between a society’s residents, between ethnic groups, and towards its political and legal institutions. To test this research question, I combine nine waves of European Social Survey data from 17 countries and data on national elections spanning the years 1999 to 2020. Two-way fixed effects models estimate that RRPs representation in the national parliament is associated with a reduction in public support for redistribution of ca. 18% of a standard deviation. Additionally, I demonstrate that this inverse relationship runs parallel to growing welfare chauvinistic beliefs and that it is stronger in countries with weak integration policies. Contra theoretical expectations, the radical rights’ political representation has not produced any change in societal levels of anti-immigration attitudes, institutional trust, or social trust. While the findings persist across a wide range of robustness checks and other model specifications, threats to identification in the form of non-parallel pre-trends and unobserved sources of confounding, means that one should be cautious in interpreting the findings in a causal manner.

Gender stereotypes in print and online media coverage of Slovak presidential candidates in 2009 and 2019 [European Political Science Review]

In Slovakia, women are poorly represented in politics and public life. Yet it is the first country in Central Europe with a female president. By applying a mixed-methods approach to analyzing an original dataset containing media coverage of leading presidential candidates (n = 1492), this study explores how the media covered them and discusses under what conditions gender-stereotypical coverage could be detrimental or beneficial to electoral outcomes. The results show media outlet type was not significantly associated with a gender-stereotypical attribution of communal and agentic traits to candidates. Tabloids and quality press equally perpetuated gender stereotypes. Irrespective of their gender, journalists were more likely to depict women candidates as possessing communal qualities perceived as incompatible with leadership. However, findings from the qualitative analysis suggest that when corruption perception is high, and public trust in institutions is low, communal traits stereotypically attributed to women are appreciated. Novelty also works to women’s advantage. These findings have important implications for women candidates’ campaign strategies.

Political parties, issue salience, and the appointment of women cabinet members [European Political Science Review]

Do parties relegate female ministers to portfolios that are politically less important for them? This research note contributes to this debate and examines whether the issue salience of parties for specific policy areas has an effect on the nomination of a female minister. Previous theoretical work assumes that party leaders will be more likely to select men for those portfolios that are highly salient for the party. To test this assumption empirically, the paper analyzes the appointment of women cabinet members in the German states between 2006 and 2021. Notably, the findings contradict the theoretical expectations as well as previous empirical results from a cross-national study: On the German sub-national level the nomination of a female minister is more likely if the respective portfolio is highly salient for the governing party. Parties and their policy-preferences seem to be an important factor in explaining the share of women in sub-national cabinets.

Tuesday, 03 January 2023

02:35 AM

A Dynamic-Efficient Structure for Secure and Verifiable Location-Based Skyline Queries [IEEE Transactions on Information Forensics and Security - new TOC]

In a broad range of commercial and government applications, supporting secure location-based query services over outsourced cloud-based services particularly for data update on encrypted datasets remains challenging in practice. Compounding the challenge is the need to ensure update and query efficiency, dataset confidentiality (including against potentially malicious cloud service providers) and query authenticity. Thus in this paper, we propose DynPilot, a novel solution for privacy-preserving verifiable location-based skyline queries over dynamic and encrypted data(sets). The key challenge is how to devise a ciphertext-based authenticated data structure (ADS) that not only protects the confidentiality of the dataset (including the verification phase), but also the effective maintenance of such a dataset. Moreover, to motivate the cloud into actively updating ADS, the digest of the raw dataset is stored in the blockchain due to its immutability and consensus mechanism where update cost is also considered. Therefore, we present a novel ADS (hereafter referred to as Dynamic-Efficient Secure and Verifiable Tree (DSV-tree)), designed to be dynamic and support secure and verifiable skyline queries. Meanwhile, DynPilot also achieves forward privacy using a novel fuzzy update strategy. To further improve the efficiency of queries, an optimized version (i.e., DSV*-tree) is also developed based on the idea of the multi-level index structure. Finally, we analyze the security and complexity of our approach, and the empirical evaluations demonstrate the utility of our approach.

Friday, 23 December 2022

02:35 AM

Fingerprint Template Invertibility: Minutiae vs. Deep Templates [IEEE Transactions on Information Forensics and Security - new TOC]

Much of the success of fingerprint recognition is attributed to minutiae-based fingerprint representation. It was believed that minutiae templates could not be inverted to obtain a high fidelity fingerprint image, but this assumption has been shown to be false. The success of deep learning has resulted in alternative fingerprint representations (embeddings), in the hope that they might offer better recognition accuracy as well as non-invertibility of deep network-based templates. We evaluate whether deep fingerprint templates suffer from the same reconstruction attacks as the minutiae templates. We show that while a deep template can be inverted to produce a fingerprint image that could be matched to its source image, deep templates are more resistant to reconstruction attacks than minutiae templates. In particular, reconstructed fingerprint images from minutiae templates yield a TAR of about 100.0% (98.3%) @ FAR of 0.01% for type-I (type-II) attacks using a state-of-the-art commercial fingerprint matcher, when tested on NIST SD4. The corresponding attack performance for reconstructed fingerprint images from deep templates using the same commercial matcher yields a TAR of less than 1% for both type-I and type-II attacks; however, when the reconstructed images are matched using the same deep network, they achieve a TAR of 85.95% (68.10%) for type-I (type-II) attacks. Furthermore, what is missing from previous fingerprint template inversion studies is an evaluation of the black-box attack performance, which we perform using 3 different state-of-the-art fingerprint matchers. We conclude that fingerprint images generated by inverting minutiae templates are highly susceptible to both white-box and black-box attack evaluations, while fingerprint images generated by deep templates are resistant to black-box evaluations and compar- tively less susceptible to white-box evaluations.

Spike-Based Motion Estimation for Object Tracking Through Bio-Inspired Unsupervised Learning [IEEE Transactions on Image Processing - new TOC]

Neuromorphic vision sensors, whose pixels output events/spikes asynchronously with a high temporal resolution according to the scene radiance change, are naturally appropriate for capturing high-speed motion in the scenes. However, how to utilize the events/spikes to smoothly track high-speed moving objects is still a challenging problem. Existing approaches either employ time-consuming iterative optimization, or require large amounts of labeled data to train the object detector. To this end, we propose a bio-inspired unsupervised learning framework, which takes advantage of the spatiotemporal information of events/spikes generated by neuromorphic vision sensors to capture the intrinsic motion patterns. Without off-line training, our models can filter the redundant signals with dynamic adaption module based on short-term plasticity, and extract the motion patterns with motion estimation module based on the spike-timing-dependent plasticity. Combined with the spatiotemporal and motion information of the filtered spike stream, the traditional DBSCAN clustering algorithm and Kalman filter can effectively track multiple targets in extreme scenes. We evaluate the proposed unsupervised framework for object detection and tracking tasks on synthetic data, publicly available event-based datasets, and spiking camera datasets. The experiment results show that the proposed model can robustly detect and smoothly track the moving targets on various challenging scenarios and outperforms state-of-the-art approaches.

Tuesday, 23 August 2022

Saturday, 13 August 2022

Saturday, 30 July 2022

Friday, 13 May 2022

Thursday, 12 May 2022

06:23 PM

Friday, 16 July 2021

06:18 PM

University of Maryland engineers 3D printed a soft robotic hand that can play Nintendo [EurekAlert! - Breaking News]

A team of researchers from the University of Maryland has 3D printed a soft robotic hand that is agile enough to play Nintendo's Super Mario Bros. - and win!

Galactic fireworks: New ESO images reveal stunning features of nearby galaxies [EurekAlert! - Breaking News]

A team of astronomers has released new observations of nearby galaxies that resemble colourful cosmic fireworks. The images, obtained with the European Southern Observatory's Very Large Telescope (ESO's VLT), show different components of the galaxies in distinct colours, allowing astronomers to pinpoint the locations of young stars and the gas they warm up around them.

Wildfire smoke exposure linked to increased risk of contracting COVID-19 [EurekAlert! - Breaking News]

Wildfire smoke may greatly increase susceptibility to SARS-CoV-2, the virus that causes COVID-19, according to new research from the Center for Genomic Medicine at the Desert Research Institute (DRI), Washoe County Health District (WCHD), and Renown Health (Renown) in Reno, Nev.

02:27 AM

Arrival of land plants changed Earth's climate control system [EurekAlert! - Breaking News]

In a new study, published in the journal Nature, researchers looked at samples from rocks spanning the last three billion years and found evidence of a dramatic change in how the carbon cycle functioned about 400 million years ago, when plants started to colonise land.

Thursday, 15 July 2021

06:17 PM

Human waste contaminating urban water leads to 'superbug' spread -- study [EurekAlert! - Breaking News]

Contamination of urban lakes, rivers and surface water by human waste is creating pools of 'superbugs' in Low- and Middle-Income Countries (LMIC) - but improving access to clean water, sanitation and sewerage infrastructure could help to protect people's health, a new study reveals.

Tuesday, 15 December 2020

06:02 PM

Reply to Elmendorf and Ettinger: Photoperiod plays a dominant and irreplaceable role in triggering secondary growth resumption [Letters (Online Only)] [Early Edition]

In their Letter, Elmendorf and Ettinger (1) question the dominant role of photoperiod in driving secondary growth resumption (hereafter referred to as xylem formation onset) of the Northern Hemisphere conifers, recently reported by Huang et al. (2). Their opinions are grounded on the following three aspects, including 1) the seasonality...

02:14 AM

Allosteric cooperation in a de novo-designed two-domain protein [Chemistry] [Early Edition]

We describe the de novo design of an allosterically regulated protein, which comprises two tightly coupled domains. One domain is based on the DF (Due Ferri in Italian or two-iron in English) family of de novo proteins, which have a diiron cofactor that catalyzes a phenol oxidase reaction, while the...

Identification of Z nucleotides as an ancient signal for two-component system activation in bacteria [Microbiology] [Early Edition]

Two-component systems (TCSs) in bacteria are molecular circuits that allow the perception of and response to diverse stimuli. These signaling circuits rely on phosphoryl-group transfers between transmitter and receiver domains of sensor kinase and response regulator proteins, and regulate several cellular processes in response to internal or external cues. Phosphorylation,...

Exopolysaccharide defects cause hyper-thymineless death in Escherichia coli via massive loss of chromosomal DNA and cell lysis [Microbiology] [Early Edition]

Thymineless death in Escherichia coli thyA mutants growing in the absence of thymidine (dT) is preceded by a substantial resistance phase, during which the culture titer remains static, as if the chromosome has to accumulate damage before ultimately failing. Significant chromosomal replication and fragmentation during the resistance phase could provide...

Thursday, 12 November 2020

Thursday, 29 October 2020

Friday, 23 October 2020

Thursday, 15 October 2020

Thursday, 08 October 2020

Thursday, 30 January 2020

03:00 PM

Mitochondrial dysfunctions trigger the calcium signaling-dependent fungal multidrug resistance [Microbiology] [Early Edition]

Drug resistance in fungal pathogens has risen steadily over the past decades due to long-term azole therapy or triazole usage in agriculture. Modification of the drug target protein to prevent drug binding is a major recognized route to induce drug resistance. However, mechanisms for nondrug target-induced resistance remain only loosely...

Feeds

FeedRSSLast fetchedNext fetched after
Annual Reviews: Annual Review of Economics: Table of Contents XML 10:13 AM, Monday, 03 April 2023 01:13 PM, Monday, 03 April 2023
Annual Reviews: Annual Review of Nutrition: Table of Contents XML 10:13 AM, Monday, 03 April 2023 01:13 PM, Monday, 03 April 2023
Annual Reviews: Annual Review of Physiology: Table of Contents XML 10:13 AM, Monday, 03 April 2023 01:13 PM, Monday, 03 April 2023
Annual Reviews: Annual Review of Political Science: Table of Contents XML 10:13 AM, Monday, 03 April 2023 01:13 PM, Monday, 03 April 2023
Annual Reviews: Annual Review of Sociology: Table of Contents XML 10:13 AM, Monday, 03 April 2023 01:13 PM, Monday, 03 April 2023
cs.CR updates on arXiv.org XML 10:13 AM, Monday, 03 April 2023 01:13 PM, Monday, 03 April 2023
Early Edition XML 10:13 AM, Monday, 03 April 2023 01:13 PM, Monday, 03 April 2023
EurekAlert! - Breaking News XML 10:13 AM, Monday, 03 April 2023 01:13 PM, Monday, 03 April 2023
European Political Science Review XML 10:13 AM, Monday, 03 April 2023 01:13 PM, Monday, 03 April 2023
IEEE Transactions on Image Processing - new TOC XML 10:13 AM, Monday, 03 April 2023 01:13 PM, Monday, 03 April 2023
IEEE Transactions on Industrial Electronics - new TOC XML 10:13 AM, Monday, 03 April 2023 01:13 PM, Monday, 03 April 2023
IEEE Transactions on Industrial Informatics - new TOC XML 10:13 AM, Monday, 03 April 2023 01:13 PM, Monday, 03 April 2023
IEEE Transactions on Information Forensics and Security - new TOC XML 10:13 AM, Monday, 03 April 2023 01:13 PM, Monday, 03 April 2023
International Journal of Sports Physiology and Performance XML 10:13 AM, Monday, 03 April 2023 01:13 PM, Monday, 03 April 2023
JAMA Current Issue XML 10:13 AM, Monday, 03 April 2023 01:13 PM, Monday, 03 April 2023
Latest BMJ Research XML 10:13 AM, Monday, 03 April 2023 01:13 PM, Monday, 03 April 2023
Nature XML 10:13 AM, Monday, 03 April 2023 01:13 PM, Monday, 03 April 2023
The Lancet XML 10:13 AM, Monday, 03 April 2023 01:13 PM, Monday, 03 April 2023