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Dishonest Majority Constant-Round MPC with Linear Communication from DDH 30th

Dishonest Majority Constant-Round MPC with Linear Communicat...

引用

30th International Conference on the Theory and Application of Cryptology and Information Security

作者： Goyal, Vipul Li, Junru Misra, Ankit Kumar Ostrovsky, Rafail Song, Yifan Weng, Chenkai NTT Res Sunnyvale CA 94085 USA Carnegie Mellon Univ Pittsburgh PA 15213 USA Tsinghua Univ Beijing Peoples R China UCLA Los Angeles CA USA Shanghai Qi Zhi Inst Shanghai Peoples R China Arizona State Univ Tempe AZ USA

ISBN: (纸本)9789819609376;9789819609383

In this work, we study constant round multiparty computation (MPC) for Boolean circuits against a fully malicious adversary who may control up to n - 1 out of n parties. Without relying on fully homomorphic encryption (FHE), the best-known results in this setting are achieved by Wang et al. (CCS 2017) and Hazay et al. (ASIACRYPT 2017) based on garbled circuits, which require a quadratic communication in the number of parties O(vertical bar C vertical bar . n(2)). In contrast, for non-constant round MPC, the recent result by Rachuri and Scholl (CRYPTO 2022) has achieved linear communication O(vertical bar C vertical bar . n). In this work, we present the first concretely efficient constant round MPC protocol in this setting with linear communication in the number of parties O(vertical bar C vertical bar . n). Our construction can be based on any publickey encryption scheme that is linearly homomorphic for public keys. Our work gives a concrete instantiation from a variant of the El-Gamal Encryption Scheme assuming the DDH assumption. The analysis shows that when the computational security parameter lambda = 128 and statistical security parameter kappa = 80, our protocol achieves a smaller communication than Wang et al. (CCS 2017) when there are 16 parties for AES circuit and 8 parties for general Boolean circuits (where we assume that the numbers of AND gates and XOR gates are the same). When comparing with the recent work by Beck et al. (CCS 2023) that achieves constant communication complexity O(vertical bar C vertical bar) in the strong honest majority setting (t < (1/2 - epsilon)n where epsilon is a constant), our protocol is better as long as n < 3500 (when t = n/4 for their work).

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Early Results of an AI Multiagent System for Requirements Elicitation and Analysis 25th

Early Results of an AI Multiagent System for Requirements El...

引用

25th International Conference on Product Focused Software Process Improvement

作者： Sami, Malik Abdul Waseem, Muhammad Zhang, Zheying Rasheed, Zeeshan Systa, Kari Abrahamsson, Pekka Tampere Univ Tampere Finland Univ Jyvaskyla Jyvaskyla Finland

ISBN: (纸本)9783031783852;9783031783869

In agile software development, user stories capture requirements from the user's perspective, emphasizing their needs and each feature's value. Writing concise and quality user stories is necessary for guiding software development. Alongside user story generation, prioritizing these requirements ensures that the most important features are developed first, maximizing project value. This study explores the use of Large Language Models (LLMs) to automate the process of user story generation, quality assessment, and prioritization. We implemented a multi-agent system using Generative Pre-trained Transformers (GPT), specifically GPT-3.5 and GPT-4o, to generate and prioritize user stories from the initial project description. Our experiments on a real-world project demonstrate that GPT-3.5 handled user story generation well, achieving a higher semantic similarity score comnpared to the GPT4o. Both models showed consistent performance in prioritizing requirements, effectively identifying the core features of the application. These early results indicate that LLMs have significant potential for automating requirements analysis, particularly generating and prioritizing user stories.

关键词： Software Engineering Requirements Engineering Requirements prioritization Generative AI Large language model(s)

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A Model-Based Design Approach for a System of Systems Based on an Integrated UAV Platform 10th

A Model-Based Design Approach for a System of Systems Based ...

引用

10th International Conference on Modelling and Simulation for Autonomous Systems

作者： Morlacchi, Giovanni Cicalini, Marco Testa, Amedeo Pagliani, Filippo Frisini, David TXT E Tech I-20093 Cologno Monzese Italy

ISBN: (纸本)9783031713965;9783031713972

Considering the trend seen in recent years regarding drones and their applications in the near future, it becomes clear that more and more systems will be created to support the use of UAVs. This paper presents the integrated Model-Based design approach employed for the development of DIVE (Drone Integration and Validation Ecosystem): a System of Systems (SoS) designed as a functionalities-based architecture. This design technique has been chosen to reduce the time to market new systems since it allows to lower the number of iterations during development, hence facilitating the development and integration of new UAV systems. Currently, DIVE comprises four main areas: Mission Planning, Validation, Operations, and Safety. SkyMission, ARMONIS (Aircraft and Remote MONitored Integrated System), and ELITE (Emergency Landing Identification and Termination System) are the systems that cover these modules. DIVE and the systems it comprises are tested in a digitalized world, exploiting the concept of digital twins, and Wire, the framework that connects them. SkyMission is a simulation environment, created to study and test mission scenarios with UAVs. ARMONIS is a versatile platform meant to permit direct teaming between aircraft personnel, unmanned vehicles, and ground operators. ELITE is a system for UAVs that, unlike a common FTS, employs state-of-the-art Machine Learning and computer Vision technologies to determine the best termination area on the terrain. The underlying backbone that connects all those modules is Wire, a distributed communication framework that can exchange data between them in a decoupled and efficient way. The first tests for these applications with the digital twin have shown promising results. Leveraging different systems, DIVE will be a reliable and scalable system of systems developed using a Model-Based approach, for the integration of UAV-based applications, establishing a novel functionalities-based ecosystem.

关键词： Drones System of Systems Model-Based Design Approach Digital Twin System Integration

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Analysis of Kinematics and Dynamics for Mobile Robots Under Nonholonomic Constraints 10th

Analysis of Kinematics and Dynamics for Mobile Robots Under ...

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29th International Conference on Database Systems for Advanced Applications (DASFAA)

作者： Shao, Yongcun Suzhou City Univ Suzhou 215000 Jiangsu Peoples R China

ISBN: (纸本)9789819609130;9789819609147

With the widespread application of mobile robots in industries, services, and exploration, their capabilities in motion planning and obstacle avoidance have become a focal point of research. Nonholonomic constraints, especially those of wheeled mobile robots, significantly impact the motion planning of robots. This paper focuses on the nonholonomic characteristics of Differential Wheeled Robots (DWRs), establishes their kinematic and dynamic models, and analyzes the influence of these constraints on robot motion planning. By introducing the Lagrange multiplier method, nonholonomic constraints are incorporated into the dynamic equations, and the unknown multipliers are eliminated through transformation, resulting in the dynamic equations for DWRs. Moreover, the paper analyzes the controllability of the system using the Chow-Rashevskii theorem, proving that the DWR system is locally controllable in the short term.

关键词： Nonholonomic Constraints Differential Wheeled Robots Kinematic Model Dynamic Model Controllability Analysis

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A Gamified Learning Approach for IoT Security Education Using Capture-the-Flag Competitions: Architecture and Insights 29th

A Gamified Learning Approach for IoT Security Education Usin...

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29th Nordic Conference on Secure IT Systems

作者： Hamad, Mohammad Finkenzeller, Andreas Hasan, Monowar Pahl, Marc-Oliver Steinhorst, Sebastian Tech Univ Munich Munich Germany Washington State Univ Washington DC USA IMT Atlantique Rennes France

ISBN: (纸本)9783031790065;9783031790072

Cybersecurity is one of the most critical issues for Internet of Things (IoT) systems today and in the future. Therefore, it is essential to educate students about cybersecurity and provide them with the skills needed to design and protect secure IoT systems. We share the experience we gained using a gamified learning approach to IoT security by integrating Capture the Flag (CTF) competitions into our university course. During the semester, students form teams and compete against each other in hacking various educational systems designed in a practically relevant way on our CTF platform. In our paper, we introduce the architecture of the CTF platform and provide student feedback on its effectiveness in teaching IoT security. The evaluation reflects student feedback over three semesters. We also share our lessons learned from creating and maintaining the CTF platform and discuss ideas on how to improve it further. Overall, the students engaged extensively in the CTF, had positive experiences with the provided platform and challenges, and were highly satisfied with our teaching approach. Based on the positive feedback, we believe our approach is an effective way to educate students in IoT security, and we encourage others to adopt this method.

关键词： Active Learning Security Capture the Flag Internet-of-Things

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Color Enhanced Network for Image Dehazing 7th

Color Enhanced Network for Image Dehazing

引用

7th Chinese Conference on Pattern Recognition and computer Vision

作者： Nie, Yongsha Anhui Univ Anhui Prov Int Joint Res Ctr Adv Technol Med Imag Sch Comp Sci & Technol Hefei 230601 Peoples R China

ISBN: (纸本)9789819786848;9789819786855

Image dehazing is an important and challenging task in image processing. Existing dehazing methods often encounter color distortion in the dehazed results. To address this issue, in this paper, we propose a novel approach named Color Enhanced Dehazing network (CED). It consists of two main branches: a dehazing branch and a color reconstruction branch. Initially, we employ Fast Fourier Transform to separate the low-frequency sub-image from the hazy image, which contains substantial color information. Alongside inputting the original hazy image into the dehazing branch, we concurrently feed the low-frequency sub-image into the color reconstruction branch. This allows us to extract and reconstruct corresponding color information to augment the dehazing process. To thoroughly fuse the information from two branches, we design a Selective Spatial-Channel adjustment fusion module (SSC) for the feature fusion across different branches. Extensive experiments on benchmark datasets well demonstrate the effectiveness and superiority of the proposed method in the image dehazing.

关键词： Image dehazing Low-frequency Selective spatial-channel adjustment

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MEM: Mask Enhancement Model for Video Object Segmentation 19th

MEM: Mask Enhancement Model for Video Object Segmentation

引用

19th International Symposium on Visual Computing

作者： Abdelfattah, Islam Shehata, Mohamed S. Univ British Columbia Dept Comp Sci Kelowna BC Canada

ISBN: (纸本)9783031773914;9783031773921

Video Object Segmentation (VOS) is a crucial task in computer vision, involving the identification, tracking, and segmentation of objects in video sequences. Despite significant advancements, state-of-the-art models often struggle with specific challenges such as occlusions and highly similar objects in close proximity. This paper presents the Mask Enhancement Model (MEM), an approach that combines the strengths of the Segment Anything Model (SAM) and the Cutie model to address these limitations. While SAM excels in zero-shot image segmentation, it is not inherently designed for video sequences. Conversely, Cutie provides robust segmentation using memory-based approaches but faces challenges with occlusions and similar objects. MEM integrates these models to produce an enhanced output mask, resulting in improving performance over each model individually. The proposed solution is evaluated through several experiments, demonstrating state-of-the-art J&Fscores on standard benchmark datasets, outperforming other stateof-the-art models. This paper details the MEM architecture, its integration with SAM and Cutie, and the improvements observed in video object segmentation performance. On DAVIS-17 dataset, MEM improves by 0.7% J&Fon Cuties and 3.2% on DeAOT-R50.

关键词： Video Object Segmentation Mask Enhancement Model Segment Anything Model Deep Learning

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Efficient Shortest Path Computation for Electric Vehicles in Time-Dependent Networks 35th

Efficient Shortest Path Computation for Electric Vehicles in...

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35th Australasian Database Conference

作者： Alam, Faisal Shen, Bojie Cheema, Muhammad Aamir Arora, Chetan Monash Univ Fac Informat Technol Clayton Vic Australia

ISBN: (纸本)9789819612413;9789819612420

Conventional vehicles significantly contribute to fossil fuel consumption, straining the planet. As efforts to achieve net-zero emissions intensify, the adoption of Electric Vehicles (EVs) in transportation has become crucial to success. While calculating efficient shortest paths in road networks is a common task, most studies focus primarily on charging needs and energy consumption models, often overlooking other factors that can affect the travel time of EV. In this paper, we address two key factors that impact travel time for EVs: (i) the variability of traffic conditions throughout the day, which causes travel times of each edge of the road network to change from time to time;and (ii) the limited availability of charging stations, which can lead to significant waiting times. To tackle these challenges, we first propose the pareto-optimal search to find the efficient shortest path for EVs as the baseline algorithm. However, the pareto-optimal search requires to maintain the pareto frontier at each vertex of graph, thus can be time-consuming due to its exponential branching. To improve efficiency, we introduce a binning algorithm that effectively reduces runtime while keeping a balance with solution quality. While our binning algorithm returns an approximate solution, the bin size can be adjusted to balance between query runtime and solution quality. Experimental results show that our binning algorithm outperforms the pareto-optimal search by around two orders of magnitude while effectively exploring near-optimal solutions.

关键词： Efficient Shortest Path Electric Vehicle Time-dependent Road Network

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Exploring Gesture-Based Interaction in Smartwatch Games: A Comparative Study Between Continuous Gesture Recognition and Hidden Markov Models 19th

Exploring Gesture-Based Interaction in Smartwatch Games: A C...

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19th International Symposium on Visual Computing

作者： Silva, Leonardo Fernandes, Deborah Nogueira, Emilia Felix, Juliana Cardoso, Luciana Aranha, Renan Nascimento, Thamer Horbylon Soares, Fabrizzio Fed Inst Goiano Campus Ipora Ipora Goias Brazil Univ Fed Goias Inst Informat Goiania Go Brazil Univ Fed Mato Grosso Cuiaba Goias Brazil

ISBN: (纸本)9783031773884;9783031773891

This work presents the evaluation of two interaction techniques in games using a smartwatch as a control device: On-screen Continuous Gesture Recognition and air gestures with HMM. The experiment involved participants, aged between 17 and 50 years old. The results indicated a clear preference for the On-screen Continuous Gesture Recognition technique, highlighting its effectiveness and acceptance by users. The analysis of the System Usability Scale (SUS) results showed a positive evaluation for this technique, while the HMM technique was considered less favorable for endless running games. Participants showed a preference for the on-screen touch approach, emphasizing its intuitiveness and satisfactory interaction experience. The findings suggest that On-screen Continuous Gesture Recognition provides a smoother and more natural interaction compared to air gestures with HMM.

关键词： Smartwatches Gesture interaction Continuous gesture recognition Hidden Markov Models (HMM) Games

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Hyperspectral Data Dimensionality Reduction: A Comparative Study Between PCA and Autoencoder Methods 10th

Hyperspectral Data Dimensionality Reduction: A Comparative S...

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10th International Conference on Modelling and Simulation for Autonomous Systems

作者： Motsch, Jean Bergeon, Yves Ktivanek, Vaclav Acad Mil St Cyr Coetquidan Guer France Univ Def Brno Czech Republic

ISBN: (纸本)9783031713965;9783031713972

Hyperspectral imaging has emerged as a powerful tool for remote sensing providing detection and identification of objects of interest using their unique spectral signature. Accurate information obtained can reveal details about the physical properties of materials that are relevant to intelligence gathering. Those interesting characteristics coupled with Unmanned Aerial Vehicles (UAVs) offer the perspective of easier detection of camouflaged army gear on the battlefield. This paper presents some aspect of hyperspectral measurements and processing and focuses on workload reduction and latent data representation using Principal Component Analysis (PCA) and autoencoder techniques. Both techniques are compared through a simple segmentation method that shows their efficiency in reducing the dimensionality of the hyperspectral data, spectrum-wise and image-wise.

关键词： hyperspectral images PCA autoencoders machine learning segmentation

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