Catálogo de publicaciones - revistas

<jats:p>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 primarily focusing on electrocardiogram (ECG) have demonstrated remarkable success; however, the degree of exploration with other cardiac signals is still limited. To this end, we discuss the challenges in various cardiac domains and propose future prospectives for developing effective heart biometrics systems in real-world applications.</jats:p>

<jats:p>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 able to receive useful information even in the presence of superimposed signals from different transmitters. We survey the growing number of protocols that exploit synchronous transmissions for higher robustness and efficiency as well as unprecedented functionality and versatility compared to conventional designs. The illustration of protocols based on synchronous transmissions is cast in a conceptional framework we establish, with the goal of highlighting differences and similarities among the proposed solutions. We conclude this article with a discussion on open questions and challenges in this research field.</jats:p>

<jats:p>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, the tools used to benchmark their performance must be accurate and useful in measuring different evaluation parameters. There are dozens of controller proposals for general and specialized networks in the literature. However, there is a very limited comprehensive quantitative analysis for them. In this article, we present a comprehensive qualitative comparison of different SDN controllers, along with a quantitative analysis of their performance in different network scenarios. We categorize and classify 34 controllers and present a qualitative comparison. We also present a comparative analysis of controllers for specialized networks such as the Internet of Things, blockchain networks, vehicular networks, and wireless sensor networks. We also discuss in-depth capabilities of benchmarking tools and provide a comparative analysis of their capabilities. This work uses three benchmarking tools to compare 9 controllers and presents a detailed analysis of their performance, along with discussion on performance of specialized network controllers.</jats:p>

<jats:p> One of the most critical tasks for improving data quality and increasing the reliability of data analytics is <jats:italic>Entity Resolution</jats:italic> (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 one of the Big Data characteristics simultaneously (i.e., Volume and Velocity with Variety). We present the basic concepts, processing steps, and execution strategies that have been proposed by database, semantic Web, and machine learning communities in order to cope with the loose <jats:italic>structuredness</jats:italic> , extreme <jats:italic>diversity</jats:italic> , high <jats:italic>speed,</jats:italic> and large <jats:italic>scale</jats:italic> of entity descriptions used by real-world applications. We provide an end-to-end view of ER workflows for Big Data, critically review the pros and cons of existing methods, and conclude with the main open research directions. </jats:p>

<jats:p>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 are responsible for slower growth of IoT in recent years. For this reason, this article presents a systematic and comprehensive survey on IoT Big Data (IoTBD) with the aim to identify the uncharted challenges for IoTBD. This article analyzes the state-of-the-art academic works in IoT and big data management across various domains and proposes a taxonomy for IoTBD management. Then, the survey explores the IoT portfolio of major cloud vendors and provides a classification of vendor services for the integration of IoT and IoTBD on their cloud platforms. After that, the survey identifies the IoTBD challenges in terms of 13 V’s challenges and envisions IoTBD as “Big Data 2.0.” Then the survey provides comprehensive analysis of recent works that address IoTBD challenges by highlighting their strengths and weaknesses to assess the recent trends and future research directions. Finally, the survey concludes with discussion on open research issues for IoTBD.</jats:p>

<jats:p>With the constantly growing number of reviews and other sentiment-bearing texts on the Web, the demand for automatic sentiment analysis algorithms continues to expand. Aspect-based sentiment classification (ABSC) allows for the automatic extraction of highly fine-grained sentiment information from text documents or sentences. In this survey, the rapidly evolving state of the research on ABSC is reviewed. A novel taxonomy is proposed that categorizes the ABSC models into three major categories: knowledge-based, machine learning, and hybrid models. This taxonomy is accompanied with summarizing overviews of the reported model performances, and both technical and intuitive explanations of the various ABSC models. State-of-the-art ABSC models are discussed, such as models based on the transformer model, and hybrid deep learning models that incorporate knowledge bases. Additionally, various techniques for representing the model inputs and evaluating the model outputs are reviewed. Furthermore, trends in the research on ABSC are identified and a discussion is provided on the ways in which the field of ABSC can be advanced in the future.</jats:p>

<jats:p>In 2006, Geoffrey Hinton proposed the concept of training “Deep Neural Networks (DNNs)” and an improved model training method to break the bottleneck of neural network development. More recently, the introduction of AlphaGo in 2016 demonstrated the powerful learning ability of deep learning and its enormous potential. Deep learning has been increasingly used to develop state-of-the-art software engineering (SE) research tools due to its ability to boost performance for various SE tasks. There are many factors, e.g., deep learning model selection, internal structure differences, and model optimization techniques, that may have an impact on the performance of DNNs applied in SE. Few works to date focus on summarizing, classifying, and analyzing the application of deep learning techniques in SE. To fill this gap, we performed a survey to analyze the relevant studies published since 2006. We first provide an example to illustrate how deep learning techniques are used in SE. We then conduct a background analysis (BA) of primary studies and present four research questions to describe the trend of DNNs used in SE (BA), summarize and classify different deep learning techniques (RQ1), analyze the data processing including data collection, data classification, data pre-processing, and data representation (RQ2). In RQ3, we depicted a range of key research topics using DNNs and investigated the relationships between DL-based model adoption and multiple factors (i.e., DL architectures, task types, problem types, and data types). We also summarized commonly used datasets for different SE tasks. In RQ4, we summarized the widely used optimization algorithms and provided important evaluation metrics for different problem types, including regression, classification, recommendation, and generation. Based on our findings, we present a set of current challenges remaining to be investigated and outline a proposed research road map highlighting key opportunities for future work.</jats:p>

<jats:p>A blockchain is a distributed system that achieves strong security guarantees in storing, managing, and processing data. All blockchains achieve a common goal: building a decentralized system that provides a trustworthy service in an untrustworthy environment. A blockchain builds a Byzantine fault-tolerant system where decentralized nodes run a protocol to reach an agreement on the common system state. In this article, we focus on the research of BFT protocols. In particular, we categorize BFT protocols according to both the system models and workflow. We seek to answer a few important questions: How has the research in BFT evolved in the past four decades, especially with the rise of blockchains? What are the driven needs for BFT research in the future?</jats:p>

<jats:p>Graph neural networks (GNNs) have recently grown in popularity in the field of artificial intelligence (AI) due to their unique ability to ingest relatively unstructured data types as input data. Although some elements of the GNN architecture are conceptually similar in operation to traditional neural networks (and neural network variants), other elements represent a departure from traditional deep learning techniques. This tutorial exposes the power and novelty of GNNs to AI practitioners by collating and presenting details regarding the motivations, concepts, mathematics, and applications of the most common and performant variants of GNNs. Importantly, we present this tutorial concisely, alongside practical examples, thus providing a practical and accessible tutorial on the topic of GNNs.</jats:p>

<jats:p> Oblivious transfer (OT) protocol is an essential tool in cryptography that provides a wide range of applications like secure multi-party computation, private information retrieval, private set intersection, contract signing, and privacy-preserving location-based services. The OT protocol has different variants such as one-out-of-2, one-out-of- <jats:italic>n</jats:italic> , <jats:italic>k</jats:italic> -out-of- <jats:italic>n</jats:italic> , and OT extension. In the OT (one-out-of-2, one-out-of- <jats:italic>n</jats:italic> , and OT extension) protocol, the sender has a set of messages, whereas the receiver has a key. The receiver sends that key to the sender in a secure way; the sender cannot get any information about the received key. The sender encrypts every message by operating on every message using the received key and sends all the encrypted messages to the receiver. The receiver is able to extract only the required message using his key. However, in the <jats:italic>k</jats:italic> -out-of- <jats:italic>n</jats:italic> OT protocol, the receiver sends a set of <jats:italic>k</jats:italic> keys to the sender, and in replay, the sender sends all the encrypted messages. The receiver uses his keys and extracts the required messages, but it cannot gain any information about the messages that it has not requested. Generally, the OT protocol requires high communication and computation cost if we transfer millions of oblivious messages. The OT extension protocol provides a solution for this, where the receiver transfers a set of keys to the sender by executing a few numbers of OT protocols. Then, the sender encrypts all the messages using cheap symmetric key cryptography with the help of a received set of keys and transfer millions of oblivious messages to the receiver. In this work, we present different variants of OT protocols such as one-out-of-2, one-out-of- <jats:italic>n</jats:italic> , <jats:italic>k</jats:italic> -out-of- <jats:italic>n</jats:italic> , and OT extension. Furthermore, we cover various aspects of theoretical security guarantees such as semi-honest and malicious adversaries, universally composable, used techniques, computation, and communication efficiency aspects. From the analysis, we found that the semi-honest adversary-based OT protocols required low communication and computation costs as compared to malicious adversary-based OT protocols. </jats:p>