Catálogo de publicaciones - revistas

<jats:p>This survey focuses on intrusion detection systems (IDS) that leverage host-based data sources for detecting attacks on enterprise network. The host-based IDS (HIDS) literature is organized by the input data source, presenting targeted sub-surveys of HIDS research leveraging system logs, audit data, Windows Registry, file systems, and program analysis. While system calls are generally included in audit data, several publicly available system call datasets have spawned a flurry of IDS research on this topic, which merits a separate section. To accommodate current researchers, a section giving descriptions of publicly available datasets is included, outlining their characteristics and shortcomings when used for IDS evaluation. Related surveys are organized and described. All sections are accompanied by tables concisely organizing the literature and datasets discussed. Finally, challenges, trends, and broader observations are throughout the survey and in the conclusion along with future directions of IDS research. Overall, this survey was designed to allow easy access to the diverse types of data available on a host for sensing intrusion, the progressions of research using each, and the accessible datasets for prototyping in the area.</jats:p>

<jats:p>Formal methods have provided approaches for investigating software engineering fundamentals and also have high potential to improve current practices in dependability assurance. In this article, we summarise known strengths and weaknesses of formal methods. From the perspective of the assurance of robots and autonomous systems (RAS), we highlight new opportunities for integrated formal methods and identify threats to the adoption of such methods. Based on these opportunities and threats, we develop an agenda for fundamental and empirical research on integrated formal methods and for successful transfer of validated research to RAS assurance. Furthermore, we outline our expectations on useful outcomes of such an agenda.</jats:p>

<jats:p>Document layout analysis (DLA) is a preprocessing step of document understanding systems. It is responsible for detecting and annotating the physical structure of documents. DLA has several important applications such as document retrieval, content categorization, text recognition, and the like. The objective of DLA is to ease the subsequent analysis/recognition phases by identifying the document-homogeneous blocks and by determining their relationships. The DLA pipeline consists of several phases that could vary among DLA methods, depending on the documents’ layouts and final analysis objectives. In this regard, a universal DLA algorithm that fits all types of document-layouts or that satisfies all analysis objectives has not been developed, yet. In this survey paper, we present a critical study of different document layout analysis techniques. The study highlights the motivational reasons for pursuing DLA and discusses comprehensively the different phases of the DLA algorithms based on a general framework that is formed as an outcome of reviewing the research in the field. The DLA framework consists of preprocessing, layout analysis strategies, post-processing, and performance evaluation phases. Overall, the article delivers an essential baseline for pursuing further research in document layout analysis.</jats:p>

<jats:p>This article provides a systematic review of cloud pricing in an interdisciplinary approach. It examines many historical cases of pricing in practice and tracks down multiple roots of pricing in research. The aim is to help both cloud service provider (CSP) and cloud customers to capture the essence of cloud pricing when they need to make a critical decision either to achieve competitive advantages or to manage cloud resource effectively. Currently, the number of available pricing schemes in the cloud market is overwhelming. It is an intricate issue to understand these schemes and associated pricing models clearly due to involving several domains of knowledge, such as cloud technologies, microeconomics, operations research, and value theory. Some earlier studies have introduced this topic unsystematically. Their approaches inevitably lead to much confusion for many cloud decision-makers. To address their weaknesses, we present a comprehensive taxonomy of cloud pricing, which is driven by a framework of three fundamental pricing strategies that are built on nine cloud pricing categories. These categories can be further mapped onto a total of 60 pricing models. Many of the pricing models have been already adopted by CSPs. Others have been widespread across in other industries. We give descriptions of these model categories and highlight both advantages and disadvantages. Moreover, this article offers an extensive survey of many cloud pricing models that were proposed by many researchers during the past decade. Based on the survey, we identify four trends of cloud pricing and the general direction, which is moving from intrinsic value per physical box to extrinsic value per serverless sandbox. We conclude that hyper-converged cloud resources pool supported by cloud orchestration, virtual machine, Open Application Programming Interface, and serverless sandbox will drive the future of cloud pricing.</jats:p>

<jats:p>Sending data to the cloud for analysis was a prominent trend during the past decades, driving cloud computing as a dominant computing paradigm. However, the dramatically increasing number of devices and data traffic in the Internet-of-Things (IoT) era are posing significant burdens on the capacity-limited Internet and uncontrollable service delay. It becomes difficult to meet the delay-sensitive and context-aware service requirements of IoT applications by using cloud computing alone. Facing these challenges, computing paradigms are shifting from the centralized cloud computing to distributed edge computing. Several new computing paradigms, including Transparent Computing, Mobile Edge Computing, Fog Computing, and Cloudlet, have emerged to leverage the distributed resources at network edge to provide timely and context-aware services. By integrating end devices, edge servers, and cloud, they form a hierarchical IoT architecture, i.e., End-Edge-Cloud orchestrated architecture to improve the performance of IoT systems. This article presents a comprehensive survey of these emerging computing paradigms from the perspective of end-edge-cloud orchestration. Specifically, we first introduce and compare the architectures and characteristics of different computing paradigms. Then, a comprehensive survey is presented to discuss state-of-the-art research in terms of computation offloading, caching, security, and privacy. Finally, some potential research directions are envisioned for fostering continuous research efforts.</jats:p>

<jats:p>Random graph (RG) models play a central role in complex networks analysis. They help us to understand, control, and predict phenomena occurring, for instance, in social networks, biological networks, the Internet, and so on.</jats:p> <jats:p>Despite a large number of RG models presented in the literature, there are few concepts underlying them. Instead of trying to classify a wide variety of very dispersed models, we capture and describe concepts they exploit considering preferential attachment, copying principle, hyperbolic geometry, recursively defined structure, edge switching, Monte Carlo sampling, and so on. We analyze RG models, extract their basic principles, and build a taxonomy of concepts they are based on. We also discuss how these concepts are combined in RG models and how they work in typical applications like benchmarks, null models, and data anonymization.</jats:p>

<jats:p>Video description is the automatic generation of natural language sentences that describe the contents of a given video. It has applications in human-robot interaction, helping the visually impaired and video subtitling. The past few years have seen a surge of research in this area due to the unprecedented success of deep learning in computer vision and natural language processing. Numerous methods, datasets, and evaluation metrics have been proposed in the literature, calling the need for a comprehensive survey to focus research efforts in this flourishing new direction. This article fills the gap by surveying the state-of-the-art approaches with a focus on deep learning models; comparing benchmark datasets in terms of their domains, number of classes, and repository size; and identifying the pros and cons of various evaluation metrics, such as SPICE, CIDEr, ROUGE, BLEU, METEOR, and WMD. Classical video description approaches combined subject, object, and verb detection with template-based language models to generate sentences. However, the release of large datasets revealed that these methods cannot cope with the diversity in unconstrained open domain videos. Classical approaches were followed by a very short era of statistical methods that were soon replaced with deep learning, the current state-of-the-art in video description. Our survey shows that despite the fast-paced developments, video description research is still in its infancy due to the following reasons: Analysis of video description models is challenging, because it is difficult to ascertain the contributions towards accuracy or errors of the visual features and the adopted language model in the final description. Existing datasets neither contain adequate visual diversity nor complexity of linguistic structures. Finally, current evaluation metrics fall short of measuring the agreement between machine-generated descriptions with that of humans. We conclude our survey by listing promising future research directions.</jats:p>

<jats:p>The challenges of cloud forensics have been well-documented by both researchers and government agencies (e.g., U.S. National Institute of Standards and Technology), although many of the challenges remain unresolved. In this article, we perform a comprehensive survey of cloud forensic literature published between January 2007 and December 2018, categorized using a five-step forensic investigation process. We also present a taxonomy of existing cloud forensic solutions, with the aim of better informing both the research and practitioner communities, as well as an in-depth discussion of existing conventional digital forensic tools and cloud-specific forensic investigation tools. Based on the findings from the survey, we present a set of design guidelines to inform future cloud forensic investigation processes, and a summary of digital artifacts that can be obtained from different stakeholders in the cloud computing architecture/ecosystem.</jats:p>

<jats:p>Metaprogramming is the process of writing computer programs that treat programs as data, enabling them to analyze or transform existing programs or generate new ones. While the concept of metaprogramming has existed for several decades, activities focusing on metaprogramming have been increasing rapidly over the past few years, with most languages offering some metaprogramming support and the amount of metacode being developed growing exponentially. In this article, we introduce a taxonomy of metaprogramming languages and present a survey of metaprogramming languages and systems based on the taxonomy. Our classification is based on the metaprogramming model adopted by the language, the phase of the metaprogram evaluation, the metaprogram source location, and the relation between the metalanguage and the object language.</jats:p>

<jats:p>As general-purpose processors have hit the power wall and chip fabrication cost escalates alarmingly, coarse-grained reconfigurable architectures (CGRAs) are attracting increasing interest from both academia and industry, because they offer the performance and energy efficiency of hardware with the flexibility of software. However, CGRAs are not yet mature in terms of programmability, productivity, and adaptability. This article reviews the architecture and design of CGRAs thoroughly for the purpose of exploiting their full potential. First, a novel multidimensional taxonomy is proposed. Second, major challenges and the corresponding state-of-the-art techniques are surveyed and analyzed. Finally, the future development is discussed.</jats:p>