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Conference on Research on Equitable and Sustained Participation in Engineering, computing, and Technology (RESPECT)

作者： Mak, Janice Capurro, Carolina Torrejon Arizona State Univ Tempe AZ 85281 USA

ISBN: (纸本)9798400706264

Policymakers and intermediary organizations have focused on secondary computer science (CS) as a policy goal with 30 states requiring high schools to offer CS, 37 states counting CS as math or science course, and 8 states mandating CS as a graduation requirement in 2023. This qualitative study unveils preliminary findings from focus groups with Computer Science Education State Supervisors (CSEdSS) (n=11). CSEdSS were asked about the impact, implementation, and perspectives of secondary CS policies. Using a complex systems lens, we identify accelerators and policy tensions related to secondary CS education implementation from the perspectives of CSEdSS and discuss ways in which researchers and policymakers can collaborate to advance equitable CS education.

关键词： CS graduation requirement CS education policy equity in CS education complex systems theory

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MetaVRadar: Measuring Metaverse Virtual Reality Network Activity

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proceedings of the acm on measurement and analysis of computing systems 2023年第3期7卷 1-29页

作者： Lyu, Minzhao Tripathi, Rahul Dev Sivaraman, Vijay Univ New South Wales Sydney NSW Australia

The "metaverse", wherein users can enter virtual worlds to work, study, play, shop, socialize, and entertain, is fast becoming a reality, attracting billions of dollars in investment from companies such as Meta, Microsoft, and Clipo Labs. Further, virtual reality (VR) headsets from entities like Oculus, HTC, and Microsoft are rapidly maturing to provide fully immersive experiences to metaverse users. However, little is known about the network dynamics of metaverse VR applications in terms of service domains, flow counts, traffic rates and volumes, content location and latency, etc., which are needed to make telecommunications network infrastructure "metaverse ready" to support superlative user experience in the coming future. This paper is an empirical measurement study of metaverse VR network behavior aimed at helping telecommunications network operators better provision and manage the network to ensure good user experience. Using illustrative hour-long network traces of metaverse sessions on the Oculus VR headset, we first develop a categorization of user activity into distinct states ranging from login home to streetwalking and event attendance to asset trading, and undertake a detailed analysis of network traffic per state, identifying unique service domains, protocols, flow profiles, and volumetric patterns, thereby highlighting the vastly more complex nature of a metaverse session compared to streaming video or gaming. Armed with the network behavioral profiles, our second contribution develops a real-time method MetaVRadar to detect metaverse session and classify the user activity state leveraging formalized flow signatures and volumetric attributes. Our third contribution practically implements MetaVRadar, evaluates its accuracy in our lab environment, and demonstrates its usability in a large university network so operators can better monitor and plan resources to support requisite metaverse user experience.

关键词： metaverse virtual reality network traffic analysis

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analysis of Security Permissions on Android and iOS from a Privacy Perspective 50

Analysis of Security Permissions on Android and iOS from a P...

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50th Latin American computing Conference (CLEI)

作者： Luna, Carlos Galuppo, Raul Ignacio Univ La Republ Fac Ingn Montevideo Uruguay Univ Nacl Rosario FCEIA Rosario Argentina

ISBN: (纸本)9798331540982;9798331540975

Security on mobile devices is fundamental, as they are managing confidential information in particular. Two of the most popular operating systems for mobile devices are Android and iOS. This work presents and analyzes some key characteristics of its security models, considering in particular its permission systems. Additionally, this paper presents a hybrid mobile application, a framework, for permission analysis that can run on both Android and iOS. The framework, which can be extended, places special emphasis on the relationship between the user's privacy and the permission system.

关键词： Android iOS Security Privacy Permission

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Towards Network-friendly and Privacy-preserving Immersive computing

Towards Network-friendly and Privacy-preserving Immersive Co...

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2024 CoNEXT Student Workshop

作者： Cheng, Ruizhi George Mason Univ Fairfax VA 22030 USA

ISBN: (纸本)9798400712555

Immersive computing has transformed the way we interact with digital and physical worlds by blurring boundaries between them. However, as these technologies evolve, they introduce growing challenges related to increasing network demands and heightened privacy concerns. This article addresses these issues through three pivotal studies. First, we conduct a comprehensive measurement study of commercial social virtual reality platforms and immersive telepresence systems. We then propose MagicStream, a novel system for reducing bandwidth consumption and latency in immersive telepresence leveraging semantic communication. Finally, we introduce MetaFL, a federated-learning-based framework to accurately authenticate extended reality (XR) users while preserving their privacy. Our extensive evaluations reveal their advances in network efficiency and privacy compared to state-of-the-art efforts.

关键词： Network measurement Immersive Telepresence User Authentication Privacy Preservation Augmented/Virtual/Mixed Reality

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Optimized Cross-Path Attacks via Adversarial Reconnaissance

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proceedings of the acm on measurement and analysis of computing systems 2023年第3期7卷 1-30页

作者： Huang, Yudi Lin, Yilei He, Ting Penn State Univ University Pk PA 16802 USA Meta Santa Clara CA USA

While softwarization and virtualization technologies make modern communication networks appear easier to manage, they also introduce highly complex interactions within the networks that can cause unexpected security threats. In this work, we study a particular security threat due to the sharing of links between high-security paths and low-security paths, which enables a new type of DoS attacks, called cross-path attacks, that indirectly attack a set of targeted high-security paths (target paths) by congesting the shared links through a set of attacker-controlled low-security paths (attack paths). While the feasibility of such attacks has been recently demonstrated in the context of SDN, their potential performance impact has not been characterized. To this end, we develop an approach for designing an optimized cross-path attack under a constrained total attack rate, consisting of (i) novel reconnaissance algorithms that can provide consistent estimates of the locations and parameters of the shared links via network tomography, and (ii) efficient optimization methods to design the optimal allocation of attack rate over the attack paths to maximally degrade the performance of the target paths. The proposed attack has achieved a significantly larger performance impact than its non-optimized counterparts in extensive evaluations based on multiple network settings, signaling the importance of addressing such intelligent attacks in network design.

关键词： Denial-of-service attack topology inference queueing analysis adversarial reconnaissance attack modeling

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CarbonScaler: Leveraging Cloud Workload Elasticity for Optimizing Carbon-Efficiency

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proceedings of the acm on measurement and analysis of computing systems 2023年第3期7卷 1-28页

作者： Hanafy, Walid A. Liang, Qianlin Bashir, Noman Irwin, David Shenoy, Prashant Univ Massachusetts Amherst Amherst MA 01003 USA

Cloud platforms are increasing their emphasis on sustainability and reducing their operational carbon footprint. A common approach for reducing carbon emissions is to exploit the temporal flexibility inherent to many cloud workloads by executing them in periods with the greenest energy and suspending them at other times. Since such suspend-resume approaches can incur long delays in job completion times, we present a new approach that exploits the elasticity of batch workloads in the cloud to optimize their carbon emissions. Our approach is based on the notion of "carbon scaling," similar to cloud autoscaling, where a job dynamically varies its server allocation based on fluctuations in the carbon cost of the grid's energy. We develop a greedy algorithm for minimizing a job's carbon emissions via carbon scaling that is based on the well-known problem of marginal resource allocation. We implement a CarbonScaler prototype in Kubernetes using its autoscaling capabilities and an analytic tool to guide the carbon-efficient deployment of batch applications in the cloud. We then evaluate CarbonScaler using real-world machine learning training and MPI jobs on a commercial cloud platform and show that it can yield i) 51% carbon savings over carbon-agnostic execution;ii) 37% over a state-of-the-art suspend-resume policy;and iii) 8% over the best static scaling policy.

关键词： Carbon efficiency Sustainable computing Auto scaling

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Influences in Mixing Measures 2024

Influences in Mixing Measures

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56th Annual acm Symposium on Theory of computing (STOC)

作者： Koehler, Frederic Lifshitz, Noam Minzer, Dor Mossel, Elchanan Univ Chicago Chicago IL USA Hebrew Univ Jerusalem Jerusalem Israel MIT Cambridge MA 02139 USA

ISBN: (纸本)9798400703836

The theory of influences in product measures has profound applications in theoretical computer science, combinatorics, and discrete probability. This deep theory is intimately connected to functional inequalities and to the Fourier analysis of discrete groups. Originally, influences of functions were motivated by the study of social choice theory, wherein a Boolean function represents a voting scheme, its inputs represent the votes, and its output represents the outcome of the elections. Thus, product measures represent a scenario in which the votes of the parties are randomly and independently distributed, which is often far from the truth in real-life scenarios. We begin to develop the theory of influences for more general measures under mixing or spectral independence conditions. More specifically, we prove analogues of the KKL and Talagrand influence theorems for Markov Random Fields on bounded degree graphs when the Glauber dynamics mix rapidly. We thus resolve a long standing challenge, stated for example by Kalai and Safra (2005). We show how some of the original applications of the theory of in terms of voting and coalitions extend to these general dependent measures. Our results thus shed light both on voting with correlated voters and on the behavior of general functions of Markov Random Fields (also called "spin-systems") where the Glauber dynamics mixes rapidly.

关键词： analysis of Boolean Functions Influences of Variables Non-product Measures

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Piecing Together the Jigsaw Puzzle of Transactions on Heterogeneous Blockchain Networks

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proceedings of the acm on measurement and analysis of computing systems 2024年第3期8卷 1-27页

作者： Hu, Xiaohui Feng, Hang Xia, Pengcheng Tyson, Gareth Wu, Lei Zhou, Yajin Wang, Haoyu Huazhong Univ Sci & Technol Hubei Engn Res Ctr Big Data Secur Sch Cyber Sci & Engn Hubei Key Lab Distributed Syst Secur Wuhan Peoples R China Zhejiang Univeristy Hangzhou Peoples R China Hong Kong Univ Sci & Technol GZ Hong Kong Peoples R China

The Web3 ecosystem is increasingly evolving to multi-chain, with decentralized applications (dApps) distributing across different blockchains, which drives the need for cross-chain bridges for blockchain interoperability. However, it further opens new attack surfaces, and media outlets have reported serious attacks related to cross-chain bridges. Nevertheless, few prior research studies have studied cross-chain bridges and their related transactions, especially from a security perspective. To fill the void, this paper presents the first comprehensive analysis of cross-chain transactions. We first make efforts to create by far the largest cross-chain transaction dataset based on semantic analysis of popular cross-chain bridges, covering 13 decentralized bridges and 7 representative blockchains, with over 80 million transactions in total. Based on this comprehensive dataset, we present the landscape of cross-chain transactions from angles including token usage, user profile and the purposes of transactions, etc. We further observe that cross-chain bridges can be abused for malicious/aggressive purposes, thus we design an automated detector and deploy it in the wild to flag misbehaviors from millions of cross-chain transactions. We have identified hundreds of abnormal transactions related to exploits and arbitrages, etc. Our research underscores the prevalence of cross-chain ecosystems, unveils their characteristics, and proposes an effective detector for pinpointing security threats.

关键词： Cross-chain Decentralized Finance Blockchain Transaction analysis

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Cavity in the Loop

Cavity in the Loop

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2024 Workshops of the International Conference for High Performance computing, Networking, Storage and analysis, SC Workshops 2024

作者： Scheunert, David Gehrunger, Jonas Hochberger, Christian Lens, Dieter Klingbeil, Harald Computer Systems Group Technische Universität Darmstadt Darmstadt Germany GSI Helmholtzzentrum für Schwerionenforschung GmbH Darmstadt Germany Accelerator Technology Group Technische Universität Darmstadt Darmstadt Germany

ISBN: (纸本)9798350355543

Particle accelerators are physically and technically complex systems. Their operation requires demanding beam control systems. To support the development of new components in a beam phase control system for a synchrotron, we present a CGRA-based hardware/software environment that is capable of simulating the fundamental beam behaviour, leading to a hardware-in-the-loop setup. We show that this setup is able to emulate the longitudinal phase oscillations of the particle bunches in real-time. © 2024 IEEE.

关键词： CGRA closed-loop control real-time simulation synchrotron LLRF system

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Fully Automated Selfish Mining analysis in Efficient Proof systems Blockchains 24

Fully Automated Selfish Mining Analysis in Efficient Proof S...

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43rd acm SIGACT-SIGOPS Symposium on Principles of Distributed computing, PODC 2024

作者： Chatterjee, Krishnendu Ebrahimzadeh, Amirali Karrabi, Mehrdad Pietrzak, Krzysztof Yeo, Michelle Žikelić, Dorde Ist Austria Austria Sharif University of Technology Iran National University of Singapore Singapore Singapore Management University Singapore

ISBN: (纸本)9798400706684

We study selfish mining attacks in longest-chain blockchains like Bitcoin, but where the proof of work is replaced with efficient proof systems - like proofs of stake or proofs of space - and consider the problem of computing an optimal selfish mining attack which maximizes expected relative revenue of the adversary, thus minimizing the chain quality. To this end, we propose a novel selfish mining attack that aims to maximize this objective and formally model the attack as a Markov decision process (MDP). We then present a formal analysis procedure which computes an ϵ-tight lower bound on the optimal expected relative revenue in the MDP and a strategy that achieves this ϵ-tight lower bound, where ϵ > 0 may be any specified precision. Our analysis is fully automated and provides formal guarantees on the correctness. We evaluate our selfish mining attack and observe that it achieves superior expected relative revenue compared to two considered *** concurrent work [Sarenche FC'24] does an automated analysis on selfish mining in predictable longest-chain blockchains based on efficient proof systems. Predictable means the randomness for the challenges is fixed for many blocks (as used e.g., in Ouroboros), while we consider unpredictable (Bitcoin-like) chains where the challenge is derived from the previous block. © 2024 Association for computing Machinery. All rights reserved.

关键词： Markov processes

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