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  • Cyber-aggression, Cyberbullying, and Cyber-grooming: A Survey and Research Challenges
    ACM Comput. Surv. (IF 7.99) Pub Date : 2021-01-02
    Miljana Mladenović; Vera Ošmjanski; Staša Vujičić Stanković

    Cyber-aggression, cyberbullying, and cyber-grooming are distinctive and similar phenomena that represent the objectionable content appearing on online social media. Timely detection of the objectionable content is very important for its prevention and reduction. This article explores and spotlights diversity of definitions of cyber-aggression, cyberbulling, and cyber-grooming; analyzes current categorization

    更新日期:2021-01-02
  • Relay-based Communications in WBANs: A Comprehensive Survey
    ACM Comput. Surv. (IF 7.99) Pub Date : 2021-01-02
    Avani Vyas; Sujata Pal; Barun Kumar Saha

    Wireless Body Area Networks (WBANs) constitute an emerging technology in the field of health care that makes health monitoring possible from one’s home itself. WBANs open many challenges by placing sensors on/inside human bodies for collecting various health-related information. Unlike traditional Wireless Sensor Networks (WSNs), communication in WBANs suffers from high channel fading and attenuation

    更新日期:2021-01-02
  • Smart Contract Languages: A Multivocal Mapping Study
    ACM Comput. Surv. (IF 7.99) Pub Date : 2021-01-02
    Ángel Jesús Varela-Vaca; Antonia M. Reina Quintero

    Blockchain is a disruptive technology that has attracted the attention of the scientific community and companies, as proven by the exponential growth of publications on this topic in recent years. This growing interest is mainly due to the promise that the use of blockchain enables it to be verified, without including any trusted intermediaries, that the information received from the network is authentic

    更新日期:2021-01-02
  • Location Privacy-preserving Mechanisms in Location-based Services: A Comprehensive Survey
    ACM Comput. Surv. (IF 7.99) Pub Date : 2021-01-02
    Hongbo Jiang; Jie Li; Ping Zhao; Fanzi Zeng; Zhu Xiao; Arun Iyengar

    Location-based services (LBSs) provide enhanced functionality and convenience of ubiquitous computing, but they open up new vulnerabilities that can be utilized to violate the users’ privacy. The leakage of private location data in the LBS context has drawn significant attention from academics and industry due to its importance, leading to numerous research efforts aiming to confront the related challenges

    更新日期:2021-01-02
  • Challenges in Firmware Re-Hosting, Emulation, and Analysis
    ACM Comput. Surv. (IF 7.99) Pub Date : 2021-01-02
    Christopher Wright; William A. Moeglein; Saurabh Bagchi; Milind Kulkarni; Abraham A. Clements

    System emulation and firmware re-hosting have become popular techniques to answer various security and performance related questions, such as determining whether a firmware contain security vulnerabilities or meet timing requirements when run on a specific hardware platform. While this motivation for emulation and binary analysis has previously been explored and reported, starting to either work or

    更新日期:2021-01-02
  • From Server-Based to Client-Based Machine Learning: A Comprehensive Survey
    ACM Comput. Surv. (IF 7.99) Pub Date : 2021-01-02
    Renjie Gu; Chaoyue Niu; Fan Wu; Guihai Chen; Chun Hu; Chengfei Lyu; Zhihua Wu

    In recent years, mobile devices have gained increasing development with stronger computation capability and larger storage space. Some of the computation-intensive machine learning tasks can now be run on mobile devices. To exploit the resources available on mobile devices and preserve personal privacy, the concept of client-based machine learning has been proposed. It leverages the users’ local hardware

    更新日期:2021-01-02
  • The Creation and Detection of Deepfakes: A Survey
    ACM Comput. Surv. (IF 7.99) Pub Date : 2021-01-02
    Yisroel Mirsky; Wenke Lee

    Generative deep learning algorithms have progressed to a point where it is difficult to tell the difference between what is real and what is fake. In 2018, it was discovered how easy it is to use this technology for unethical and malicious applications, such as the spread of misinformation, impersonation of political leaders, and the defamation of innocent individuals. Since then, these “deepfakes”

    更新日期:2021-01-02
  • Relative Worst-order Analysis: A Survey
    ACM Comput. Surv. (IF 7.99) Pub Date : 2021-01-02
    Joan Boyar; Lene M. Favrholdt; Kim S. Larsen

    The standard measure for the quality of online algorithms is the competitive ratio. This measure is generally applicable, and for some problems it works well, but for others it fails to distinguish between algorithms that have very different performance. Thus, ever since its introduction, researchers have worked on improving the measure, defining variants, or defining measures based on other concepts

    更新日期:2021-01-02
  • Lattice-based Key-sharing Schemes: A Survey
    ACM Comput. Surv. (IF 7.99) Pub Date : 2021-01-02
    Prasanna Ravi; James Howe; Anupam Chattopadhyay; Shivam Bhasin

    Public-key cryptography is an indispensable component used in almost all of our present-day digital infrastructure. However, most if not all of it is predominantly built upon hardness guarantees of number theoretic problems that can be broken by large-scale quantum computers in the future. Sensing the imminent threat from continued advances in quantum computing, NIST has recently initiated a global-level

    更新日期:2021-01-02
  • Potential Deep Learning Solutions to Persistent and Emerging Big Data Challenges—A Practitioners’ Cookbook
    ACM Comput. Surv. (IF 7.99) Pub Date : 2021-01-02
    Behroz Mirza; Tahir Q. Syed; Behraj Khan; Yameen Malik

    The phenomenon of Big Data continues to present moving targets for the scientific and technological state-of-the-art. This work demonstrates that the solution space of these challenges has expanded with deep learning now moving beyond traditional applications in computer vision and natural language processing to diverse and core machine learning tasks such as learning with streaming and non-iid-data

    更新日期:2021-01-02
  • Security in Brain-Computer Interfaces: State-of-the-Art, Opportunities, and Future Challenges
    ACM Comput. Surv. (IF 7.99) Pub Date : 2021-01-02
    Sergio López Bernal; Alberto Huertas Celdrán; Gregorio Martínez Pérez; Michael Taynnan Barros; Sasitharan Balasubramaniam

    Brain-Computer Interfaces (BCIs) have significantly improved the patients’ quality of life by restoring damaged hearing, sight, and movement capabilities. After evolving their application scenarios, the current trend of BCI is to enable new innovative brain-to-brain and brain-to-the-Internet communication paradigms. This technological advancement generates opportunities for attackers, since users’

    更新日期:2021-01-02
  • A Systematic Review of Multimedia Tools for Cybersecurity Awareness and Education
    ACM Comput. Surv. (IF 7.99) Pub Date : 2021-01-02
    Leah Zhang-Kennedy; Sonia Chiasson

    We conduct a comprehensive review covering academic publications and industry products relating to tools for cybersecurity awareness and education aimed at non-expert end-users developed in the past 20 years. Through our search criteria, we identified 119 tools that we cataloged into five broad media categories. We explore current trends, assess their use of relevant instructional design principles

    更新日期:2021-01-02
  • Networking in Oceans: A Survey
    ACM Comput. Surv. (IF 7.99) Pub Date : 2021-01-02
    Shengming Jiang

    The ocean is a huge saltwater body that is different from terrestrial environments in terms of deployment circumstance, weather conditions, and user distributions. Therefore, it is difficult to apply terrestrial networking technologies directly in oceans. The cost-effectiveness of satellites is still an issue to be addressed to increase their popularity due to their high cost in construction, launching

    更新日期:2021-01-02
  • Key Generation for Internet of Things: A Contemporary Survey
    ACM Comput. Surv. (IF 7.99) Pub Date : 2021-01-02
    Weitao Xu; Junqing Zhang; Shunqi Huang; Chengwen Luo; Wei Li

    Key generation is a promising technique to bootstrap secure communications for the Internet of Things devices that have no prior knowledge between each other. In the past few years, a variety of key generation protocols and systems have been proposed. In this survey, we review and categorise recent key generation systems based on a novel taxonomy. Then, we provide both quantitative and qualitative

    更新日期:2021-01-02
  • In Memoriam Sherif Sakr (1979–2020)
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-12-29
    Albert Y. Zomaya

    No abstract available.

    更新日期:2020-12-30
  • Languages of Games and Play: A Systematic Mapping Study
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-12-29
    Riemer Van Rozen

    Digital games are a powerful means for creating enticing, beautiful, educational, and often highly addictive interactive experiences that impact the lives of billions of players worldwide. We explore what informs the design and construction of good games to learn how to speed-up game development. In particular, we study to what extent languages, notations, patterns, and tools, can offer experts theoretical

    更新日期:2020-12-30
  • Implementations in Machine Ethics: A Survey
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-12-29
    Suzanne Tolmeijer; Markus Kneer; Cristina Sarasua; Markus Christen; Abraham Bernstein

    Increasingly complex and autonomous systems require machine ethics to maximize the benefits and minimize the risks to society arising from the new technology. It is challenging to decide which type of ethical theory to employ and how to implement it effectively. This survey provides a threefold contribution. First, it introduces a trimorphic taxonomy to analyze machine ethics implementations with respect

    更新日期:2020-12-30
  • A Survey on Heart Biometrics
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-12-06
    Aditya Singh Rathore; Zhengxiong Li; Weijin Zhu; Zhanpeng Jin; Wenyao Xu

    In recent years, biometrics (e.g., fingerprint or face recognition) has replaced traditional passwords and PINs as a widely used method for user authentication, particularly in personal or mobile devices. Differing from state-of-the-art biometrics, heart biometrics offer the advantages of liveness detection, which provides strong tolerance to spoofing attacks. To date, several authentication methods

    更新日期:2020-12-07
  • A Survey of Cybersecurity Certification for the Internet of Things
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-12-06
    Sara N. Matheu; José L. Hernández-Ramos; Antonio F. Skarmeta; Gianmarco Baldini

    In recent years, cybersecurity certification is gaining momentum as the baseline to build a structured approach to mitigate cybersecurity risks in the Internet of Things (IoT). This initiative is driven by industry, governmental institutions, and research communities, which have the goal to make IoT more secure for the end-users. In this survey, we analyze the current cybersecurity certification schemes

    更新日期:2020-12-07
  • Smart Home Personal Assistants: A Security and Privacy Review
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-12-06
    Jide S. Edu; Jose M. Such; Guillermo Suarez-Tangil

    Smart Home Personal Assistants (SPA) are an emerging innovation that is changing the means by which home users interact with technology. However, several elements expose these systems to various risks: (i) the open nature of the voice channel they use, (ii) the complexity of their architecture, (iii) the AI features they rely on, and (iv) their use of a wide range of underlying technologies. This article

    更新日期:2020-12-07
  • Energy Diagnosis of Android Applications: A Thematic Taxonomy and Survey
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-12-06
    Marimuthu C.; K. Chandrasekaran; Sridhar Chimalakonda

    The abnormal energy consumption of Android applications is a significant problem faced by developers and users. In recent years, researchers have invested their efforts to develop energy diagnosis tools that pinpoint and fix the energy bugs from source code automatically. These tools use traditional software engineering methods such as program analysis, refactoring, software repair, and bug localization

    更新日期:2020-12-07
  • Patterns and Interactions in Network Security
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-12-06
    Pamela Zave; Jennifer Rexford

    Networks play a central role in cyber-security: networks deliver security attacks, suffer from them, defend against them, and sometimes even cause them. This article is a concise tutorial on the large subject of networks and security, written for all those interested in networking, whether their specialty is security or not. To achieve this goal, we derive our focus and organization from two perspectives

    更新日期:2020-12-07
  • Anomaly Detection in Road Traffic Using Visual Surveillance: A Survey
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-12-06
    K. K. Santhosh; D. P. Dogra; P. P. Roy

    Computer vision has evolved in the last decade as a key technology for numerous applications replacing human supervision. Timely detection of traffic violations and abnormal behavior of pedestrians at public places through computer vision and visual surveillance can be highly effective for maintaining traffic order in cities. However, despite a handful of computer vision–based techniques proposed in

    更新日期:2020-12-07
  • Touch-dynamics based Behavioural Biometrics on Mobile Devices – A Review from a Usability and Performance Perspective
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-12-06
    Elakkiya Ellavarason; Richard Guest; Farzin Deravi; Raul Sanchez-Riello; Barbara Corsetti

    Over the past few years, there has been an exponential increase in the percentage of people owning and using a smart phone. These devices have sensor-rich touchscreens that can capture sensitive biometric features such as keystroke typing and finger-swiping patterns. Touch-dynamics based behavioural biometrics is a time-based assessment of how a user performs a particular touch task on a mobile device

    更新日期:2020-12-07
  • Synchronous Transmissions in Low-Power Wireless: A Survey of Communication Protocols and Network Services
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-12-06
    Marco Zimmerling; Luca Mottola; Silvia Santini

    Low-power wireless communication is a central building block of cyber-physical systems and the Internet of Things. Conventional low-power wireless protocols make avoiding packet collisions a cornerstone design choice. The concept of synchronous transmissions challenges this view. As collisions are not necessarily destructive, under specific circumstances, commodity low-power wireless radios are often

    更新日期:2020-12-07
  • Security and Privacy in IoT Using Machine Learning and Blockchain: Threats and Countermeasures
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-12-06
    Nazar Waheed; Xiangjian He; Muhammad Ikram; Muhammad Usman; Saad Sajid Hashmi; Muhammad Usman

    Security and privacy of users have become significant concerns due to the involvement of the Internet of Things (IoT) devices in numerous applications. Cyber threats are growing at an explosive pace making the existing security and privacy measures inadequate. Hence, everyone on the Internet is a product for hackers. Consequently, Machine Learning (ML) algorithms are used to produce accurate outputs

    更新日期:2020-12-07
  • The Node Vector Distance Problem in Complex Networks
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-12-06
    Michele Coscia; Andres Gomez-Lievano; James Mcnerney; Frank Neffke

    We describe a problem in complex networks we call the Node Vector Distance (NVD) problem, and we survey algorithms currently able to address it. Complex networks are a useful tool to map a non-trivial set of relationships among connected entities, or nodes. An agent—e.g., a disease—can occupy multiple nodes at the same time and can spread through the edges. The node vector distance problem is to estimate

    更新日期:2020-12-07
  • Techniques for Inverted Index Compression
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-12-06
    Giulio Ermanno Pibiri; Rossano Venturini

    The data structure at the core of large-scale search engines is the inverted index, which is essentially a collection of sorted integer sequences called inverted lists. Because of the many documents indexed by such engines and stringent performance requirements imposed by the heavy load of queries, the inverted index stores billions of integers that must be searched efficiently. In this scenario, index

    更新日期:2020-12-07
  • A Survey of Android Malware Detection with Deep Neural Models
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-12-06
    Junyang Qiu; Jun Zhang; Wei Luo; Lei Pan; Surya Nepal; Yang Xiang

    Deep Learning (DL) is a disruptive technology that has changed the landscape of cyber security research. Deep learning models have many advantages over traditional Machine Learning (ML) models, particularly when there is a large amount of data available. Android malware detection or classification qualifies as a big data problem because of the fast booming number of Android malware, the obfuscation

    更新日期:2020-12-07
  • An Overview of End-to-End Entity Resolution for Big Data
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-12-06
    Vassilis Christophides; Vasilis Efthymiou; Themis Palpanas; George Papadakis; Kostas Stefanidis

    One of the most critical tasks for improving data quality and increasing the reliability of data analytics is Entity Resolution (ER), which aims to identify different descriptions that refer to the same real-world entity. Despite several decades of research, ER remains a challenging problem. In this survey, we highlight the novel aspects of resolving Big Data entities when we should satisfy more than

    更新日期:2020-12-07
  • Trust in FPGA-accelerated Cloud Computing
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-12-06
    Furkan Turan; Ingrid Verbauwhede

    Platforms combining Central Processing Systems (CPUs) with Field Programmable Gate Arrays (FPGAs) have become popular, as they promise high performance with energy efficiency. This is the result of the combination of FPGA accelerators tuned to the application, with the CPU providing the programming flexibility. Unfortunately, the security of these new platforms has received little attention: The classic

    更新日期:2020-12-07
  • Using Social Media for Mental Health Surveillance: A Review
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-12-06
    Ruba Skaik; Diana Inkpen

    Data on social media contain a wealth of user information. Big data research of social media data may also support standard surveillance approaches and provide decision-makers with usable information. These data can be analyzed using Natural Language Processing (NLP) and Machine Learning (ML) techniques to detect signs of mental disorders that need attention, such as depression and suicide ideation

    更新日期:2020-12-07
  • A Survey on IoT Big Data: Current Status, 13 V’s Challenges, and Future Directions
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-12-06
    Maggi Bansal; Inderveer Chana; Siobhán Clarke

    Driven by the core technologies, i.e., sensor-based autonomous data acquisition and the cloud-based big data analysis, IoT automates the actuation of data-driven intelligent actions on the connected objects. This automation enables numerous useful real-life use-cases, such as smart transport, smart living, smart cities, and so on. However, recent industry surveys reflect that data-related challenges

    更新日期:2020-12-07
  • SDN Controllers: A Comprehensive Analysis and Performance Evaluation Study
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-12-06
    Liehuang Zhu; Md M. Karim; Kashif Sharif; Chang Xu; Fan Li; Xiaojiang Du; Mohsen Guizani

    Software-defined networks offer flexible and intelligent network operations by splitting a traditional network into a centralized control plane and a programmable data plane. The controller in the control plane is the fundamental element used to manage all operations of the data plane. Hence, the performance and capabilities of the controller itself are essential in achieving optimal performance. Furthermore

    更新日期:2020-12-07
  • Design of Algorithms and Protocols for Underwater Acoustic Wireless Sensor Networks
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-12-06
    Azzedine Boukerche; Peng Sun

    Nowadays, with the recent advances of wireless underwater communication and acoustic sensor devices technology, we are witnessing a surge in the exploration and exploitation of the ocean’s abundant natural resources. Accordingly, to fulfill the requirements of the exploration of the ocean, researchers have focused their work toward the design of methods and algorithms for the underwater acoustic sensor

    更新日期:2020-12-07
  • A Survey on Energy Expenditure Estimation Using Wearable Devices
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-09-28
    Juan A. Álvarez-García; Božidara Cvetković; Mitja Luštrek

    Human Energy Expenditure (EE) is a valuable tool for measuring physical activity and its impact on our body in an objective way. To accurately measure the EE, there are methods such as doubly labeled water and direct and indirect calorimetry, but their cost and practical limitations make them suitable only for research and professional sports. This situation, combined with the proliferation of commercial

    更新日期:2020-09-28
  • Mobility Management in 5G-enabled Vehicular Networks: Models, Protocols, and Classification
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-09-28
    Noura Aljeri; Azzedine Boukerche

    Over the past few years, the next generation of vehicular networks is envisioned to play an essential part in autonomous driving, traffic management, and infotainment applications. The next generation of intelligent vehicular networks enabled by 5G systems will integrate various heterogeneous wireless techniques to enable time-sensitive services with guaranteed quality of service and ultimate bandwidth

    更新日期:2020-09-28
  • Density-based Algorithms for Big Data Clustering Using MapReduce Framework: A Comprehensive Study
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-09-28
    Mariam Khader; Ghazi Al-Naymat

    Clustering is used to extract hidden patterns and similar groups from data. Therefore, clustering as a method of unsupervised learning is a crucial technique for big data analysis owing to the massive number of unlabeled objects involved. Density-based algorithms have attracted research interest, because they help to better understand complex patterns in spatial datasets that contain information about

    更新日期:2020-09-28
  • Vehicle Trajectory Similarity: Models, Methods, and Applications
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-09-28
    Roniel S. De Sousa; Azzedine Boukerche; Antonio A. F. Loureiro

    The increasing availability of vehicular trajectory data is at the core of smart mobility solutions. Such data offer us unprecedented information for the development of trajectory data mining-based applications. An essential task of trajectory analysis is the employment of efficient and accurate methods to compare trajectories. This work presents a systematic survey of vehicular trajectory similarity

    更新日期:2020-09-28
  • Predictive Reliability and Fault Management in Exascale Systems: State of the Art and Perspectives
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-09-28
    Ramon Canal; Carles Hernandez; Rafa Tornero; Alessandro Cilardo; Giuseppe Massari; Federico Reghenzani; William Fornaciari; Marina Zapater; David Atienza; Ariel Oleksiak; Wojciech PiĄtek; Jaume Abella

    Performance and power constraints come together with Complementary Metal Oxide Semiconductor technology scaling in future Exascale systems. Technology scaling makes each individual transistor more prone to faults and, due to the exponential increase in the number of devices per chip, to higher system fault rates. Consequently, High-performance Computing (HPC) systems need to integrate prediction, detection

    更新日期:2020-09-28
  • Quantum Key Distribution: A Networking Perspective
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-09-28
    Miralem Mehic; Marcin Niemiec; Stefan Rass; Jiajun Ma; Momtchil Peev; Alejandro Aguado; Vicente Martin; Stefan Schauer; Andreas Poppe; Christoph Pacher; Miroslav Voznak

    The convergence of quantum cryptography with applications used in everyday life is a topic drawing attention from the industrial and academic worlds. The development of quantum electronics has led to the practical achievement of quantum devices that are already available on the market and waiting for their first application on a broader scale. A major aspect of quantum cryptography is the methodology

    更新日期:2020-09-28
  • Secure Hash Algorithms and the Corresponding FPGA Optimization Techniques
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-09-28
    Zeyad A. Al-Odat; Mazhar Ali; Assad Abbas; Samee U. Khan

    Cryptographic hash functions are widely used primitives with a purpose to ensure the integrity of data. Hash functions are also utilized in conjunction with digital signatures to provide authentication and non-repudiation services. The SHA has been developed over time by the National Institute of Standards and Technology for security, optimal performance, and robustness. The best-known hash standards

    更新日期:2020-09-28
  • A Survey of Quantum Theory Inspired Approaches to Information Retrieval
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-09-28
    Sagar Uprety; Dimitris Gkoumas; Dawei Song

    Since 2004, researchers have been using the mathematical framework of quantum theory in information retrieval (IR). Quantum theory offers a generalized probability and logic framework. Such a framework has been shown to be capable of unifying the representation, ranking, and user cognitive aspects of IR, and helpful in developing more dynamic, adaptive, and context-aware IR systems. Although quantum-inspired

    更新日期:2020-09-28
  • A Survey of Multilingual Neural Machine Translation
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-09-28
    Raj Dabre; Chenhui Chu; Anoop Kunchukuttan

    We present a survey on multilingual neural machine translation (MNMT), which has gained a lot of traction in recent years. MNMT has been useful in improving translation quality as a result of translation knowledge transfer (transfer learning). MNMT is more promising and interesting than its statistical machine translation counterpart, because end-to-end modeling and distributed representations open

    更新日期:2020-09-28
  • A Taxonomy and Survey of Power Models and Power Modeling for Cloud Servers
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-09-28
    Weiwei Lin; Fang Shi; Wentai Wu; Keqin Li; Guangxin Wu; Al-Alas Mohammed

    Due to the increasing demand of cloud resources, the ever-increasing number and scale of cloud data centers make their massive power consumption a prominent issue today. Evidence reveals that the behaviors of cloud servers make the major impact on data centers’ power consumption. Although extensive research can be found in this context, a systematic review of the models and modeling methods for the

    更新日期:2020-09-28
  • Computational Sustainability: A Socio-technical Perspective
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-09-28
    Deya Chatterjee; Shrisha Rao

    This is a consolidated look at computational techniques for sustainability, and their limits and possibilities. Sustainability is already well established as a concern and a topic of study and practice, given the alarming increase of environmental degradation, pollution, and other adverse effects of industrialization and urbanization. Computational sustainability, which focuses on the use of effective

    更新日期:2020-09-28
  • Traffic Efficiency Applications over Downtown Roads: A New Challenge for Intelligent Connected Vehicles
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-09-28
    Maram Bani Younes; Azzedine Boukerche

    Vehicular network technology is frequently used to provide several services and applications for drivers on road networks. The proposed applications in the environment of road networks are classified into three main categories based on their functions: safety, traffic efficiency, and entertainment. The traffic efficiency services are designed to enhance the moving fluency and smoothness of traveling

    更新日期:2020-09-28
  • A Survey of Ontologies for Simultaneous Localization and Mapping in Mobile Robots
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-09-28
    María A. Cornejo-Lupa; Regina P. Ticona-Herrera; Yudith Cardinale; Dennis Barrios-Aranibar

    Autonomous robots are playing important roles in academic, technological, and scientific activities. Thus, their behavior is getting more complex, particularly, in tasks related to mapping an environment and localizing themselves. These tasks comprise the Simultaneous Localization and Mapping (SLAM) problem. Representation of knowledge related to the SLAM problem with a standard, flexible, and well-defined

    更新日期:2020-09-28
  • Unveiling the Mystery of Internet Packet Forwarding: A Survey of Network Path Validation
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-09-28
    Kai Bu; Avery Laird; Yutian Yang; Linfeng Cheng; Jiaqing Luo; Yingjiu Li; Kui Ren

    Validating the network paths taken by packets is critical in constructing a secure Internet architecture. Any feasible solution must both enforce packet forwarding along end-host specified paths and verify whether packets have taken those paths. However, the current Internet supports neither enforcement nor verification. Likely due to the radical changes to the Internet architecture and a long-standing

    更新日期:2020-09-28
  • Predecessor Search
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-09-28
    Gonzalo Navarro; Javiel Rojas-Ledesma

    The predecessor problem is a key component of the fundamental sorting-and-searching core of algorithmic problems. While binary search is the optimal solution in the comparison model, more realistic machine models on integer sets open the door to a rich universe of data structures, algorithms, and lower bounds. In this article, we review the evolution of the solutions to the predecessor problem, focusing

    更新日期:2020-09-28
  • Recommender Systems Leveraging Multimedia Content
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-09-28
    Yashar Deldjoo; Markus Schedl; Paolo Cremonesi; Gabriella Pasi

    Recommender systems have become a popular and effective means to manage the ever-increasing amount of multimedia content available today and to help users discover interesting new items. Today’s recommender systems suggest items of various media types, including audio, text, visual (images), and videos. In fact, scientific research related to the analysis of multimedia content has made possible effective

    更新日期:2020-09-28
  • A Survey on Trust Evaluation Based on Machine Learning
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-09-28
    Jingwen Wang; Xuyang Jing; Zheng Yan; Yulong Fu; Witold Pedrycz; Laurence T. Yang

    Trust evaluation is the process of quantifying trust with attributes that influence trust. It faces a number of severe issues such as lack of essential evaluation data, demand of big data process, request of simple trust relationship expression, and expectation of automation. In order to overcome these problems and intelligently and automatically evaluate trust, machine learning has been applied into

    更新日期:2020-09-28
  • A Survey on Bayesian Deep Learning
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-09-28
    Hao Wang; Dit-Yan Yeung

    A comprehensive artificial intelligence system needs to not only perceive the environment with different “senses” (e.g., seeing and hearing) but also infer the world’s conditional (or even causal) relations and corresponding uncertainty. The past decade has seen major advances in many perception tasks, such as visual object recognition and speech recognition, using deep learning models. For higher-level

    更新日期:2020-09-28
  • A Survey of Fake News: Fundamental Theories, Detection Methods, and Opportunities
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-09-28
    Xinyi Zhou; Reza Zafarani

    The explosive growth in fake news and its erosion to democracy, justice, and public trust has increased the demand for fake news detection and intervention. This survey reviews and evaluates methods that can detect fake news from four perspectives: the false knowledge it carries, its writing style, its propagation patterns, and the credibility of its source. The survey also highlights some potential

    更新日期:2020-09-28
  • Big Data Systems: A Software Engineering Perspective
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-09-28
    Ali Davoudian; Mengchi Liu

    Big Data Systems (BDSs) are an emerging class of scalable software technologies whereby massive amounts of heterogeneous data are gathered from multiple sources, managed, analyzed (in batch, stream or hybrid fashion), and served to end-users and external applications. Such systems pose specific challenges in all phases of software development lifecycle and might become very complex by evolving data

    更新日期:2020-09-28
  • Causality-based Feature Selection: Methods and Evaluations
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-09-28
    Kui Yu; Xianjie Guo; Lin Liu; Jiuyong Li; Hao Wang; Zhaolong Ling; Xindong Wu

    Feature selection is a crucial preprocessing step in data analytics and machine learning. Classical feature selection algorithms select features based on the correlations between predictive features and the class variable and do not attempt to capture causal relationships between them. It has been shown that the knowledge about the causal relationships between features and the class variable has potential

    更新日期:2020-09-28
  • Comparative Analysis and Framework Evaluating Web Single Sign-on Systems
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-09-28
    Furkan Alaca; Paul C. Van Oorschot

    We perform a comprehensive analysis and comparison of 14 web single sign-on (SSO) systems proposed and/or deployed over the past decade, including federated identity and credential/password management schemes. We identify common design properties and use them to develop a taxonomy for SSO schemes, highlighting the associated tradeoffs in benefits (positive attributes) offered. We develop a framework

    更新日期:2020-09-28
  • A Survey of Multitier Programming
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-09-26
    Pascal Weisenburger; Johannes Wirth; Guido Salvaneschi

    Multitier programming deals with developing the components that pertain to different tiers in the system (e.g., client and server), mixing them in the same compilation unit. In this paradigm, the code for different tiers is then either generated at run time or it results from the compiler splitting the codebase into components that belong to different tiers based on user annotations, static analysis

    更新日期:2020-09-26
  • Homomorphic Encryption for Machine Learning in Medicine and Bioinformatics
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-08-25
    Alexander Wood; Kayvan Najarian; Delaram Kahrobaei

    Machine learning and statistical techniques are powerful tools for analyzing large amounts of medical and genomic data. On the other hand, ethical concerns and privacy regulations prevent free sharing of this data. Encryption techniques such as fully homomorphic encryption (FHE) enable evaluation over encrypted data. Using FHE, machine learning models such as deep learning, decision trees, and Naive

    更新日期:2020-08-26
  • Machine Learning Methods for Data Association in Multi-Object Tracking
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-08-20
    Patrick Emami; Panos M. Pardalos; Lily Elefteriadou; Sanjay Ranka

    Data association is a key step within the multi-object tracking pipeline that is notoriously challenging due to its combinatorial nature. A popular and general way to formulate data association is as the NP-hard multi-dimensional assignment problem. Over the past few years, data-driven approaches to assignment have become increasingly prevalent as these techniques have started to mature. We focus this

    更新日期:2020-08-20
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