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STALKER: A Framework to Analyze Fragility of Cryptographic Libraries under Hardware Fault Models 60

STALKER: A Framework to Analyze Fragility of Cryptographic L...

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60th acm/IEEE Design Automation Conference (DAC)

作者： Xu, Guorui Zhang, Fan Zhao, Xinjie Chen, Yuan Guo, Shize Ren, Kui Zhejiang Univ Hangzhou Peoples R China

ISBN: (纸本)9798350323481

For embedded devices, the uncertainty of target physical environments is always a great challenge. With constrained resources and common overloaded uses, they can be more exposed to hardware faults. Other than stability and ordinary security issues, there exist some subtle phenomenons that lead to potential cryptanalysis or secret leakage. In this paper, we present STALKER, a framework to analyze the fragility of libraries under hardware fault models. Compared with existing tools, our framework targets faulty execution outputs, and can flexibly work on different libraries, architectures and support different search schemes. We find dozens of security-sensitive bits that may cause critical issues and provide detailed analysis.

关键词： Fault injection Embedded systems Cryptographic libraries Hardware Faults

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Intelligent Automation in Stock Market Prediction: A Survey of Automated Models 4

Intelligent Automation in Stock Market Prediction: A Survey ...

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4th IEEE International Conference on Smart Technologies in computing, Electrical and Electronics, ICSTCEE 2023

作者： Anirudhan Adukkathayar, C. Hulipalled, Vishwanath R. Simha, Jay Bharthish Chundi, Ramesh Reva University Bangalore India Reva University School Of Computing And Information Technology Bangalore India Reva University Abiba Systems Cto And Race Labs Bangalore India Reva University School Of Computer Science And Applications Bangalore India

ISBN: (纸本)9798350384628

In an era marked by global digitization, the landscape of stock market prediction has undergone a transformative shift, ushering in a new era of technologically-driven trading. With soaring market capitalization, stock trading has emerged as a focal point for financial investment. Analysts and researchers have pioneered tools and methodologies to anticipate stock price movements, empowering investors in making informed decisions. Advanced trading models now harness unconventional textual data from social platforms, leveraging cutting-edge machine learning techniques like text data analytics and ensemble methods to significantly enhance prediction accuracies. Despite these advancements, the dynamic, erratic, and often chaotic nature of stock market data continues to present formidable challenges. This study elucidates the systematic application of machine learning-based approaches and sentimental analysis approaches for stock market prediction, grounded in a versatile framework. A critical analysis of findings from the reputable digital libraries and databases including acm digital library and Scopus, forms the cornerstone of this inquiry. Moreover, an expansive comparative analysis was conducted to delineate key trends and significant directions. This comprehensive exploration aims to furnish budding researchers with a foundational understanding of this burgeoning domain and pave the way for further inquiry into promising avenues. © 2023 IEEE.

关键词： Sentiment analysis

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Trace analysis Based Microservice Architecture measurement 2022

Trace Analysis Based Microservice Architecture Measurement

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30th acm Joint European Software Engineering Conference / Symposium on the Foundations of Software Engineering (ESEC/FSE)

作者： Peng, Xin Zhang, Chenxi Zhao, Zhongyuan Isami, Akasaka Guo, Xiaofeng Cui, Yunna Fudan Univ Shanghai Peoples R China Alibaba Grp Beijing Peoples R China Fudan Univ Sch Comp Sci Shanghai Peoples R China Fudan Univ Shanghai Key Lab Data Sci Shanghai Peoples R China

ISBN: (纸本)9781450394130

Microservice architecture design highly relies on expert experience and may often result in improper service decomposition. Moreover, a microservice architecture is likely to degrade with the continuous evolution of services. Architecture measurement is thus important for the long-term evolution of microservice architectures. Due to the independent and dynamic nature of services, source code analysis based approaches cannot well capture the interactions between services. In this paper, we propose a trace analysis based microservice architecture measurement approach. We define a trace data model for microservice architecture measurement, which enables fine-grained analysis of the execution processes of requests and the interactions between interfaces and services. Based on the data model, we define 14 architectural metrics to measure the service independence and invocation chain complexity of a microservice system. We implement the approach and conduct three case studies with a student course project, an open-source microservice benchmark system, and three industrial microservice systems. The results show that our approach can well characterize the independence and invocation chain complexity of microservice architectures and help developers to identify microservice architecture issues caused by improper service decomposition and architecture degradation.

关键词： Microservice Tracing Architecture Dynamic analysis

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Trace analysis of Electric Micromobility and its Application for City Sensing 28

Trace Analysis of Electric Micromobility and its Application...

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28th IEEE/acm International Symposium on Distributed Simulation and Real Time Applications, DS-RT 2024

作者： Esposito, Alfonso Ciabattini, Leonardo Sciullo, Luca Montanari, Marco Bononi, Luciano Felice, Marco Di University of Bologna Department of Computer Science and Engineering Italy

ISBN: (纸本)9798331527211

Electric micromobility is increasingly being adopted as a urban transportation means. This emerging class of vehicles, thanks to its onboard hardware and embedded sensors, can be used for gathering IoT data across cities or for producing valuable insights on users' driving behavior. However, the limited availability of public datasets on e-mobility poses a significant challenge for research, restricting the potential for improving the modeling and optimization of city-scale mobility systems. In this paper, we present an in-depth analysis of electric micromobility using GPS traces from three Italian cities. Furthermore, we identify significant spatio-temporal patterns and develop algorithms to reconstruct rental trips and model user demands, enabling the generation of synthetic vehicular traces for various urban scenarios and arbitrary number of vehicles. Our findings reveal distinct temporal patterns influenced by seasons and time of day, and spatial patterns showing varying distances covered by different vehicle types. Notably, our simulations for the city of Bologna demonstrate the potential of using electric micromobility vehicles as mobile sensors for city-sensing applications, providing extensive urban coverage with minimal units. © 2024 IEEE.

关键词： Urban transportation

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Read Between the Lines: Detecting Tracking JavaScript with Bytecode Classification 23

Read Between the Lines: Detecting Tracking JavaScript with B...

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30th acm SIGSAC Conference on Computer and Communications Security (acm CCS)

作者： Ghasemisharif, Mohammad Polakis, Jason Univ Illinois Chicago IL 60607 USA

ISBN: (纸本)9798400700507

Browsers and extensions that aim to block online ads and tracking scripts predominantly rely on rules from filter lists for determining which resource requests must be blocked. These filter lists are often manually curated by a community of online users. However, due to the arms race between blockers and ad-supported websites, these rules must continuously get updated so as to adapt to novel bypassing techniques and modified requests, thus rendering the detection and rule-generation process cumbersome and reactive (which can result in major delays between propagation and detection). In this paper, we address the detection problem by proposing an automated pipeline that detects tracking and advertisement JavaScript resources with high accuracy, designed to incur minimal false positives and overhead. Our method models script detection as a text classification problem, where JavaScript resources are documents containing bytecode sequences. Since bytecode is directly obtained from the JavaScript interpreter, our technique is resilient against commonly used bypassing methods, such as URL randomization or code obfuscation. We experiment with both deep learning and traditional ML-based approaches for bytecode classification and show that our approach identifies ad/tracking scripts with 97.08% accuracy, significantly outperforming cutting-edge systems in terms of both precision and the level of required features. Our experimental analysis further highlights our system's capabilities, by demonstrating how it can augment filter lists by uncovering ad/tracking scripts that are currently unknown, as well as proactively detecting scripts that have been erroneously added by list curators.

关键词： measurement Web security Privacy Ad/tracking blocking

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A Comparative analysis of Social Media Platforms: Cultivating Psychological Safety for Financially-Constrained Aspiring Entrepreneurs

A Comparative Analysis of Social Media Platforms: Cultivatin...

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2025 CHI Conference on Human Factors in computing systems, CHI EA 2025

作者： Yudiani, Annisa Permata Dillahunt, Tawanna R. Israni, Aarti School of Information University of Michigan Ann ArborMI United States

ISBN: (纸本)9798400713958

Psychological safety, which allows people to seek feedback and ask questions without fear, is essential for aspiring entrepreneurs in financially-constrained communities to access support online. However, little is known about how existing social media platforms support psychological safety for individuals in these communities. To address this gap, we conducted a competitive analysis of seven social media platforms frequently used by entrepreneurs, evaluating each based on established criteria for fostering psychological safety. These criteria included features that guided interactions, highlighted shared identities among community members, protected user privacy, and fostered interpersonal trust. We identify untapped opportunities for social media platforms to better support financially-constrained aspiring entrepreneurs. These include incorporating effective conversational prompts, emphasizing more meaningful shared identities, and promoting synchronous interactions. Our findings offer actionable insights for designing psychologically safe and inclusive social media platforms to support financially-marginalized communities. © 2025 Copyright held by the owner/author(s).

关键词： Tweets

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Scaling analysis of Creative Activity Traces via Fuzzy Linkography

Scaling Analysis of Creative Activity Traces via Fuzzy Linko...

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2025 CHI Conference on Human Factors in computing systems, CHI EA 2025

作者： Smith, Amy Anderson, Barrett R. Otto, Jasmine Tan Karth, Isaac Sun, Yuqian Chung, John Joon Young Roemmele, Melissa Kreminski, Max Queen Mary University of London London United Kingdom San Mateo CA United States Berkeley CA United States Midjourney London United Kingdom Midjourney San FranciscoCA United States

ISBN: (纸本)9798400713958

Creativity researchers sometimes employ linkography—a family of techniques involving the visualization and analysis of links between design moves—to make sense of people’s behavior in creative contexts, but traditional linkography (which involves manual annotation of both moves and links) is so time-consuming that it is mostly applied at very small scales. Meanwhile, digital creativity support tools (e.g., text-to-image prompting tools) automatically capture vast numbers of user interaction traces, but these traces are not yet well understood. We introduce a means of quickly and automatically producing fuzzy linkographs of text-to-image prompting traces and apply this technique to a large corpus of traces collected from the live deployment of a commercial text-to-image tool. This allows us to uncover recurring linkographic structures in text-to-image prompting interactions;cluster traces to classify user behaviors into several distinct archetypes;and quickly sift through thousands of traces to surface structurally interesting episodes of prompting. © 2025 Copyright held by the owner/author(s).

关键词： Visualization

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BikeSimWS: Workshop on Simulators, Scenarios, and Test Standard for Bicycle Research 23

BikeSimWS: Workshop on Simulators, Scenarios, and Test Stand...

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2nd International Conference on Mobile and Ubiquitous Multimedia, proceedings of MUM 2023

作者： Wintersberger, Philipp Matviienko, Andrii Wang, Yu Ebel, Patrick Al-Taie, Ammar Brewster, Stephen Michahelles, Florian Stuiver, Arjan University of Applied Sciences Upper Austria Hagenberg Austria Tu Wien Austria Kth Royal Institute of Technology Stockholm Sweden ScaDS.AI Leipzig University Leipzig Germany Glasgow Interactive Systems Section School of Computing Science Univ. of Glasgow United Kingdom University of Groningen Netherlands

ISBN: (纸本)9798400709210

Research on cyclists"safety and comfort is a growing topic. Existing works address support systems with novel interaction concepts such as augmented reality but also the design and evaluation of high-fidelity bicycle simulators. Since the field is still in its exploratory phase, there have been few attempts to systematically provide guidance for conducting experiments. For example, there is no consensus on the choice of representative driving scenarios, the proper choice of different bicycle simulators, and measurement standards to systematically compare the results of different studies. With this workshop, we want the community to gather and discuss a roadmap for the future of HCI bicycle research so that these issues can be overcome. © 2023 Owner/Author.

关键词： Mixed reality

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CreAItive Collaboration? Users' Misjudgment of AI-Creativity Affects Their Collaborative Performance 25

CreAItive Collaboration? Users' Misjudgment of AI-Creativity...

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2025 CHI Conference on Human Factors in computing systems, CHI 2025

作者： Bangerl, Mia Magdalena Disch, Leonie David, Tamara Pammer-Schindler, Viktoria Institute of Human-Centred Computing Graz University of Technology Styria Graz Austria Area Digital Transformation Design Know Center Research GmbH Styria Graz Austria Digital Transformation Design Know Center Research GmbH Styria Graz Austria Graz University of Technology Graz Austria Know Center Research GmbH Graz Austria

ISBN: (纸本)9798400713941

How does generative AI affect collaborative creative work and humans' capability to carry it out? We tested 52 participant pairs in a standard creativity test, the Alternate Uses Test. The experimental AI group had access to ChatGPT-4, while the control group did not. The intervention did not lead to an improved performance overall. Further, the AI group elaborated their ideas significantly less. This effect carried over to the unaided post-test, pointing to longer-term effects of AI be(com)ing everyday technology, as how people perform a task with a tool shapes how they (learn to) perform the task without it. analysis of the human-AI collaboration process revealed that participants were selective in using ChatGPT-4 output for the experimental task, misjudging and falsely assessing its output. This actually reduced their number of created ideas and underscores that users need to understand a (generative AI-based) tool's capability for the specific task to support effective performance. © 2025 Copyright held by the owner/author(s).

关键词： generative AI

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Confirmation Bias: The Double-Edged Sword of Data Facts in Visual Data Communication 25

Confirmation Bias: The Double-Edged Sword of Data Facts in V...

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2025 CHI Conference on Human Factors in computing systems, CHI 2025

作者： Li, Shiyao Davidson, Thomas James Xiong Bearfield, Cindy Wall, Emily Computer Science Emory University AtlantaGA United States Interactive Computing Georgia Institute of Technology AtlantaGA United States

ISBN: (纸本)9798400713941

Incorporating data facts, which are natural language descriptions of data patterns, alongside visualizations can guide readers and enhance the visibility of data patterns. However, data facts might also induce confirmation bias in visual analysis. We conducted a series of crowdsourced experiments to explore the biasing effects of data facts. Our findings show that the presentation style, strength, and alignment of data facts with pre-existing beliefs significantly impact confirmation bias. Data facts that support prior beliefs can exacerbate confirmation bias, whereas those that refute an individual's beliefs can mitigate it. This effect is amplified when data facts are used in combination with visual annotations. Data facts describing variable correlations are perceived to be more compelling than ones describing average values and are associated with higher levels of confirmation bias. We underscore the persuasive influence of data facts in visualizations and caution against their indiscriminate use in efforts to mitigate bias. © 2025 Copyright held by the owner/author(s).

关键词： Data visualization

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