Security analysis and enhancements of an improved multi-factor biometric authentication scheme

Many remote user authentication schemes have been designed and developed to establish secure and authorized communication between a user and server over an insecure channel. By employing a secure remote user authentication scheme, a user and server can authenticate each other and utilize advanced services. In 2015, Cao and Ge demonstrated that An's scheme is also vulnerable to several attacks and does not provide user anonymity. They also proposed an improved multi-factor biometric authentication scheme. However, we review and cryptanalyze Cao and Ge's scheme and demonstrate that their scheme fails in correctness and providing user anonymity and is vulnerable to ID guessing attack and server masquerading attack. To overcome these drawbacks, we propose a security-improved authentication scheme that provides a dynamic ID mechanism and better security functionalities. Then, we show that our proposed scheme is secure against various attacks and prove the security of the proposed scheme using BAN Logic.111Ysciescopu

From Values to Opinions: Predicting Human Behaviors and Stances Using Value-Injected Large Language Models

Being able to predict people's opinions on issues and behaviors in realistic scenarios can be helpful in various domains, such as politics and marketing. However, conducting large-scale surveys like the European Social Survey to solicit people's opinions on individual issues can incur prohibitive costs. Leveraging prior research showing influence of core human values on individual decisions and actions, we propose to use value-injected large language models (LLM) to predict opinions and behaviors. To this end, we present Value Injection Method (VIM), a collection of two methods -- argument generation and question answering -- designed to inject targeted value distributions into LLMs via fine-tuning. We then conduct a series of experiments on four tasks to test the effectiveness of VIM and the possibility of using value-injected LLMs to predict opinions and behaviors of people. We find that LLMs value-injected with variations of VIM substantially outperform the baselines. Also, the results suggest that opinions and behaviors can be better predicted using value-injected LLMs than the baseline approaches.Comment: EMNLP 2023 main paper accepte

NeBLa: Neural Beer-Lambert for 3D Reconstruction of Oral Structures from Panoramic Radiographs

Panoramic radiography (panoramic X-ray, PX) is a widely used imaging modality for dental examination. However, its applicability is limited as compared to 3D Cone-beam computed tomography (CBCT), because PX only provides 2D flattened images of the oral structure. In this paper, we propose a new framework which estimates 3D oral structure from real-world PX images. Since there are not many matching PX and CBCT data, we used simulated PX from CBCT for training, however, we used real-world panoramic radiographs at the inference time. We propose a new ray-sampling method to make simulated panoramic radiographs inspired by the principle of panoramic radiography along with the rendering function derived from the Beer-Lambert law. Our model consists of three parts: translation module, generation module, and refinement module. The translation module changes the real-world panoramic radiograph to the simulated training image style. The generation module makes the 3D structure from the input image without any prior information such as a dental arch. Our ray-based generation approach makes it possible to reverse the process of generating PX from oral structure in order to reconstruct CBCT data. Lastly, the refinement module enhances the quality of the 3D output. Results show that our approach works better for simulated and real-world images compared to other state-of-the-art methods.Comment: 10 pages, 4 figure

Correlation between low skeletal muscle index and 3D anthropometric data measured by 3D body scanner: screening sarcopenia

BackgroundThe screening tools for sarcopenia are measuring calf circumference, SARC-F or SPPB. However, not all of these tools have high sensitivity, specificity, and low margins of error. This research investigates potential of 3D anthropometry of the lower extremities on screening of sarcopenia.MethodsFrom October 2022 to February 2023, we retrospectively analyzed results of 3D body scanner and bio-impedance analysis for patients aged 45 to 85 at risk of sarcopenia. The 3D scanner measured the surface and volume values of both thighs and calves. When skeletal muscle index (SMI) is less than 5.7, patients were classified to Low SMI group, indicative of sarcopenia.ResultsA total six out of 62 patients were classified to Low SMI group, showing significantly lower values of right, left, mean calf volumes and mean calf surface than the other patients (right calf volume 2.62 L vs. 3.34 L, p = 0.033; left calf volume 2.62 L vs. 3.25 L, p = 0.044; mean calf volume 2.62 L vs. 3.29 L, p = 0.029; mean calf surface 0.12 m2 vs. 0.13 m2, p = 0.049). There was no statistical difference in thigh volume and surface. Through AUC-ROC analysis, mean calf volume was the most significant cut-off value (right calf volume 2.80 L, AUC = 0.768; left calf volume 2.75 L, AUC = 0.753; mean calf volume 3.06 L, AUC = 0.774; mean calf surface 0.12 m2, AUC = 0.747).ConclusionThe calf volume and surface values have significant relationship with low SMI, and the mean calf volume was the most significant cut-off screening value for Low SMI. The 3D scanner demonstrated its value as a new means for screening sarcopenia

Security and Privacy for Modern Wireless Communication Systems

The aim of this reprint focuses on the latest protocol research, software/hardware development and implementation, and system architecture design in addressing emerging security and privacy issues for modern wireless communication networks. Relevant topics include, but are not limited to, the following: deep-learning-based security and privacy design; covert communications; information-theoretical foundations for advanced security and privacy techniques; lightweight cryptography for power constrained networks; physical layer key generation; prototypes and testbeds for security and privacy solutions; encryption and decryption algorithm for low-latency constrained networks; security protocols for modern wireless communication networks; network intrusion detection; physical layer design with security consideration; anonymity in data transmission; vulnerabilities in security and privacy in modern wireless communication networks; challenges of security and privacy in node–edge–cloud computation; security and privacy design for low-power wide-area IoT networks; security and privacy design for vehicle networks; security and privacy design for underwater communications networks

Low-Surface-Brightness Galaxies are missing in the observed Stellar Mass Function

We investigate the impact of the surface brightness (SB) limit on the galaxy stellar mass functions (GSMFs) using mock surveys generated from the Horizon Run 5 (HR5) simulation. We compare the stellar-to-halo-mass relation, GSMF, and size-stellar mass relation of the HR5 galaxies with empirical data and other cosmological simulations. The mean SB of simulated galaxies are computed using their effective radii, luminosities, and colors. To examine the cosmic SB dimming effect, we compute $k$-corrections from the spectral energy distributions of individual simulated galaxy at each redshift, apply the $k$-corrections to the galaxies, and conduct mock surveys based on the various SB limits. We find that the GSMFs are significantly affected by the SB limits at a low-mass end. This approach can ease the discrepancy between the GSMFs obtained from simulations and observations at $0.625\le z\le 2$. We also find that a redshift survey with a SB selection limit of \left^e = 28 mag arcsec${}^{-2}$ will miss 20% of galaxies with $M_\star^g=10^{9}~{\rm M_\odot}$ at $z=0.625$. The missing fraction of low-surface-brightness galaxies increases to 50%, 70%, and 98% at $z=0.9$, 1.1, and 1.9, respectively, at the SB limit.Comment: 27 pages, 30 figures, accepted for publication in Ap

Identification of Galaxy Protoclusters Based on the Spherical Top-hat Collapse Theory

We propose a new method for finding galaxy protoclusters that is motivated by structure formation theory and also directly applicable to observations. We adopt the conventional definition that a protocluster is a galaxy group whose virial mass $M_{\rm vir} < M_{\rm cl}$ at its epoch, where $M_{\rm cl}=10^{14}\,M_{\odot}$, but would exceed that limit when it evolves to $z=0$. We use the critical overdensity for complete collapse at $z = 0$ predicted by the spherical top-hat collapse model to find the radius and total mass of the regions that would collapse at $z=0$. If the mass of a region centered at a massive galaxy exceeds $M_{\rm cl}$, the galaxy is at the center of a protocluster. We define the outer boundary of protocluster as the zero-velocity surface at the turnaround radius so that the member galaxies are those sharing the same protocluster environment and showing some conformity in physical properties. We use the cosmological hydrodynamical simulation Horizon Run 5 (HR5) to calibrate this prescription and demonstrate its performance. We find that the protocluster identification method suggested in this study is quite successful. Its application to the high-redshift HR5 galaxies shows a tight correlation between the mass within the protocluster regions identified according to the spherical collapse model and the final mass to be found within the clusters at $z=0$, meaning that the regions can be regarded as the bona fide protoclusters with high reliability. We also confirm that the redshift-space distortion does not significantly affect the performance of the protocluster identification scheme.Comment: 23 pages, 21 figures. Accepted for publication in Ap