Catálogo de publicaciones - revistas

<jats:p>Blockchain offers an innovative approach to storing information, executing transactions, performing functions, and establishing trust in an open environment. Many consider blockchain as a technology breakthrough for cryptography and cybersecurity, with use cases ranging from globally deployed cryptocurrency systems like Bitcoin, to smart contracts, smart grids over the Internet of Things, and so forth. Although blockchain has received growing interests in both academia and industry in the recent years, the security and privacy of blockchains continue to be at the center of the debate when deploying blockchain in different applications. This article presents a comprehensive overview of the security and privacy of blockchain. To facilitate the discussion, we first introduce the notion of blockchains and its utility in the context of Bitcoin-like online transactions. Then, we describe the basic security properties that are supported as the essential requirements and building blocks for Bitcoin-like cryptocurrency systems, followed by presenting the additional security and privacy properties that are desired in many blockchain applications. Finally, we review the security and privacy techniques for achieving these security properties in blockchain-based systems, including representative consensus algorithms, hash chained storage, mixing protocols, anonymous signatures, non-interactive zero-knowledge proof, and so forth. We conjecture that this survey can help readers to gain an in-depth understanding of the security and privacy of blockchain with respect to concept, attributes, techniques, and systems.</jats:p>

<jats:p>Monitoring of human and social activities is becoming increasingly pervasive in our living environment for public security and safety applications. The recognition of suspicious events is important in both indoor and outdoor environments, such as child-care centers, smart-homes, old-age homes, residential areas, office environments, elevators, and smart cities. Environmental audio scene and sound event recognition are the fundamental tasks involved in many audio surveillance applications. Although numerous approaches have been proposed, robust environmental audio surveillance remains a huge challenge due to various reasons, such as various types of overlapping audio sounds, background noises, and lack of universal and multi-modal datasets. The goal of this article is to review various features of representing audio scenes and sound events and provide appropriate machine learning algorithms for audio surveillance tasks. Benchmark datasets are categorized based on the real-world scenarios of audio surveillance applications. To have a quantitative understanding, some of the state-of-the-art approaches are evaluated based on two benchmark datasets for audio scenes and sound event recognition tasks. Finally, we outline the possible future directions for improving the recognition of environmental audio scenes and sound events.</jats:p>

<jats:p>Indoor localization is essential for healthcare, security, augmented reality gaming, and many other location-based services. There is currently a wealth of relevant literature on indoor localization. This article focuses on recent advances in indoor localization methods that use spatial context to improve the location estimation. Spatial context in the form of maps and spatial models have been used to improve the localization by constraining location estimates in the navigable parts of indoor environments. Landmarks such as doors and corners, which are also one form of spatial context, have proved useful in assisting indoor localization by correcting the localization error. This survey gives a comprehensive review of state-of-the-art indoor localization methods and localization improvement methods using maps, spatial models, and landmarks.</jats:p>

<jats:p>Volunteer Computing is a kind of distributed computing that harnesses the aggregated spare computing resources of volunteer devices. It provides a cheaper and greener alternative computing infrastructure that can complement the dedicated, centralized, and expensive data centres. The aggregated idle computing resources of devices ranging from desktop computers to routers and smart TVs are being utilized to provide the much needed computing infrastructure for compute intensive tasks such as scientific simulations and big data analysis. However, the use of Volunteer Computing is still dominated by scientific applications and only a very small fraction of the potential volunteer nodes are participating. This article provides a comprehensive survey of Volunteer Computing, covering key technical and operational issues such as security, task distribution, resource management, and incentive models. The article also presents a taxonomy of Volunteer Computing systems, together with discussions of the characteristics of specific systems in each category. To harness the full potentials of Volunteer Computing and make it a reliable alternative computing infrastructure for general applications, we need to improve the existing techniques and device new mechanisms. Thus, this article also sheds light on important issues regarding the future research and development of Volunteer Computing systems with the aim of making them a viable alternative computing infrastructure.</jats:p>

<jats:p>Online Social Networks (OSNs) incorporate different forms of interactive communication, including microblogging services, multimedia sharing, business networking, and so on. They allow users to create profiles, connect with friends, and share their daily activities and thoughts. However, this ease of use of OSNs comes with a cost in terms of users’ privacy and security. The big amount of personal data shared in the users’ profiles or correlated from their activities can be stored, processed, and sold for advertisement or statistical purposes. It attracts also malicious users who can collect and exploit the data and target different types of attacks. In this article, we review the state of the art of OSNs existing either in the literature or deployed for use. We focus on the OSN systems that offer, but not exclusively, microblogging services. We analyze and evaluate each system based on a set of characteristics, and we compare them based on their usability and the level of protection of privacy and security they provide. This study is a first step toward understanding the security and privacy controls and measuring their level in an OSN.</jats:p>

<jats:p> Textual deception constitutes a major problem for online security. Many studies have argued that deceptiveness leaves traces in writing style, which could be detected using text classification techniques. By conducting an extensive literature review of existing empirical work, we demonstrate that while certain linguistic features have been indicative of deception in certain corpora, they fail to generalize across divergent semantic domains. We suggest that deceptiveness as such leaves no <jats:italic>content-invariant stylistic trace</jats:italic> , and textual similarity measures provide a superior means of classifying texts as potentially deceptive. Additionally, we discuss forms of deception beyond semantic content, focusing on hiding author identity by <jats:italic>writing style obfuscation</jats:italic> . Surveying the literature on both author identification and obfuscation techniques, we conclude that current style transformation methods fail to achieve reliable obfuscation while simultaneously ensuring semantic faithfulness to the original text. We propose that future work in style transformation should pay particular attention to disallowing semantically drastic changes. </jats:p>

<jats:p>With the high demand for wireless data traffic, WiFi networks have experienced very rapid growth, because they provide high throughput and are easy to deploy. Recently, Channel State Information (CSI) measured by WiFi networks is widely used for different sensing purposes. To get a better understanding of existing WiFi sensing technologies and future WiFi sensing trends, this survey gives a comprehensive review of the signal processing techniques, algorithms, applications, and performance results of WiFi sensing with CSI. Different WiFi sensing algorithms and signal processing techniques have their own advantages and limitations and are suitable for different WiFi sensing applications. The survey groups CSI-based WiFi sensing applications into three categories, detection, recognition, and estimation, depending on whether the outputs are binary/multi-class classifications or numerical values. With the development and deployment of new WiFi technologies, there will be more WiFi sensing opportunities wherein the targets may go beyond from humans to environments, animals, and objects. The survey highlights three challenges for WiFi sensing: robustness and generalization, privacy and security, and coexistence of WiFi sensing and networking. Finally, the survey presents three future WiFi sensing trends, i.e., integrating cross-layer network information, multi-device cooperation, and fusion of different sensors, for enhancing existing WiFi sensing capabilities and enabling new WiFi sensing opportunities.</jats:p>

<jats:p>Motion Capture and whole-body interaction technologies have been experimentally proven to contribute to the enhancement of dance learning and to the investigation of bodily knowledge, innovating at the same time the practice of dance. Designing and implementing a dance interactive learning system with the aim to achieve effective, enjoyable, and meaningful educational experiences is, however, a highly demanding interdisciplinary and complex problem. In this work, we examine the interactive dance training systems that are described in the recent bibliography, proposing a framework of the most important design parameters, which we present along with particular examples of implementations. We discuss the way that the different phases of a common workflow are designed and implemented in these systems, examining aspects such as the visualization of feedback to the learner, the movement qualities involved, the technological approaches used, as well as the general context of use and learning approaches. Our aim is to identify common patterns and areas that require further research and development toward creating more effective and meaningful digital dance learning tools.</jats:p>

<jats:p>Binary rewriting is changing the semantics of a program without having the source code at hand. It is used for diverse purposes, such as emulation (e.g., QEMU), optimization (e.g., DynInst), observation (e.g., Valgrind), and hardening (e.g., Control flow integrity enforcement). This survey gives detailed insight into the development and state-of-the-art in binary rewriting by reviewing 67 publications from 1966 to 2018. Starting from these publications, we provide an in-depth investigation of the challenges and respective solutions to accomplish binary rewriting. Based on our findings, we establish a thorough categorization of binary rewriting approaches with respect to their use-case, applied analysis technique, code-transformation method, and code generation techniques. We contribute a comprehensive mapping between binary rewriting tools, applied techniques, and their domain of application. Our findings emphasize that although much work has been done over the past decades, most of the effort was put into improvements aiming at rewriting general purpose applications but ignoring other challenges like altering throughput-oriented programs or software with real-time requirements, which are often used in the emerging field of the Internet of Things. To the best of our knowledge, our survey is the first comprehensive overview on the complete binary rewriting process.</jats:p>

<jats:p>Among all Internet of Things (IoT) devices, a subset of them are related to users. Leveraging these user-related IoT elements, it is possible to ensure the identity of the user for a period of time, thus avoiding impersonation. This need is known as Continuous Authentication (CA). Since 2009, a plethora of IoT-based CA academic research and industrial contributions have been proposed. We offer a comprehensive overview of 58 research papers regarding the main components of such a CA system. The status of the industry is studied as well, covering 32 market contributions, research projects, and related standards. Lessons learned, challenges, and open issues to foster further research in this area are finally presented.</jats:p>