ACM Computing Surveys最新文献

How to Improve Video Analytics with Action Recognition: A Survey 如何通过动作识别改进视频分析？一项调查

IF 23.8 1区计算机科学

ACM Computing Surveys Pub Date : 2024-08-08 DOI: 10.1145/3679011

Gayathri T, Mamatha Hr

引用次数: 0

When Federated Learning Meets Privacy-Preserving Computation 当联合学习遇上隐私保护计算

IF 23.8 1区计算机科学

ACM Computing Surveys Pub Date : 2024-07-22 DOI: 10.1145/3679013

Jingxue Chen, Hang Yan, Zhiyuan Liu, Min Zhang, Hu Xiong, Shui Yu

{"title":"When Federated Learning Meets Privacy-Preserving Computation","authors":"Jingxue Chen, Hang Yan, Zhiyuan Liu, Min Zhang, Hu Xiong, Shui Yu","doi":"10.1145/3679013","DOIUrl":"https://doi.org/10.1145/3679013","url":null,"abstract":"Nowadays, with the development of artificial intelligence (AI), privacy issues attract wide attention from society and individuals. It is desirable to make the data available but invisible, i.e., to realize data analysis and calculation without disclosing the data to unauthorized entities. Federated learning (FL) has emerged as a promising privacy-preserving computation method for AI. However, new privacy issues have arisen in FL-based application because various inference attacks can still infer relevant information about the raw data from local models or gradients. This will directly lead to the privacy disclosure. Therefore, it is critical to resist these attacks to achieve complete privacy-preserving computation. In light of the overwhelming variety and a multitude of privacy-preserving computation protocols, we survey these protocols from a series of perspectives to supply better comprehension for researchers and scholars. Concretely, the classification of attacks is discussed including four kinds of inference attacks as well as malicious server and poisoning attack. Besides, this paper systematically captures the state of the art of privacy-preserving computation protocols by analyzing the design rationale, reproducing the experiment of classic schemes, and evaluating all discussed protocols in terms of efficiency and security properties. Finally, this survey identifies a number of interesting future directions.","PeriodicalId":50926,"journal":{"name":"ACM Computing Surveys","volume":null,"pages":null},"PeriodicalIF":23.8,"publicationDate":"2024-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141817556","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A review and benchmark of feature importance methods for neural networks 神经网络特征重要性方法回顾与基准

IF 23.8 1区计算机科学

ACM Computing Surveys Pub Date : 2024-07-19 DOI: 10.1145/3679012

Hannes Mandler, Bernhard Weigand

{"title":"A review and benchmark of feature importance methods for neural networks","authors":"Hannes Mandler, Bernhard Weigand","doi":"10.1145/3679012","DOIUrl":"https://doi.org/10.1145/3679012","url":null,"abstract":"\u0000 Feature attribution methods (AMs) are a simple means to provide explanations for the predictions of black-box models like neural networks. Due to their conceptual differences, the numerous different methods, however, yield ambiguous explanations. While this allows for obtaining different insights into the model, it also complicates the decision which method to adopt. This paper, therefore, summarizes the current state of the art regarding AMs, which includes the requirements and desiderata of the methods themselves as well as the properties of their explanations. Based on a survey of existing methods, a representative subset consisting of the\u0000 δ\u0000 -sensitivity index, permutation feature importance, variance-based feature importance in artificial neural networks and DeepSHAP, is described in greater detail and, for the first time, benchmarked in a regression context. Specifically for this purpose, a new verification strategy for model-specific AMs is proposed. As expected, the explanations’ agreement with the intuition and among each other clearly depends on the AMs’ properties. This has two implications: First, careful reasoning about the selection of an AM is required. Secondly, it is recommended to apply multiple AMs and combine their insights in order to reduce the model’s opacity even further.\u0000","PeriodicalId":50926,"journal":{"name":"ACM Computing Surveys","volume":null,"pages":null},"PeriodicalIF":23.8,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141823933","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Enabling Technologies and Techniques for Floor Identification 楼层识别的使能技术和工艺

IF 23.8 1区计算机科学

ACM Computing Surveys Pub Date : 2024-07-17 DOI: 10.1145/3678878

Imran Ashraf, Y. B. Zikria, Sahil Garg, Soojung Hur, Yongwan Park, Mohsen Guizani

{"title":"Enabling Technologies and Techniques for Floor Identification","authors":"Imran Ashraf, Y. B. Zikria, Sahil Garg, Soojung Hur, Yongwan Park, Mohsen Guizani","doi":"10.1145/3678878","DOIUrl":"https://doi.org/10.1145/3678878","url":null,"abstract":"Location information has initiated a multitude of applications such as location-based services, health care, emergency response and rescue operations, and assets tracking. A plethora of techniques and technologies have been presented to ensure enhanced location accuracy, both horizontal and vertical. Despite many surveys covering horizontal localization technologies, the literature lacks a comprehensive survey incorporating up-to-data vertical localization approaches. This paper provides a detailed survey of different vertical localization techniques such as path loss models, time of arrival, received signal strength, reference signal received power, and fingerprinting utilized by WiFi, radio frequency identification (RFID), global system for mobile communications (GSM), long term evolution (LTE), barometer, inertial measurement unit (IMU) sensors, and geomagnetic field. The paper primarily aims at human localization in indoor environments using smartphones in essence. Besides the localization accuracy, the presented approaches are evaluated in terms of cost, infrastructure dependence, deployment complexity, and sensitivity. We highlight the pros and cons of these approaches and outline future research directions to enhance the accuracy to meet the future needs of floor identification standards set by the Federal Communications Commission.","PeriodicalId":50926,"journal":{"name":"ACM Computing Surveys","volume":null,"pages":null},"PeriodicalIF":23.8,"publicationDate":"2024-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141831472","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Comprehensive Analysis of Explainable AI for Malware Hunting 全面分析用于恶意软件猎杀的可解释人工智能

IF 23.8 1区计算机科学

ACM Computing Surveys Pub Date : 2024-07-11 DOI: 10.1145/3677374

Mohd Saqib, Samaneh Mahdavifar, Benjamin C. M. Fung, P. Charland

{"title":"A Comprehensive Analysis of Explainable AI for Malware Hunting","authors":"Mohd Saqib, Samaneh Mahdavifar, Benjamin C. M. Fung, P. Charland","doi":"10.1145/3677374","DOIUrl":"https://doi.org/10.1145/3677374","url":null,"abstract":"In the past decade, the number of malware variants has increased rapidly. Many researchers have proposed to detect malware using intelligent techniques, such as Machine Learning (ML) and Deep Learning (DL), which have high accuracy and precision. These methods, however, suffer from being opaque in the decision-making process. Therefore, we need Artificial Intelligence (AI)-based models to be explainable, interpretable, and transparent to be reliable and trustworthy. In this survey, we reviewed articles related to Explainable AI (XAI) and their application to the significant scope of malware detection. The article encompasses a comprehensive examination of various XAI algorithms employed in malware analysis. Moreover, we have addressed the characteristics, challenges, and requirements in malware analysis that cannot be accommodated by standard XAI methods. We discussed that even though Explainable Malware Detection (EMD) models provide explainability, they make an AI-based model more vulnerable to adversarial attacks. We also propose a framework that assigns a level of explainability to each XAI malware analysis model, based on the security features involved in each method. In summary, the proposed project focuses on combining XAI and malware analysis to apply XAI models for scrutinizing the opaque nature of AI systems and their applications to malware analysis.","PeriodicalId":50926,"journal":{"name":"ACM Computing Surveys","volume":null,"pages":null},"PeriodicalIF":23.8,"publicationDate":"2024-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141656095","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Comprehensive Survey on Biclustering-based Collaborative Filtering 基于双聚类的协同过滤综合调查

IF 16.6 1区计算机科学

ACM Computing Surveys Pub Date : 2024-06-22 DOI: 10.1145/3674723

Miguel G. Silva, Sara C. Madeira, Rui Henriques

{"title":"A Comprehensive Survey on Biclustering-based Collaborative Filtering","authors":"Miguel G. Silva, Sara C. Madeira, Rui Henriques","doi":"10.1145/3674723","DOIUrl":"https://doi.org/10.1145/3674723","url":null,"abstract":"Collaborative Filtering (CF) is achieving a plateau of high popularity. Still, recommendation success is challenged by the diversity of user preferences, structural sparsity of user-item ratings, and inherent subjectivity of rating scales. The increasing user base and item dimensionality of e-commerce and e-entertainment platforms creates opportunities, while further raising generalization and scalability needs. Moved by the need to answer these challenges, user-based and item-based clustering approaches for CF became pervasive. However, classic clustering approaches assess user (item) rating similarity across all items (users), neglecting the rich diversity of item and user profiles. Instead, as preferences are generally simultaneously correlated on subsets of users and items, biclustering approaches provide a natural alternative, being successfully applied to CF for nearly two decades and synergistically integrated with emerging deep learning CF stances. Notwithstanding, biclustering-based CF principles are dispersed, causing state-of-the-art approaches to show accentuated behavioral differences. This work offers a structured view on how biclustering aspects impact recommendation success, coverage, and efficiency. To this end, we introduce a taxonomy to categorize contributions in this field and comprehensively survey state-of-the-art biclustering approaches to CF, highlighting their limitations and potentialities.","PeriodicalId":50926,"journal":{"name":"ACM Computing Surveys","volume":null,"pages":null},"PeriodicalIF":16.6,"publicationDate":"2024-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141439849","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Object-Centric Learning with Capsule Networks: A Survey 利用胶囊网络进行以对象为中心的学习：调查

IF 16.6 1区计算机科学

ACM Computing Surveys Pub Date : 2024-06-21 DOI: 10.1145/3674500

Fabio De Sousa Ribeiro, Kevin Duarte, Miles Everett, Georgios Leontidis, Mubarak Shah

{"title":"Object-Centric Learning with Capsule Networks: A Survey","authors":"Fabio De Sousa Ribeiro, Kevin Duarte, Miles Everett, Georgios Leontidis, Mubarak Shah","doi":"10.1145/3674500","DOIUrl":"https://doi.org/10.1145/3674500","url":null,"abstract":"Capsule networks emerged as a promising alternative to convolutional neural networks for learning object-centric representations. The idea is to explicitly model part-whole hierarchies by using groups of neurons called capsules to encode visual entities, then learn the relationships between these entities dynamically from data. However, a major hurdle for capsule network research has been the lack of a reliable point of reference for understanding their foundational ideas and motivations. This survey provides a comprehensive and critical overview of capsule networks which aims to serve as a main point of reference going forward. To that end, we introduce the fundamental concepts and motivations behind capsule networks, such as equivariant inference. We then cover various technical advances in capsule routing algorithms as well as alternative geometric and generative formulations. We provide a detailed explanation of how capsule networks relate to the attention mechanism in Transformers and uncover non-trivial conceptual similarities between them in the context of object-centric representation learning. We also review the extensive applications of capsule networks in computer vision, video and motion, graph representation learning, natural language processing, medical imaging, and many others. To conclude, we provide an in-depth discussion highlighting promising directions for future work.","PeriodicalId":50926,"journal":{"name":"ACM Computing Surveys","volume":null,"pages":null},"PeriodicalIF":16.6,"publicationDate":"2024-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141435748","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A survey of 3D Space Path-Planning Methods and Algorithms 三维空间路径规划方法和算法概览

IF 16.6 1区计算机科学

ACM Computing Surveys Pub Date : 2024-06-20 DOI: 10.1145/3673896

Hakimeh mazaheri, salman goli, ali nourollah

{"title":"A survey of 3D Space Path-Planning Methods and Algorithms","authors":"Hakimeh mazaheri, salman goli, ali nourollah","doi":"10.1145/3673896","DOIUrl":"https://doi.org/10.1145/3673896","url":null,"abstract":"Due to their agility, cost-effectiveness, and high maneuverability, Unmanned Aerial Vehicles (UAVs) have attracted considerable attention from researchers and investors alike. Path planning is one of the practical subsets of motion planning for UAVs. It prevents collisions and ensures complete coverage of an area. This study provides a structured review of applicable algorithms and coverage path planning solutions in Three-Dimensional (3D) space, presenting state-of-the-art technologies related to heuristic decomposition approaches for UAVs and the forefront challenges. Additionally, it introduces a comprehensive and novel classification of practical methods and representational techniques for path-planning algorithms. This depends on environmental characteristics and optimal parameters in the real world. The first category presents a classification of semi-accurate decomposition approaches as the most practical decomposition method, along with the data structure of these practices, categorized by phases. The second category illustrates path-planning processes based on symbolic techniques in 3D space. Additionally, it provides a critical analysis of crucial influential approaches based on their importance in path quality and researchers' attention, highlighting their limitations and research gaps. Furthermore, it will provide the most pertinent recommendations for future work for researchers. The studies demonstrate an apparent inclination among experimenters towards using the semi-accurate cellular decomposition approach to improve 3D path planning.","PeriodicalId":50926,"journal":{"name":"ACM Computing Surveys","volume":null,"pages":null},"PeriodicalIF":16.6,"publicationDate":"2024-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141430377","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

AI-Based Affective Music Generation Systems: A Review of Methods and Challenges 基于人工智能的情感音乐生成系统：方法与挑战综述

IF 16.6 1区计算机科学

ACM Computing Surveys Pub Date : 2024-06-17 DOI: 10.1145/3672554

Adyasha Dash, Kathleen Agres

{"title":"AI-Based Affective Music Generation Systems: A Review of Methods and Challenges","authors":"Adyasha Dash, Kathleen Agres","doi":"10.1145/3672554","DOIUrl":"https://doi.org/10.1145/3672554","url":null,"abstract":"Music is a powerful medium for altering the emotional state of the listener. In recent years, with significant advancements in computing capabilities, artificial intelligence-based (AI-based) approaches have become popular for creating affective music generation (AMG) systems. Entertainment, healthcare, and sensor-integrated interactive system design are a few of the areas in which AI-based affective music generation (AI-AMG) systems may have a significant impact. Given the surge of interest in this topic, this article aims to provide a comprehensive review of controllable AI-AMG systems. The main building blocks of an AI-AMG system are discussed, and existing systems are formally categorized based on the core algorithm used for music generation. In addition, this article discusses the main musical features employed to compose affective music, along with the respective AI-based approaches used for tailoring them. Lastly, the main challenges and open questions in this field, as well as their potential solutions, are presented to guide future research. We hope that this review will be useful for readers seeking to understand the state-of-the-art in AI-AMG systems, and gain an overview of the methods used for developing them, thereby helping them explore this field in the future.","PeriodicalId":50926,"journal":{"name":"ACM Computing Surveys","volume":null,"pages":null},"PeriodicalIF":16.6,"publicationDate":"2024-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141333730","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Toward a Privacy-Preserving Face Recognition System: A Survey of Leakages and Solutions 实现保护隐私的人脸识别系统：泄漏与解决方案调查

IF 16.6 1区计算机科学

ACM Computing Surveys Pub Date : 2024-06-17 DOI: 10.1145/3673224

Lamyanba Laishram, Muhammad Shaheryar, Jong Taek Lee, Soon Ki Jung

{"title":"Toward a Privacy-Preserving Face Recognition System: A Survey of Leakages and Solutions","authors":"Lamyanba Laishram, Muhammad Shaheryar, Jong Taek Lee, Soon Ki Jung","doi":"10.1145/3673224","DOIUrl":"https://doi.org/10.1145/3673224","url":null,"abstract":"Abstract Recent advancements in face recognition (FR) technology in surveillance systems make it possible to monitor a person as they move around. FR gathers a lot of information depending on the quantity and data sources. The most severe privacy concern with FR technology is its use to identify people in real-time public monitoring applications or via an aggregation of datasets without their consent. Due to the importance of private data leakage in the FR environment, academia and business have given it a lot of attention, leading to the creation of several research initiatives meant to solve the corresponding challenges. As a result, this study aims to look at privacy-preserving face recognition (PPFR) methods. We propose a detailed and systematic study of the PPFR based on our suggested six-level framework. Along with all the levels, more emphasis is given to the processing of face images as it is more crucial for FR technology. We explore the privacy leakage issues and offer an up-to-date and thorough summary of current research trends in the FR system from six perspectives. We also encourage additional research initiatives in this promising area for further investigation.","PeriodicalId":50926,"journal":{"name":"ACM Computing Surveys","volume":null,"pages":null},"PeriodicalIF":16.6,"publicationDate":"2024-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141333700","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0