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Evaluating the Impact of Special Characters on Password Security: a Comparative Analysis

IEEE Network 2025年

作者： He, Daojing Liu, Zhiyong Chan, Sammy Zhou, Beibei Guizani, Mohsen Harbin Institute of Technology School of Computer Science and Technology Shenzhen China Guizhou University State Key Laboratory of Public Big Data Guizhou China Research and Development Center Guangzhou Jingyuan Security Technology Co. Ltd Guangzhou China City University of Hong Kong Kowloon Department of Electrical Engineering Hong Kong Hong Kong Shanghai Urban Construction Vocational College School of Artificial Intelligence Application Shanghai China Machine Learning Department Abu Dhabi United Arab Emirates

Text-based password authentication remains essential for identity verification on internet platforms and blockchain systems. However, as computational power advances, security threats to user passwords have intensified, raising concerns about their effectiveness. While special characters (i.e., non-alphanumeric symbols, which include punctuation marks, mathematical symbols, and other non-letter/number characters like '.', '@', '#', '$', and similar) are often recommended to enhance password strength, the National Institute of Standards and Technology (NIST) prioritizes length over complexity, challenging their necessity. This study fills a critical gap in understanding user behavior regarding special character usage. By analyzing 15 datasets from Chinese, English, and German languages, we examined patterns of special character incorporation and their impact on password strength. Our findings indicate that users frequently employ predictable methods for including special characters, potentially compromising security, especially under stringent policies. We present three key contributions: (1) an analysis of special character usage patterns, (2) a quantitative assessment of strength differences using the PCFGv4.1 model, and (3) actionable recommendations for stakeholders to enhance password security practices. This research further advocates for aligning password policies with user behavior for more effective security. © 1986-2012 IEEE.

关键词： Authentication Protocol

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Modern extreme value statistics for Utopian extremes

arXiv

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arXiv 2023年

作者： Richards, Jordan Alotaibi, Noura Cisneros, Daniela Gong, Yan Guerrero, Matheus B. Redondo, Paolo Shao, Xuanjie School of Mathematics University of Edinburgh United Kingdom Statistics Program Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal Saudi Arabia Harvard School of Public Health BostonMA United States Department of Mathematics California State University FullertonCA United States

Capturing the extremal behaviour of data often requires bespoke marginal and dependence models which are grounded in rigorous asymptotic theory, and hence provide reliable extrapolation into the upper tails of the data-generating distribution. We present a toolbox of four methodological frameworks, motivated by modern extreme value theory, that can be used to accurately estimate extreme exceedance probabilities or the corresponding level in either a univariate or multivariate setting. Our frameworks were used to facilitate the winning contribution of Team Yalla to the EVA (2023) Conference Data Challenge, which was organised for the 13th International Conference on Extreme Value Analysis. This competition comprised seven teams competing across four separate sub-challenges, with each requiring the modelling of data simulated from known, yet highly complex, statistical distributions, and extrapolation far beyond the range of the available samples in order to predict probabilities of extreme events. Data were constructed to be representative of real environmental data, sampled from the fantasy country of "Utopia". © 2023, CC BY.

关键词： Extrapolation

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Adolescent Asthma Monitoring: A Preliminary Study of Audio and Spirometry Modalities

Adolescent Asthma Monitoring: A Preliminary Study of Audio a...

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Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： Jeffrey A. Barahona Katie Mills Michelle Hernandez Alper Bozkurt Delesha Carpenter Edgar J. Lobaton Department of Electrical and Computer Engineering North Carolina State University Raleigh NC USA Children’s Research Institute University of North Carolina at Chapel Hill Chapel Hill NC USA Division of Pharmaceutical Outcomes and Policy Eshelman School of Pharmacy University of North Carolina at Chapel Hill Chapel Hill NC USA

Asthma patients’ sleep quality is correlated with how well their asthma symptoms are controlled. In this paper, deep learning techniques are explored to improve forecasting of forced expiratory volume in one second (FEV1) by using audio data from participants and test whether auditory sleep disturbances are correlated with poorer asthma outcomes. These are applied to a representative data set of FEV1 collected from a commercially available sprirometer and audio spectrograms collected overnight using a smartphone. A model for detecting nonverbal vocalizations including coughs, sneezes, sighs, snoring, throat clearing, sniffs, and breathing sounds was trained and used to capture nightly sleep disturbances. Our preliminary analysis found significant improvement in FEV1 forecasting when using overnight nonverbal vocalization detections as an additional feature for regression using XGBoost over using only spirometry *** relevance— This preliminary study establishes up to 30% improvement of FEV1 forecasting using features generated by deep learning techniques over only spirometry-based features.

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A Comparison of Point Cloud Registration Techniques for on-site Disaster Data from the Surfside Structural Collapse

A Comparison of Point Cloud Registration Techniques for on-s...

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IEEE International Workshop on Safety, Security, and Rescue Robotics (SSRR)

作者： Ananya Ball Robert Ladig Pranav Goyal John Galeotti Howie Choset David Merrick Robin Murphy The Robotics Institute Carnegie Mellon University Pittsburgh PA USA The Department of Science and Engineering Ritsumeikan University Kusatsu Japan The Birla Institute of Technology & Science - Pilani Goa India The College of Social Science and Public Policy Florida State University USA Raytheon Professor of Computer Science and Engineering Texas A&M University USA

ISBN: (纸本)9781665456814

3D representations of geographical surfaces in the form of dense point clouds can be a valuable tool for documenting and reconstructing a structural collapse, such as the 2021 Champlain Towers Condominium collapse in Surfside, Florida. Point cloud data reconstructed from aerial footage taken by uncrewed aerial systems at frequent intervals from a dynamic search and rescue scene poses significant challenges. Properly aligning large point clouds in this context, or registering them, poses noteworthy issues as they capture multiple regions whose geometries change over time. These regions denote dynamic features such as excavation machinery, cones marking boundaries and the structural collapse rubble itself. In this paper, the performances of commonly used point cloud registration methods for dynamic scenes present in the raw data are studied. The use of Iterative Closest Point (ICP), Rigid - Coherent Point Drift (CPD) and PointNetLK for registering dense point clouds, reconstructed sequentially over a time-frame of five days, is studied and evaluated. All methods are compared by error in performance, execution time, and robustness with a concluding analysis and a judgement of the preeminent method for the specific data at hand is provided.

关键词： Point cloud compression Surface reconstruction Three-dimensional displays Poles and towers Robustness Safety Registers

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The potential for electrifying industrial utility systems in existing chemical plants

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Applied Energy 2025年 392卷

作者： Bielefeld, Svenja Cvetković, Miloš Ramírez, Andrea Engineering Systems and Services Department Faculty of Technology Policy and Management Delft University of Technology Delft Netherlands Electrical Sustainable Energy Department Faculty of Electrical Engineering Mathematics & Computer Science Delft University of Technology Delft Netherlands Department of Chemical Engineering Faculty of Applied Science Delft University of Technology Delft Netherlands

The electrification of utility systems in energy-intensive plants is a promising measure for decarbonising the chemical industry in the short term. However, with the increasing deployment of renewable energy sources, the variability of electricity prices will become a challenge for plants with continuous and constant energy demand. It is thus uncertain whether electrification can become financially viable. This work models the electrification of utility systems in combination with storage technologies for five chemical plants with existing fossil fuel-based utility generation and uses historical data as energy price scenarios. The results show that partial electrification is cost-effective when using electricity is cheaper than natural gas for more than 600 h. Regarding the portfolio of technologies, electric boilers are installed first, followed by thermal energy storage and batteries. Hydrogen is not cost-effective in any of the scenarios explored. This is independent of the type of plant, the available grid connection capacity, and the minimal load of existing fossil fuel-based utility generation. This work thus highlights the potential for electrifying industrial utility systems and the role that electric boilers and energy storage units can play in electrification. © 2025 The Author(s)

关键词： Chemical plants

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The Bankable Economic Potential of Utility-Scale Solar Pv: A Novel Gis-Based Framework with Application to Indonesia

SSRN

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SSRN 2023年

作者： Langer, Jannis Ashqar, Ziad Zhou, Yilong Isabella, Olindo Praktiknjo, Aaron Quist, Jaco Kwee, Zenlin Blok, Kornelis Delft University of Technology Faculty of Technology Policy and Management Department of Engineering Systems and Services Jaffalaan 5 Delft2628 BX Netherlands Delft University of Technology Faculty of Electrical Engineering Mathematics and Computer Science Department of Electrical Sustainable Energy Photovoltaic Materials and Devices group Mekelweg 4 Delft2628 CD Netherlands RWTH Aachen University Energy System Economics Institute for Future Energy Consumer Needs and Behavior E.ON Energy Research Center Mathieustraße 10 Aachen52074 Germany Delft University of Technology Faculty of Technology Policy and Management Department of Values Technology and Innovation Jaffalaan 5 Delft2628 BX Netherlands

Geospatial analysis is useful to calculate and map solar photovoltaic’s (PV) economic potential. However, recent studies do not address PV’s bankable potential for practical implementation and show limitations in (1) potential and input reporting, (2) studied metrics, (3) uncertainty analysis, and (4) policy analysis. To tackle these limitations, we propose a novel framework for utility-scale PV’s bankable potential, which combines geospatial analysis and project finance. The framework involves 20 years of hourly solar electricity production, a debt sizing and cash flow analysis model, and Monte Carlo simulation. We report a conservative technical potential of 9.3 TWpeak and 12.1 PWh/year in Indonesia. Considering expected 2030 demand, PV’s bankable potential is up to 40.8 TWh/year mostly situated in East Indonesia where population and demand are low. PV’s bankability is currently limited by strict loan maturities and low electricity tariffs, and could be improved to up to 232 TWh/year (52% of 2030 demand) via a feed-in tariff of 11.5 US¢(2021)/kWh and a temporary lift of local content for solar panels. Despite their effectiveness, policymakers should be aware of possible side effects of PV policies, e.g. for local coal-based industries and rural communities with limited electricity access. © 2023, The Authors. All rights reserved.

关键词： Economic analysis

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Allocation of Emission Allowances Considering Strategic Voting

SSRN

引用

SSRN 2022年

作者： Mei, Tianhua Liu, Jie Guo, Jianming Siano, Pierluigi Jin, Xuanxuan School of Electrical Engineering Zhejiang University Zhejiang Hangzhou310027 China School of Public Administration Zhejiang University of Finance and Economics Zhejiang Hangzhou310018 China China Research Institute of Regulation and Public Policy Zhejiang Hangzhou310018 China Department of Management & Innovation Systems University of Salerno Salerno Italy Department of Electrical and Electronic Engineering Science University of Johannesburg Johannesburg2006 South Africa China Institute of Regulation Research Zhejiang University of Finance and Economics Zhejiang Hangzhou310018 China

The initial allocation of carbon emission rights among different generating units is an important element in the initial stage of the construction of the carbon emission market for the power system, and is also the focus of attention in the construction of the current carbon market for the power system in *** practical situations, a variety of equity principles have been utilized in different allocation problems. However, conflicts always exist among these principles. It is necessary to justify and coordinate different allocation *** paper tries to apply the axiomatic method and social choice theory to propose an axiomatic and fair allocation method based on iterative election and establish a mathematical model for the fair allocation of initial carbon emission rights in power systems. This paper studies the game equilibrium problem under the iterative election allocation mechanism, and describes the finite rationality of participants in a complex environment by means of the "local optimal search" and "greedy algorithm".By introducing the method of strict intention table, the general equilibrium under specific conditions and the game equilibrium problem below four strategies are solved analytically in detail. Finally, some real-world case studies are carried out to show that the iterative election allocation algorithm can satisfy the main principle of fair allocation and the given allocation results are easily accepted by each unit *** study not only provides a reasonable and feasible path for China's power system to realize the scientific research on the fair distribution of initial carbon emissions and the practicability of distribution methods, but also provides profound policy enlightenment for the construction of carbon emission market in China's power industry. © 2022, The Authors. All rights reserved.

关键词： Game theory

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Label-Free Detection of Respiratory Virus Co-Infections: Integrating Surface-Enhanced Raman Scattering with Deep Learning

Label-Free Detection of Respiratory Virus Co-Infections: Int...

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Photonic Diagnosis, Monitoring, Prevention, and Treatment of Infections and Inflammatory Diseases 2025

作者： Yang, Yanjun Cui, Jiaheng Kumar, Amit Luo, Dan Murray, Jackelyn Jones, Les Chen, Xianyan Hülck, Sebastian Tripp, Ralph A. Zhao, Yiping Department of Physics and Astronomy Franklin College of Arts and Sciences The University of Georgia AthensGA30602 United States School of Electrical and Computer Engineering College of Engineering The University of Georgia AthensGA30602 United States Department of Statistics Franklin College of Arts and Sciences The University of Georgia AthensGA30602 United States Department of Infectious Diseases College of Veterinary Medicine The University of Georgia AthensGA30602 United States Department of Epidemiology & Biostatistics College of Public Health The University of Georgia AthensGA30602 United States Tec5USA Inc. PlainviewNY11803 United States

ISBN: (纸本)9781510683440

Concurrent or sequential infections by multiple respiratory viruses pose significant challenges for diagnosis, treatment, and disease management, necessitating accurate and rapid identification methods. Here, we introduce a label-free diagnostic platform that combines surface-enhanced Raman scattering (SERS) with deep learning to enable rapid, quantitative detection of respiratory virus co-infections. Utilizing highly sensitive silica-coated silver nanorod array substrates, we collected over 1.2 million SERS spectra from 11 viruses, nine two-virus mixtures, and four three-virus mixtures at varying concentrations in saliva. A novel deep learning model, MultiplexCR, was developed to simultaneously identify virus species and quantify their concentrations from the SERS spectra. The model achieved an exceptional classification accuracy of 98.6% for virus co-infections and a mean absolute error of 0.028 for concentration regression. In blind testing, MultiplexCR consistently demonstrated high accuracy and precise concentration predictions. This SERS-MultiplexCR platform performs the entire detection process within 15 minutes, highlighting its potential for rapid, point-of-care diagnostics in infection detection, as well as broader applications in food safety and environmental monitoring. © 2025 SPIE.

关键词： Nanorods

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Granular Compensation, Information, and Carbon Pricing Promote DER Deployment

arXiv

引用

arXiv 2022年

作者： Khan, Hafiz Anwar Ullah Ünel, Burçin Dvorkin, Yury Department of Electrical and Computer Engineering NYU Tandon School of Engineering New York University NY United States Institute for Policy Integrity NYU School of Law New York University NY United States Ralph O’Connor Sustainable Energy Institute Johns Hopkins University BaltimoreMD United States

The socially efficient deployment of Distributed Energy Resources (DERs), e.g., rooftop solar, depends on the underlying retail electricity policies. Current debates on DER policies, including Net Energy Metering (NEM) variants, center around developing value-reflective compensation policies that can expedite DER deployment while preventing potential cost shifts between DER adopters and non-adopters. However, these debates mostly ignore the temporally- and spatially- granular value of DERs, market failures (e.g., information asymmetry among DER stakeholders) and externalities (e.g., carbon-dioxide emissions). In this paper, we develop a game-theoretic approach with information asymmetry to examine efficiency implications of adopting granular DER compensation policies, e.g., value stacks and distributional locational marginal price, instead of NEM with flat retail rates. We show that granular compensation policies result in more efficient market outcomes than under NEM, even in the presence of information asymmetry, thus avoiding the need for interventions. Combined with granular DER compensation, carbon pricing provides the most accurate price signal to DER investors/aggregators, and leads to the highest social welfare. © 2022, CC BY.

关键词： Costs

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Invariant neuromorphic representations of tactile stimuli improve robustness of a real-time texture classification system

arXiv

引用

arXiv 2024年

作者： Iskarous, Mark M. Chaudhry, Zan Li, Fangjie Bello, Samuel Sankar, Sriramana Slepyan, Ariel Chugh, Natasha Hunt, Christopher L. Greene, Rebecca J. Thakor, Nitish V. Department of Biomedical Engineering Johns Hopkins School of Medicine BaltimoreMD21205 United States Department of Organismal Biology and Anatomy University of Chicago ChicagoIL60637 United States National Heart Lung and Blood Institute National Institutes of Health BethesdaMD20814 United States Department of Biomedical Engineering Vanderbilt University NashvilleTN37325 United States Department of Electrical and Computer Engineering Johns Hopkins University BaltimoreMD21218 United States Department of Public Health Johns Hopkins University BaltimoreMD21218 United States Texas College of Osteopathic Medicine The University of North Texas Health Science Center Fort WorthTX76107 United States Infinite Biomedical Technologies LLC. BaltimoreMD21202 United States

Humans have an exquisite sense of touch which robotic and prosthetic systems aim to recreate. We developed algorithms to create neuron-like (neuromorphic) spiking representations of texture that are invariant to the scanning speed and contact force applied in the sensing process. The spiking representations are based on mimicking activity from mechanoreceptors in human skin and further processing up to the brain. The neuromorphic encoding process transforms analog sensor readings into speed and force invariant spiking representations in three sequential stages: the force invariance module (in the analog domain), the spiking activity encoding module (transforms from analog to spiking domain), and the speed invariance module (in the spiking domain). The algorithms were tested on a tactile texture dataset collected in 15 speed-force conditions. An offline texture classification system built on the invariant representations has higher classification accuracy, improved computational efficiency, and increased capability to identify textures explored in novel speed-force conditions. The speed invariance algorithm was adapted to a real-time human-operated texture classification system. Similarly, the invariant representations improved classification accuracy, computational efficiency, and capability to identify textures explored in novel conditions. The invariant representation is even more crucial in this context due to human imprecision which seems to the classification system as a novel condition. These results demonstrate that invariant neuromorphic representations enable better performing neurorobotic tactile sensing systems. Furthermore, because the neuromorphic representations are based on biological processing, this work can be used in the future as the basis for naturalistic sensory feedback for upper limb amputees. © 2024, CC BY-NC-ND.

关键词： Sensory feedback

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