Task scheduling is a critical issue in distributed computing environments like cloud and fog. The objective is to provide an optimal distribution of tasks among the resources. Several research initiatives to use metaheuristic techniques for finding near-optimal solutions to task scheduling problems are under way. This study presents a comprehensive taxonomic review and analysis of recent metaheuristic scheduling techniques using exhaustive evaluation criteria in the cloud and fog environment. A taxonomy of metaheuristic scheduling algorithms is presented. Besides, we have considered an extensive list of scheduling objectives along with their associated metrics. Rigorous evaluation of existing literature is performed, and limitations highlighted. We have also focused on hybrid algorithms as they tend to improve scheduling performance. We believe that this work will encourage researchers to conduct further research for removing the limitations in existing studies.
{"title":"Towards Metaheuristic Scheduling Techniques in Cloud and Fog: An Extensive Taxonomic Review","authors":"R. Singh, L. Awasthi, Geeta Sikka","doi":"10.1145/3494520","DOIUrl":"https://doi.org/10.1145/3494520","url":null,"abstract":"Task scheduling is a critical issue in distributed computing environments like cloud and fog. The objective is to provide an optimal distribution of tasks among the resources. Several research initiatives to use metaheuristic techniques for finding near-optimal solutions to task scheduling problems are under way. This study presents a comprehensive taxonomic review and analysis of recent metaheuristic scheduling techniques using exhaustive evaluation criteria in the cloud and fog environment. A taxonomy of metaheuristic scheduling algorithms is presented. Besides, we have considered an extensive list of scheduling objectives along with their associated metrics. Rigorous evaluation of existing literature is performed, and limitations highlighted. We have also focused on hybrid algorithms as they tend to improve scheduling performance. We believe that this work will encourage researchers to conduct further research for removing the limitations in existing studies.","PeriodicalId":7000,"journal":{"name":"ACM Computing Surveys (CSUR)","volume":"5 1","pages":"1 - 43"},"PeriodicalIF":0.0,"publicationDate":"2022-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82464223","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Fuzz testing (fuzzing) has witnessed its prosperity in detecting security flaws recently. It generates a large number of test cases and monitors the executions for defects. Fuzzing has detected thousands of bugs and vulnerabilities in various applications. Although effective, there lacks systematic analysis of gaps faced by fuzzing. As a technique of defect detection, fuzzing is required to narrow down the gaps between the entire input space and the defect space. Without limitation on the generated inputs, the input space is infinite. However, defects are sparse in an application, which indicates that the defect space is much smaller than the entire input space. Besides, because fuzzing generates numerous test cases to repeatedly examine targets, it requires fuzzing to perform in an automatic manner. Due to the complexity of applications and defects, it is challenging to automatize the execution of diverse applications. In this article, we systematically review and analyze the gaps as well as their solutions, considering both breadth and depth. This survey can be a roadmap for both beginners and advanced developers to better understand fuzzing.
{"title":"Fuzzing: A Survey for Roadmap","authors":"Xiaogang Zhu, Sheng Wen, S. Çamtepe, Yang Xiang","doi":"10.1145/3512345","DOIUrl":"https://doi.org/10.1145/3512345","url":null,"abstract":"Fuzz testing (fuzzing) has witnessed its prosperity in detecting security flaws recently. It generates a large number of test cases and monitors the executions for defects. Fuzzing has detected thousands of bugs and vulnerabilities in various applications. Although effective, there lacks systematic analysis of gaps faced by fuzzing. As a technique of defect detection, fuzzing is required to narrow down the gaps between the entire input space and the defect space. Without limitation on the generated inputs, the input space is infinite. However, defects are sparse in an application, which indicates that the defect space is much smaller than the entire input space. Besides, because fuzzing generates numerous test cases to repeatedly examine targets, it requires fuzzing to perform in an automatic manner. Due to the complexity of applications and defects, it is challenging to automatize the execution of diverse applications. In this article, we systematically review and analyze the gaps as well as their solutions, considering both breadth and depth. This survey can be a roadmap for both beginners and advanced developers to better understand fuzzing.","PeriodicalId":7000,"journal":{"name":"ACM Computing Surveys (CSUR)","volume":"38 1","pages":"1 - 36"},"PeriodicalIF":0.0,"publicationDate":"2022-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79028163","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Hasini Witharana, Yangdi Lyu, Subodha Charles, P. Mishra
Hardware verification of modern electronic systems has been identified as a major bottleneck due to the increasing complexity and time-to-market constraints. One of the major objectives in hardware verification is to drastically reduce the validation and debug time without sacrificing the design quality. Assertion-based verification is a promising avenue for efficient hardware validation and debug. In this article, we provide a comprehensive survey of recent progress in assertion-based hardware verification. Specifically, we outline how to define assertions using temporal logic to specify expected behaviors in different abstraction levels. Next, we describe state-of-the art approaches for automated generation of assertions. We also discuss test generation techniques for activating assertions to ensure that the generated assertions are valid. Finally, we present both pre-silicon and post-silicon assertion-based validation approaches that utilize simulation, formal methods as well as hybrid techniques. We conclude with a discussion on utilizing assertions for verifying both functional and non-functional requirements.
{"title":"A Survey on Assertion-based Hardware Verification","authors":"Hasini Witharana, Yangdi Lyu, Subodha Charles, P. Mishra","doi":"10.1145/3510578","DOIUrl":"https://doi.org/10.1145/3510578","url":null,"abstract":"Hardware verification of modern electronic systems has been identified as a major bottleneck due to the increasing complexity and time-to-market constraints. One of the major objectives in hardware verification is to drastically reduce the validation and debug time without sacrificing the design quality. Assertion-based verification is a promising avenue for efficient hardware validation and debug. In this article, we provide a comprehensive survey of recent progress in assertion-based hardware verification. Specifically, we outline how to define assertions using temporal logic to specify expected behaviors in different abstraction levels. Next, we describe state-of-the art approaches for automated generation of assertions. We also discuss test generation techniques for activating assertions to ensure that the generated assertions are valid. Finally, we present both pre-silicon and post-silicon assertion-based validation approaches that utilize simulation, formal methods as well as hybrid techniques. We conclude with a discussion on utilizing assertions for verifying both functional and non-functional requirements.","PeriodicalId":7000,"journal":{"name":"ACM Computing Surveys (CSUR)","volume":"6 1","pages":"1 - 33"},"PeriodicalIF":0.0,"publicationDate":"2022-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81609699","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
H. Korala, Dimitrios Georgakopoulos, P. Jayaraman, Ali Yavari
This article surveys existing techniques for meeting the time-bound requirements of time-sensitive applications in the Internet of Things (IoT). To provide the foundation for identifying and classifying relevant techniques, we present three sample time-sensitive IoT applications and their time-bound requirements, describe the main computation and network resources in IoT that can be used to process such applications, and identify the main challenges in meeting their time-bound requirements. Based on these, the article presents a comprehensive literature review of existing techniques and tools that can help meet application-specific time-bound requirements in IoT. The article also includes a gap analysis in existing research outcomes and proposes research directions for bridging the remaining research gaps in supporting time-sensitive IoT applications.
{"title":"A Survey of Techniques for Fulfilling the Time-Bound Requirements of Time-Sensitive IoT Applications","authors":"H. Korala, Dimitrios Georgakopoulos, P. Jayaraman, Ali Yavari","doi":"10.1145/3510411","DOIUrl":"https://doi.org/10.1145/3510411","url":null,"abstract":"This article surveys existing techniques for meeting the time-bound requirements of time-sensitive applications in the Internet of Things (IoT). To provide the foundation for identifying and classifying relevant techniques, we present three sample time-sensitive IoT applications and their time-bound requirements, describe the main computation and network resources in IoT that can be used to process such applications, and identify the main challenges in meeting their time-bound requirements. Based on these, the article presents a comprehensive literature review of existing techniques and tools that can help meet application-specific time-bound requirements in IoT. The article also includes a gap analysis in existing research outcomes and proposes research directions for bridging the remaining research gaps in supporting time-sensitive IoT applications.","PeriodicalId":7000,"journal":{"name":"ACM Computing Surveys (CSUR)","volume":"4 1","pages":"1 - 36"},"PeriodicalIF":0.0,"publicationDate":"2022-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86398508","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In a dynamic stream there is an assumption that the underlying process generating the stream is non-stationary and that concepts within the stream will drift and change as the stream progresses. Concepts learned by a classification model are prone to change and non-adaptive models are likely to deteriorate and become ineffective over time. The challenge of recognising and reacting to change in a stream is compounded by the scarcity of labels problem. This refers to the very realistic situation in which the true class label of an incoming point is not immediately available (or might never be available) or in situations where manually annotating data points are prohibitively expensive. In a high-velocity stream, it is perhaps impossible to manually label every incoming point and pursue a fully supervised approach. In this article, we formally describe the types of change, which can occur in a data-stream and then catalogue the methods for dealing with change when there is limited access to labels. We present an overview of the most influential ideas in the field along with recent advancements and we highlight trends, research gaps, and future research directions.
{"title":"Scarcity of Labels in Non-Stationary Data Streams: A Survey","authors":"Conor Fahy, Shengxiang Yang, Mario Gongora","doi":"10.1145/3494832","DOIUrl":"https://doi.org/10.1145/3494832","url":null,"abstract":"In a dynamic stream there is an assumption that the underlying process generating the stream is non-stationary and that concepts within the stream will drift and change as the stream progresses. Concepts learned by a classification model are prone to change and non-adaptive models are likely to deteriorate and become ineffective over time. The challenge of recognising and reacting to change in a stream is compounded by the scarcity of labels problem. This refers to the very realistic situation in which the true class label of an incoming point is not immediately available (or might never be available) or in situations where manually annotating data points are prohibitively expensive. In a high-velocity stream, it is perhaps impossible to manually label every incoming point and pursue a fully supervised approach. In this article, we formally describe the types of change, which can occur in a data-stream and then catalogue the methods for dealing with change when there is limited access to labels. We present an overview of the most influential ideas in the field along with recent advancements and we highlight trends, research gaps, and future research directions.","PeriodicalId":7000,"journal":{"name":"ACM Computing Surveys (CSUR)","volume":"2 1","pages":"1 - 39"},"PeriodicalIF":0.0,"publicationDate":"2022-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75891789","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Portfolio optimization can be roughly categorized as the mean-variance approach and the exponential growth rate approach based on different theoretical foundations, trading logics, optimization objectives, and methodologies. The former and the latter are often used in long-term and short-term portfolio optimizations, respectively. Although the mean-variance approach could be applied to short-term portfolio optimization, the performance may not be satisfactory (same with the exponential growth rate approach to the long-term portfolio optimization). This survey mainly explores the gaps between these two approaches, and investigates what common ideas or mechanisms are beneficial. Besides, the evaluating framework of this field and some unsolved problems are also discussed.
{"title":"A Survey on Gaps between Mean-Variance Approach and Exponential Growth Rate Approach for Portfolio Optimization","authors":"Zhao-Rong Lai, Haisheng Yang","doi":"10.1145/3485274","DOIUrl":"https://doi.org/10.1145/3485274","url":null,"abstract":"Portfolio optimization can be roughly categorized as the mean-variance approach and the exponential growth rate approach based on different theoretical foundations, trading logics, optimization objectives, and methodologies. The former and the latter are often used in long-term and short-term portfolio optimizations, respectively. Although the mean-variance approach could be applied to short-term portfolio optimization, the performance may not be satisfactory (same with the exponential growth rate approach to the long-term portfolio optimization). This survey mainly explores the gaps between these two approaches, and investigates what common ideas or mechanisms are beneficial. Besides, the evaluating framework of this field and some unsolved problems are also discussed.","PeriodicalId":7000,"journal":{"name":"ACM Computing Surveys (CSUR)","volume":"25 1","pages":"1 - 36"},"PeriodicalIF":0.0,"publicationDate":"2022-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78035904","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Tabinda Sarwar, S. Seifollahi, Jeffrey A Chan, Xiuzhen Zhang, V. Aksakalli, I. Hudson, Karin M. Verspoor, L. Cavedon
The primary objective of implementing Electronic Health Records (EHRs) is to improve the management of patients’ health-related information. However, these records have also been extensively used for the secondary purpose of clinical research and to improve healthcare practice. EHRs provide a rich set of information that includes demographics, medical history, medications, laboratory test results, and diagnosis. Data mining and analytics techniques have extensively exploited EHR information to study patient cohorts for various clinical and research applications, such as phenotype extraction, precision medicine, intervention evaluation, disease prediction, detection, and progression. But the presence of diverse data types and associated characteristics poses many challenges to the use of EHR data. In this article, we provide an overview of information found in EHR systems and their characteristics that could be utilized for secondary applications. We first discuss the different types of data stored in EHRs, followed by the data transformations necessary for data analysis and mining. Later, we discuss the data quality issues and characteristics of the EHRs along with the relevant methods used to address them. Moreover, this survey also highlights the usage of various data types for different applications. Hence, this article can serve as a primer for researchers to understand the use of EHRs for data mining and analytics purposes.
{"title":"The Secondary Use of Electronic Health Records for Data Mining: Data Characteristics and Challenges","authors":"Tabinda Sarwar, S. Seifollahi, Jeffrey A Chan, Xiuzhen Zhang, V. Aksakalli, I. Hudson, Karin M. Verspoor, L. Cavedon","doi":"10.1145/3490234","DOIUrl":"https://doi.org/10.1145/3490234","url":null,"abstract":"The primary objective of implementing Electronic Health Records (EHRs) is to improve the management of patients’ health-related information. However, these records have also been extensively used for the secondary purpose of clinical research and to improve healthcare practice. EHRs provide a rich set of information that includes demographics, medical history, medications, laboratory test results, and diagnosis. Data mining and analytics techniques have extensively exploited EHR information to study patient cohorts for various clinical and research applications, such as phenotype extraction, precision medicine, intervention evaluation, disease prediction, detection, and progression. But the presence of diverse data types and associated characteristics poses many challenges to the use of EHR data. In this article, we provide an overview of information found in EHR systems and their characteristics that could be utilized for secondary applications. We first discuss the different types of data stored in EHRs, followed by the data transformations necessary for data analysis and mining. Later, we discuss the data quality issues and characteristics of the EHRs along with the relevant methods used to address them. Moreover, this survey also highlights the usage of various data types for different applications. Hence, this article can serve as a primer for researchers to understand the use of EHRs for data mining and analytics purposes.","PeriodicalId":7000,"journal":{"name":"ACM Computing Surveys (CSUR)","volume":"8 1","pages":"1 - 40"},"PeriodicalIF":0.0,"publicationDate":"2022-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84047977","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The purpose of a reputation system is to hold the users of a distributed application accountable for their behavior. The reputation of a user is computed as an aggregate of the feedback provided by fellow users in the system. Truthful feedback is clearly a prerequisite for computing a reputation score that accurately represents the behavior of a user. However, it has been observed that users can hesitate in providing truthful feedback because, for example, of fear of retaliation. Privacy-preserving reputation systems enable users to provide feedback in a private and thus uninhibited manner. In this survey, we propose analysis frameworks for privacy-preserving reputation systems. We use these analysis frameworks to review and compare the existing approaches. Emphasis is placed on blockchain-based systems as they are a recent significant development in the area. Blockchain-based privacy-preserving reputation systems have properties, such as trustlessness, transparency, and immutability, which prior systems do not have. Our analysis provides several insights and directions for future research. These include leveraging blockchain to its full potential in order to develop truly trustless systems, to achieve some important security properties, and to include defenses against common attacks that have so far not been addressed by most current systems.
{"title":"Privacy-Preserving Reputation Systems Based on Blockchain and Other Cryptographic Building Blocks: A Survey","authors":"Omar Hasan, L. Brunie, E. Bertino","doi":"10.1145/3490236","DOIUrl":"https://doi.org/10.1145/3490236","url":null,"abstract":"The purpose of a reputation system is to hold the users of a distributed application accountable for their behavior. The reputation of a user is computed as an aggregate of the feedback provided by fellow users in the system. Truthful feedback is clearly a prerequisite for computing a reputation score that accurately represents the behavior of a user. However, it has been observed that users can hesitate in providing truthful feedback because, for example, of fear of retaliation. Privacy-preserving reputation systems enable users to provide feedback in a private and thus uninhibited manner. In this survey, we propose analysis frameworks for privacy-preserving reputation systems. We use these analysis frameworks to review and compare the existing approaches. Emphasis is placed on blockchain-based systems as they are a recent significant development in the area. Blockchain-based privacy-preserving reputation systems have properties, such as trustlessness, transparency, and immutability, which prior systems do not have. Our analysis provides several insights and directions for future research. These include leveraging blockchain to its full potential in order to develop truly trustless systems, to achieve some important security properties, and to include defenses against common attacks that have so far not been addressed by most current systems.","PeriodicalId":7000,"journal":{"name":"ACM Computing Surveys (CSUR)","volume":"9 1","pages":"1 - 37"},"PeriodicalIF":0.0,"publicationDate":"2022-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88388421","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Network traffic workloads are widely utilized in applied research to verify correctness and to measure the impact of novel algorithms, protocols, and network functions. We provide a comprehensive survey of traffic generators referenced by researchers over the last 13 years, providing in-depth classification of the functional behaviors of the most frequently cited generators. These classifications are then used as a critical component of a methodology presented to aid in the selection of generators derived from the workload requirements of future research.
{"title":"Network Traffic Generation: A Survey and Methodology","authors":"O. A. Adeleke, Nicholas Bastin, D. Gurkan","doi":"10.1145/3488375","DOIUrl":"https://doi.org/10.1145/3488375","url":null,"abstract":"Network traffic workloads are widely utilized in applied research to verify correctness and to measure the impact of novel algorithms, protocols, and network functions. We provide a comprehensive survey of traffic generators referenced by researchers over the last 13 years, providing in-depth classification of the functional behaviors of the most frequently cited generators. These classifications are then used as a critical component of a methodology presented to aid in the selection of generators derived from the workload requirements of future research.","PeriodicalId":7000,"journal":{"name":"ACM Computing Surveys (CSUR)","volume":"24 1","pages":"1 - 23"},"PeriodicalIF":0.0,"publicationDate":"2022-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74757345","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Personal information of online social networks (OSNs) is governed by the privacy policies chosen by users besides OSN’s policies. Users make these decisions using privacy mechanisms, but privacy problems and regrets are daily reported. This article reviews current privacy mechanisms and solutions. For this, we analyze all the sub-decisions and elements of online communication involved in the privacy decision-making process. However, the differences in users’ motivations and the disclosure of too sensitive information (among others) can lead to loss of privacy. In this work, we identify requirements such as automation, preference-centered, relationship-based, and multi-party privacy mechanisms, which have been more researched. But also other requirements (recently emerged), such as privacy preservation with risk metrics, explainability, and ephemeral messages. We explore all the advances made in the literature, and we have seen that most of these have been focused on matching the users’ preferences with their decision (which is not appropriate, because users cannot evaluate all of the potential privacy scenarios) instead of assessing privacy risk metrics, adaptation, and explainability. Therefore, we have identified open challenges, such as metrics for assessing privacy risks, explainable solutions for users, ephemeral communication solutions, and the application of these requirements to the multi-party privacy scenario.
OSN (online social networks)的个人信息除了受OSN策略的约束外，还受用户选择的隐私策略的约束。用户使用隐私机制做出这些决定，但隐私问题和遗憾每天都有报告。本文回顾了当前的隐私机制和解决方案。为此，我们分析了隐私决策过程中涉及的所有在线交流子决策和要素。然而，用户动机的差异和过于敏感的信息(以及其他)的披露可能导致隐私的丧失。在这项工作中，我们确定了自动化、以偏好为中心、基于关系和多方隐私机制等需求，这些需求已经得到了更多的研究。但也有其他需求(最近出现的)，例如带有风险度量、可解释性和短暂消息的隐私保护。我们探索了文献中取得的所有进展，我们已经看到，其中大多数都集中在将用户的偏好与他们的决定相匹配(这是不合适的，因为用户无法评估所有潜在的隐私场景)，而不是评估隐私风险指标、适应性和可解释性。因此，我们已经确定了开放的挑战，例如评估隐私风险的指标，用户可解释的解决方案，临时通信解决方案，以及将这些要求应用于多方隐私场景。
{"title":"A Review of Privacy Decision-making Mechanisms in Online Social Networks","authors":"José Alemany, E. Noguera, A. García-Fornes","doi":"10.1145/3494067","DOIUrl":"https://doi.org/10.1145/3494067","url":null,"abstract":"Personal information of online social networks (OSNs) is governed by the privacy policies chosen by users besides OSN’s policies. Users make these decisions using privacy mechanisms, but privacy problems and regrets are daily reported. This article reviews current privacy mechanisms and solutions. For this, we analyze all the sub-decisions and elements of online communication involved in the privacy decision-making process. However, the differences in users’ motivations and the disclosure of too sensitive information (among others) can lead to loss of privacy. In this work, we identify requirements such as automation, preference-centered, relationship-based, and multi-party privacy mechanisms, which have been more researched. But also other requirements (recently emerged), such as privacy preservation with risk metrics, explainability, and ephemeral messages. We explore all the advances made in the literature, and we have seen that most of these have been focused on matching the users’ preferences with their decision (which is not appropriate, because users cannot evaluate all of the potential privacy scenarios) instead of assessing privacy risk metrics, adaptation, and explainability. Therefore, we have identified open challenges, such as metrics for assessing privacy risks, explainable solutions for users, ephemeral communication solutions, and the application of these requirements to the multi-party privacy scenario.","PeriodicalId":7000,"journal":{"name":"ACM Computing Surveys (CSUR)","volume":"3 1","pages":"1 - 32"},"PeriodicalIF":0.0,"publicationDate":"2022-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86170522","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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