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27th acm International Conference on Architectural Support for Programming Languages and Operating systems (ASPLOS)

作者： Zhang, Haotian Ren, Mengfei Lei, Yu Ming, Jiang Univ Texas Arlington Arlington TX 76019 USA

ISBN: (纸本)9781450392051

Embedded systems have become prominent targets for cyberattacks. To exploit firmware's memory corruption vulnerabilities, cybercriminals harvest reusable code gadgets from the large shared library codebase (e.g., uClibc). Unfortunately, unlike their desktop counterparts, embedded systems lack essential computing resources to enforce security hardening techniques. Recently, we have witnessed a surge of software debloating as a new defense mechanism against code-reuse attacks;it erases unused code to significantly diminish the possibilities of constructing reusable gadgets. Because of the single firmware image update style, static library debloating shows promise to fortify embedded systems without compromising performance and forward compatibility. However, static library debloating on stripped binaries (e.g., firmware's shared libraries) is still an enormous challenge. In this paper, we show that this challenge is not insurmountable for MIPS firmware. We develop a novel system, named. mu Trimmer, to identify and wipe out unused basic blocks from shared libraries' binary code, without causing additional runtime overhead or memory consumption. We propose a new method to identify address-taken blocks/functions, which further help us maintain an interprocedural control flow graph to conservatively include library code that could be potentially used by firmware. By capturing address access patterns for position-independent code, we circumvent the challenge of determining code-pointer targets and safely eliminate unused code. We run. mu Trimmer to debloat shared libraries for SPEC CPU2017 benchmarks, popular firmware applications (e.g., Apache, BusyBox, and OpenSSL), and a real-world wireless router firmware image. Our experiments show that not only does. mu Trimmer deliver functional programs, but also it can cut the exposed code surface and eliminate various reusable code gadgets remarkably. mu Trimmer's debloating capability can compete with the static linking results.

关键词： software debloating static analysis embedded systems

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Understanding the Digital Lives of Youth: Analyzing Media Shared within Safe Versus Unsafe Private Conversations on Instagram 22

Understanding the Digital Lives of Youth: Analyzing Media Sh...

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CHI Conference on Human Factors in computing systems (CHI)

作者： Ali, Shiza Razi, Afsaneh Seunghyun, Kim Alsoubai, Ashwaq Gracie, Joshua De Choudhury, Munmun Wisniewski, Pamela J. Stringhini, Gianluca Boston Univ Boston MA 02215 USA Univ Cent Florida Orlando FL 32816 USA Georgia Inst Technol Atlanta GA 30332 USA

ISBN: (纸本)9781450391573

We collected Instagram Direct Messages (DMs) from 100 adolescents and young adults (ages 13-21) who then flagged their own conversations as safe or unsafe. We performed a mixed-method analysis of the media files shared privately in these conversations to gain human-centered insights into the risky interactions experienced by youth. Unsafe conversations ranged from unwanted sexual solicitations to mental health related concerns, and images shared in unsafe conversations tended to be of people and convey negative emotions, while those shared in regular conversations more often conveyed positive emotions and contained objects. Further, unsafe conversations were significantly shorter, suggesting that youth disengaged when they felt unsafe. Our work uncovers salient characteristics of safe and unsafe media shared in private conversations and provides the foundation to develop automated systems for online risk detection and mitigation.

关键词： Adolescents Teens Datasets Instagram unsafe private conversations Image analysis

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Towards a Design Space for Emotion Recognition 21

Towards a Design Space for Emotion Recognition

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acm International Joint Conference on Pervasive and Ubiquitous computing (UbiComp) / acm International Symposium on Wearable Computers (ISWC)

作者： Motti, Vivian Genaro George Mason Univ Fairfax VA 22030 USA

ISBN: (纸本)9781450384612

Recognizing emotions through pervasive technologies has been the objective of several research studies. Still, the inherent complexities of emotion recognition result in applications that support the process rather than fully address it. Existing methods for data collection combine multiple sensors and devices. The analysis and classification of users' and environmental data face challenges to reach high accuracy, responsiveness, and reliability. Because emotion recognition is user-dependent, it still remains as an open challenge to be resolved. This paper provides a unified view about emotion recognition, presenting a multidimensional design space that includes multiple approaches. We discuss the practicalities involved with the implementation of each approach and the deployment of emotion recognition systems. We conclude with a discussion about their advantages, limitations, and open questions.

关键词： affective computing emotion recognition design space comparative analysis

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Energy-Constrained D2D Assisted Federated Learning in Edge computing 22

Energy-Constrained D2D Assisted Federated Learning in Edge C...

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25th acm International Conference on Modeling analysis and Simulation of Wireless and Mobile systems (MSWiM)

作者： Li, Yuchen Liang, Weifa Li, Jing Cheng, Xiuzhen Yu, Dongxiao Zomaya, Albert Y. Guo, Song Australian Natl Univ Canberra ACT Australia City Univ Hong Kong Hong Kong Peoples R China Hong Kong Polytech Univ Hong Kong Peoples R China Shandong Univ Qingdao Peoples R China Univ Sydney Sydney NSW Australia

ISBN: (纸本)9781450394796

The surging of deep learning brings new vigor and vitality to shape the prospect of intelligent Internet of Things (IoT), and edge intelligence arises to provision real-time deep neural network (DNN) inference services for mobile users. To perform efficient and effective DNN model training in edge environments while preserving training data security and privacy of IoT devices, federated learning has been envisioned as an ideal learning paradigm for this purpose. In this paper we study energy-aware DNN model training in an edge environment. We first formulate a novel energy-aware, device-to-device (D2D) assisted federated learning problem with the aim to minimize the global loss of a training DNN model, subject to bandwidth capacity on an edge server and the energy capacity on each IoT device. We then devise an efficient heuristic algorithm for the problem. The crux of the proposed algorithm is to explore the energy usage of neighboring devices of each device for its local model uploading, by reducing the problem to a series of maximum weight matching problems in corresponding auxiliary graphs. We finally evaluate the performance of the proposed algorithm through experimental simulations. Experimental results show that the proposed algorithm is promising.

关键词： energy-aware federated learning D2D-assisted edge learning

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A New Lower Bound for Deterministic Truthful Scheduling

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ALGORITHMICA 2021年第9期83卷 2895-2913页

作者： Giannakopoulos, Yiannis Hammerl, Alexander Pocas, Diogo Friedrich Alexander Univ Erlangen Nurnberg FAU Erlangen Germany Tech Univ Munich Munich Germany Univ Lisbon LASIGE Fac Ciencias Lisbon Portugal

We study the problem of truthfully scheduling m tasks to n selfish unrelated machines, under the objective of makespan minimization, as was introduced in the seminal work of Nisan and Ronen (in: The 31st Annual acm symposium on Theory of computing (STOC), 1999). Closing the current gap of [2.618, n] on the approximation ratio of deterministic truthful mechanisms is a notorious open problem in the field of algorithmic mechanism design. We provide the first such improvement in more than a decade, since the lower bounds of 2.414 (for n = 3) and 2.618 (for n -> infinity) by Christodoulou et al. (in: proceedings of the 18th Annual acm-SIAM Symposium on Discrete Algorithms (SODA), 2007) and Koutsoupias and Vidali (in: proceedings of Mathematical Foundations of Computer Science (MFCS), 2007), respectively. More specifically, we show that the currently best lower bound of 2.618 can be achieved even for just n = 4 machines;for n = 5 we already get the first improvement, namely 2.711;and allowing the number of machines to grow arbitrarily large we can get a lower bound of 2.755.

关键词： Algorithm analysis and Problem Complexity Theory of Computation Mathematics of computing Algorithms Computer systems Organization and Communication Networks Data Structures and Information Theory

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Video-Based Jump Height Estimation in Athletic Performance Testing

Video-Based Jump Height Estimation in Athletic Performance T...

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2023 IEEE International Workshop on Sport, Technology and Research, STAR 2023

作者： Lokas, Ivan Vasilj, Matea Skender, Sven Vucetic, Vlatko Mihaldinec, Hrvoje Dzapo, Hrvoje Ultrax Technologies Software Development Zagreb Croatia Human Performance Laboratory Faculty of Kinesiology Zagreb Croatia Hardware Development Ultrax Technologies Zagreb Croatia Faculty of Electrical Engineering and Computing Department of Electronic Systems and Information Processing Zagreb Croatia

ISBN: (纸本)9798350316056

Jump height estimation is well-studied problem in sports science with a variety of methods proposed over the years. This paper introduces a portable, simple-to-setup and a cost-effective video-based jump height estimation method, and compares it with existing traditional methods that use expensive and specialized equipment. To enable more accurate comparison between different systems, a custom-designed Inertial measurement Unit (IMU) was used as an additional sensor input. The analysis was performed on eleven female physically active handball players. The dataset consists of three most common vertical jump variations: squat jump, counter-movement jump and counter-movement jump with free arms. The analysis show that our video-based approach achieves comparable results to the traditional methods. © 2023 IEEE.

关键词： Cost effectiveness

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Sports Training 3D Human Motion Simulation and Video analysis Based on Fish Swarm Algorithm

Sports Training 3D Human Motion Simulation and Video Analysi...

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2023 International Conference on Networking, Informatics and computing, ICNETIC 2023

作者： Zhang, Mengjie Xi'an Academy of Fine Arts Sports Ministry Xi'an710065 China

ISBN: (纸本)9798350313314

Computer vision is an important branch of computer science and artificial intelligence. The main content of its research is how to use a variety of imaging systems instead of visual organs as signal input means, by the computer to complete the processing and interpretation of information instead of the brain. That is, from the traditional method mainly based on human eye observation to the human motion measurement method based on high precision video capture and analysis, from the experience-based training analysis method to the human motion analysis method based on human motion simulation change. With the maturity and popularization of motion capture technology, it has become a reality to acquire a large number of 3d motion data sets efficiently and quickly. Digital graphics and image technology are introduced into sports training, and a 3d human motion simulation and video analysis system for sports training is developed. It has become an important development direction of sports teaching to conduct standardized guidance and scientific teaching for sports participants through sports video. The ultimate research goal of computer vision is to enable computers to observe and understand the world through vision as humans do. Among them, the realization of key frame extraction, automatic recognition and classification of 3D human motion data is an important research content of human motion analysis, and an important premise and basis for the effective management and reuse of motion capture data. © 2023 IEEE.

关键词： Sports

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International Conference on Edge computing and Applications, ICECAA 2022 - proceedings

International Conference on Edge Computing and Applications,...

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2022 International Conference on Edge computing and Applications, ICECAA 2022

ISBN: (纸本)9781665482325

The proceedings contain 325 papers. The topics discussed include: an overview on emerging security threats in big data clusters and their defenses;construction of intelligent network for sports training safety assurance based on portable heart rate detection intelligent equipment;blockchain based electronic voting machine;implementing machine learning adoption and blockchain in the health care system;enhanced optimized link state secure routing algorithm using RSA crypto key exchange & revocation in FANET framework;federated learning approach for tracking malicious activities in cyber-physical systems;federated learning approach for tracking malicious activities in cyber-physical systems;design of emergency management system for public emergencies under big data, intrusion detection, and defense;data interface matching and information security measurement of scientific and technological innovation measurement analysis and multi-agent economic MIS;an adaptive long-short term prediction model for resource management in cloud;improving security in edge computing by using cognitive trust management model;and trustworthy cloud storage data protection based on blockchain technology.

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Prevalence and Salience of Problematic Microtransactions in Top-Grossing Mobile and PC Games: A Content analysis of User Reviews 22

Prevalence and Salience of Problematic Microtransactions in ...

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CHI Conference on Human Factors in computing systems (CHI)

作者： Petrovskaya, Elena Deterding, Sebastian Zendle, David Univ York York N Yorkshire England

ISBN: (纸本)9781450391573

Microtransactions have become a major monetisation model in digital games, shaping their design, impacting player experience, and raising ethical concerns. Research in this area has chiefly focused on loot boxes. This begs the question whether other microtransactions might actually be more relevant and problematic for players. We therefore conducted a content analysis of negative player reviews (n=801) of top-grossing mobile and desktop games to determine which problematic microtransactions are most prevalent and salient for players. We found that problematic microtransactions with mobile games featuring more frequent and different techniques compared to desktop games. Across both, players minded issues related to fairness, transparency, and degraded user experience, supporting prior theoretical work, and importantly take issue with monetisation-driven design as such. We identify future research needs on why microtransactions in particular spark this critique, and which player communities it may be more or less representative of.

关键词： microtransactions mobile games dark patterns player experience ethics

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Stationary Behavior of Constant Stepsize SGD Type Algorithms: An Asymptotic Characterization

Stationary Behavior of Constant Stepsize SGD Type Algorithms...

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作者： Chen, Zaiwei Mou, Shancong Maguluri, Siva Theja Georgia Institute of Technology 755 Ferst Dr NW AtlantaGA30332 United States

Stochastic approximation (SA) and stochastic gradient descent (SGD) algorithms are work-horses for modern machine learning algorithms. Their constant stepsize variants are preferred in practice due to fast convergence behavior. However, constant stepsize SA algorithms do not converge to the optimal solution, but instead have a stationary distribution, which in general cannot be analytically characterized. In this work, we study the asymptotic behavior of the appropriately scaled stationary distribution, in the limit when the constant stepsize goes to zero. Specifically, we consider the following three settings: (1) SGD algorithm with a smooth and strongly convex objective, (2) linear SA algorithm involving a Hurwitz matrix, and (3) nonlinear SA algorithm involving a contractive operator. When the iterate is scaled by 1/α, where α is the constant stepsize, we show that the limiting scaled stationary distribution is a solution of an implicit equation. Under a uniqueness assumption (which can be removed in certain settings) on this equation, we further characterize the limiting distribution as a Gaussian distribution whose covariance matrix is the unique solution of a suitable Lyapunov equation. For SA algorithms beyond these cases, our numerical experiments suggest that unlike central limit theorem type results: (1) the scaling factor need not be 1/α, and (2) the limiting distribution need not be Gaussian. Based on the numerical study, we come up with a heuristic formula to determine the right scaling factor, and make insightful connection to the Euler-Maruyama discretization scheme for approximating stochastic differential equations. © 2022 acm.

关键词： Asymptotic analysis

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