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Spacelike Curves of Constant-Ratio in Pseudo-Galilean Space

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arXiv 2022年

作者： Abdel-Aziz, H.S. Saad, M. Khalifa Ali, Haytham A. Dept. of Math. Faculty of Science Sohag Univ. Sohag82524 Egypt Dept. of Math. Faculty of Science Islamic University in Madinah Saudi Arabia

In the theory of differential geometry curves, a curve is said to be of constant-ratio if the ratio of the length of the tangential and normal components of its position vector function is constant. In this paper, we study and characterize a spacelike admissible curve of constant-ratio in terms of its curvature functions in pseudo-Galilean space G13. Some special curves of constant-ratio such as T and N constant types are investigated. As an application of our main results, some examples are *** Codes 53A04, 53A17, 53B30 © 2022, CC BY.

关键词： Vector spaces

An adaptive Particle Swarm Optimization to Solve Modern Security System

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An adaptive Particle Swarm Optimization to Solve Modern Secu...

Innovative Approaches in Smart Technologies (ISAS), International Symposium on

作者： Mohammed H. Ahmed Asaad Noori Hashim Khalid A. Hussein dept. Computer Science College of Education Mustansiriyah University Baghdad Iraq dept. Computer Science College of Computer Science and Math University of Kufa Najaf Iraq

Nonlinear stream ciphers hold a vital position in ensuring confidentiality within contemporary cryptographic systems. In this context, we interduce a new approach known as the Adaptive Three Sub-Swarm PSO based on Regrouping Strategy (ATSPSO-RG) to enhance the effectiveness of deciphering nonlinear stream ciphers, particularly those based on the Bruer generator system. Our method significantly reduces the complexity of cipher-only attacks, making the extraction of the correct secret key more efficient. The proposed system dividing the population size into three distinct subswarm, each incorporating its evolving strategies, namely the single score, four score, and nine score strategies. In the single score strategy, we employed, the traditional PSO evolving process. In the four scores strategy, we used three additional scores in addition to the single score of the traditional PSO to update the velocity and position of particles. lastly, the nine score strategy employed five scores to update the velocity and position, as well as the four scores of the previous score. To counteract the issue of premature convergence, we employ a regrouping strategy that periodically reinitializes the population. Experimental results vividly demonstrate the success of the ATSPSO-RG method in deciphering the Bruer cipher, even when dealing with a varying number of Linear Feedback Shift Registers (LFSRs) and polynomial degrees, spanning up to 15, and secret initial values extending up to 39. The method proves its efficiency in cryptanalysis, offering a potent solution for nonlinear stream ciphers with substantial key sizes while ensuring a reasonable timeframe for analysis. The research outcomes underscore the efficacy of ATSPSO-RG, highlighting both its accuracy and time efficiency in deciphering nonlinear stream ciphers.

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An Innovative Tool for Uploading/Scraping Large Image Datasets on Social Networks

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arXiv 2023年

作者： Arceri, Nicolò Fabio Giudice, Oliver Battiato, Sebastiano Dept. of Math and Computer Science University of Catania Catania Italy

Nowadays, people can retrieve and share digital information in an increasingly easy and fast fashion through the well-known digital platforms, including sensitive data, inappropriate or illegal content, and, in general, information that might serve as probative evidence in court. Consequently, to assess forensics issues, we need to figure out how to trace back to the posting chain of a digital evidence (e.g., a picture, an audio) throughout the involved platforms—this is what Digital (also Forensics) Ballistics basically deals with. With the entry of Machine Learning as a tool of the trade in many research areas, the need for vast amounts of data has been dramatically increasing over the last few years. However, collecting or simply find the "right" datasets that properly enables data-driven research studies can turn out to be not trivial in some cases, if not extremely challenging, especially when it comes with highly specialized tasks, such as creating datasets analyzed to detect the source media platform of a given digital media. In this paper we propose an automated approach by means of a digital tool that we created on purpose. The tool is capable of automatically uploading an entire image dataset to the desired digital platform and then downloading all the uploaded pictures, thus shortening the overall time required to output the final dataset to be analyzed. © 2023, CC BY-NC-SA.

关键词： Digital forensics

A Continuation Method for Fitting a Bandlimited Curve to Points in the Plane

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arXiv 2023年

作者： Zhao, Mohan Serkh, Kirill Dept. of Computer Science University of Toronto TorontoONM5S 2E4 Canada Dept. of Math. and Computer Science University of Toronto TorontoONM5S 2E4 Canada

In this paper, we describe an algorithm for fitting an analytic and bandlimited closed or open curve to interpolate an arbitrary collection of points in R2. The main idea is to smooth the parametrization of the curve by iteratively filtering the Fourier or Chebyshev coefficients of both the derivative of the arc length function and the tangential angle of the curve, and applying smooth perturbations, after each filtering step, until the curve is represented by a reasonably small number of coefficients. The algorithm produces a curve passing through the set of points to an accuracy of machine precision, after a limited number of iterations. It costs O(N log N) operations at each iteration, provided that the number of discretization nodes is N. The resulting curves are smooth and visually appealing, and do not exhibit any ringing artifacts. The bandwidths of the constructed curves are much smaller than those of curves constructed by previous methods. We demonstrate the performance of our algorithm with several numerical *** Codes 65D10, 65D18, 68U05 © 2023, CC BY.

关键词： Interpolation

On the Approximation of Singular Functions by Series of Non-integer Powers

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arXiv 2023年

作者： Zhao, Mohan Serkh, Kirill Dept. of Computer Science University of Toronto TorontoONM5S 2E4 Canada Dept. of Math. and Computer Science University of Toronto TorontoONM5S 2E4 Canada

In this paper, we describe an algorithm for approximating functions of the form f(x) = Rab xµσ(µ) dµ over [0, 1], where σ(µ) is some signed Radon measure, or, more generally, of the form f(x) = 〈σ(µ), xµ〉, where σ(µ) is some distribution supported on [a, b], with 0 c(log x)m = (−1)m〈δ(m)(µ − c), xµ〉, where a ≤ c ≤ b and m ≥ 0 is an integer. Given the desired accuracy ϵ and the values of a and b, our method determines a priori a collection of non-integer powers t1, t2, . . ., tN, so that the functions are approximated by series of the form f(x) ≈ PNj=1 cjxtj, and a set of collocation points x1, x2, . . ., xN, such that the expansion coefficients can be found by collocating the function at these points. We prove that our method has a small uniform approximation error which is proportional to ϵ multiplied by some small constants, and that the number of singular powers and collocation points grows as N = O(log 1ϵ). We demonstrate the performance of our algorithm with several numerical *** Codes 41A30, 41A58, 65D15 © 2023, CC BY.

关键词： Laplace transforms

Key Exchange in the Quantum Era: Evaluating a Hybrid System of Public-Key Cryptography and Physical-Layer Security 59

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Key Exchange in the Quantum Era: Evaluating a Hybrid System ...

59th Annual Conference on Information sciences and Systems, CISS 2025

作者： Staat, Paul Dorpinghaus, Meik Sheikholeslami, Azadeh Paar, Christof Fcllwcis, Gerhard Goeckel, Dennis Max Planck Institute for Security and Privacy Bochum Germany Technische Universität Dresden Vodafone Chair Mobile Communications Systems Dresden Germany Suffolk University Math and Computer Science Department Boston United States University of Massachusetts Dept. Electrical and Computer Engineering Amherst United States

ISBN: (纸本)9798331513269

Today's information society relies on cryptography to achieve security goals such as confidentiality, integrity, authentication, and non-repudiation for digital communications. Here, public-key cryptosystems play a pivotal role to share encryption keys and create digital signatures. However, quantum computers threaten the security of traditional public-key cryptosystems as they can tame computational problems underlying the schemes, i.e., discrete logarithm and integer factorization. The prospective arrival of capable-enough quantum computers already threatens today's secret communication in terms of their long-term secrecy when stored to be later decrypted. Therefore, researchers strive to develop and deploy alternative *** this work, we evaluate a key exchange protocol based on combining public-key schemes with physical-layer security, anticipating the prospect of quantum attacks: If a powerful quantum attacker cannot immediately obtain a private key, legitimate parties have a window of short-term secrecy to perform a physical-layer jamming key exchange (JKE) to establish a long-term shared secret. Thereby, the protocol constraints the computation time available to the attacker to break the employed public-key cryptography. In this paper, we outline the protocol, discuss its security, and point out challenges to be resolved. © 2025 IEEE.

关键词： Quantum computers

Evaluating Low-Resource Lane Following Algorithms for Compute-Constrained Automated Vehicles

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arXiv 2024年

作者： Froemming-Aldanondo, Beñat Rastoskueva, Tatiana Evans, Michael Machado, Marcial Vadella, Anna Johnson, Rickey Escamilla, Luis Jostes, Milan Butani, Devson Kaddis, Ryan Chung, Chan-Jin Siegel, Josh Dept. of Computer Science & Engineering University of Minnesota Minneapolis United States Dept. of Computer Science The University of Arizona Tucson United States Dept. of Computer Science Old Dominion University Norfolk United States Dept. of Computer Science & Engineering The Ohio State University Columbus United States Dept. of Computer Science SWE Butler University Indianapolis United States Dept. of Computer Science North Carolina A&T State University Greensboro United States Dept. of Computer Science New Mexico State University Las Cruces United States Dept. of Math & Computer Science Lawrence Technological University Southfield United States DeepTech Lab Michigan State University East Lansing United States

Reliable lane-following is essential for automated and assisted driving, yet existing solutions often rely on models that require extensive computational resources, limiting their deployment in compute-constrained vehicles. We evaluate five low-resource lane-following algorithms designed for real-time operation on vehicles with limited computing resources. Performance was assessed through simulation and deployment on real drive-by-wire electric vehicles, with evaluation metrics including reliability, comfort, speed, and adaptability. The top-performing methods used unsupervised learning to detect and separate lane lines with processing time under 10 ms per frame, outperforming compute-intensive and poor generalizing deep learning approaches. These approaches demonstrated robustness across lighting conditions, road textures, and lane geometries. The findings highlight the potential for efficient lane detection approaches to enhance the accessibility and reliability of autonomous vehicle technologies. Reducing computing requirements enables lane keeping to be widely deployed in vehicles as part of lower-level automation, including active safety systems. © 2024, CC BY.

关键词： Unsupervised learning

Explaining text classifiers through progressive neighborhood approximation with realistic samples

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arXiv 2023年

作者： Cai, Yi Zimek, Arthur Ntoutsi, Eirini Wunder, Gerhard Dept. of Math. and Comp. Science Freie Universität Berlin Berlin Germany Dept. of Math. and Comp. Science University of Southern Denmark Odense Denmark Research Institute CODE Universität der Bundeswehr München Munich Germany

The importance of neighborhood construction in local explanation methods has been already highlighted in the literature. And several attempts have been made to improve neighborhood quality for high-dimensional data, for example, texts, by adopting generative models. Although the generators produce more realistic samples, the intuitive sampling approaches in the existing solutions leave the latent space underexplored. To overcome this problem, our work, focusing on local model-agnostic explanations for text classifiers, proposes a progressive approximation approach that refines the neighborhood of a to-be-explained decision with a careful two-stage interpolation using counterfactuals as landmarks. We explicitly specify the two properties that should be satisfied by generative models, the reconstruction ability and the locality-preserving property, to guide the selection of generators for local explanation methods. Moreover, noticing the opacity of generative models during the study, we propose another method that implements progressive neighborhood approximation with probability-based editions as an alternative to the generator-based solution. The explanation results from both methods consist of word-level and instance-level explanations benefiting from the realistic neighborhood. Through exhaustive experiments, we qualitatively and quantitatively demonstrate the effectiveness of the two proposed methods. Copyright © 2023, The Authors. All rights reserved.

关键词： Classification (of information)

Revealing Modern Stream Ciphers Security: A Comprehensive Review

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Revealing Modern Stream Ciphers Security: A Comprehensive Re...

Engineering Applied and Nano sciences (ICEANS), International Conference on

作者： Mohammed Albawi Asaad N. Hashim Khalid A. Hussein Dept. Computer Science College of Education Technical Mustansiriyah University Baghdad Iraq Dept. Computer Science College of Computer Science and Math University of Kufa Najaf Iraq Dept. Computer Science College of Education Mustansiriyah University Baghdad Iraq

ISBN: (数字)9798350341973

ISBN: (纸本)9798350341980

Stream ciphers are essential cryptographic primitives widely employed in various applications for efficient data protection. This paper presents a comprehensive review of attacks on the Grain, Trivium, and SNOW stream ciphers, which are considered prominent in modern cryptography. Through an extensive analysis of existing research and publications, this work systematically categorizes and evaluates known attacks, shedding light on the vulnerabilities and weaknesses exhibited by these ciphers. By examining a diverse range of attack techniques, including algebraic, statistical, and differential attacks, this work provides insights into the security landscape of Grain, Trivium, and SNOW. Furthermore, it conducts a comparative analysis of the findings across the three ciphers, identifying common patterns and vulnerabilities. The outcomes of our study have profound implications for the practical deployment and usage of these stream ciphers, emphasizing the ongoing need for research and the development of robust countermeasures. By gaining a comprehensive understanding of the weaknesses exposed by these attacks, cryptographic practitioners can make informed decisions concerning the implementation and security of these stream ciphers.

关键词： Performance evaluation Ciphers Correlation Reviews Snow Data protection Object recognition