Annotated Dataset for Anomaly Detection in a Data Center with IoT Sensors

[Abstract] The relative simplicity of IoT networks extends service vulnerabilities and possibilities to different network failures exhibiting system weaknesses. Therefore, having a dataset with a sufficient number of samples, labeled and with a systematic analysis, is essential in order to understand how these networks behave and detect traffic anomalies. This work presents DAD: a complete and labeled IoT dataset containing a reproduction of certain real-world behaviors as seen from the network. To approximate the dataset to a real environment, the data were obtained from a physical data center, with temperature sensors based on NFC smart passive sensor technology. Having carried out different approaches, performing mathematical modeling using time series was finally chosen. The virtual infrastructure necessary for the creation of the dataset is formed by five virtual machines, a MQTT broker and four client nodes, each of them with four sensors of the refrigeration units connected to the internal IoT network. DAD presents a seven day network activity with three types of anomalies: duplication, interception and modification on the MQTT message, spread over 5 days. Finally, a feature description is performed, so it can be used for the application of the various techniques of prediction or automatic classification.This project was funded by the Accreditation, Structuring, and Improvement of Consolidated Research Units and Singular Centers (ED431G/01), funded by Vocational Training of the Xunta de Galicia endowed with EU FEDER funds. This research was partially supported by the Ministry of Science and Innovation, Spain’s National Research and Development Plan, through the PID2019-111388GB-I00 projectXunta de Galicia; ED431G/0

Machine Learning Meets Communication Networks: Current Trends and Future Challenges

The growing network density and unprecedented increase in network traffic, caused by the massively expanding number of connected devices and online services, require intelligent network operations. Machine Learning (ML) has been applied in this regard in different types of networks and networking technologies to meet the requirements of future communicating devices and services. In this article, we provide a detailed account of current research on the application of ML in communication networks and shed light on future research challenges. Research on the application of ML in communication networks is described in: i) the three layers, i.e., physical, access, and network layers; and ii) novel computing and networking concepts such as Multi-access Edge Computing (MEC), Software Defined Networking (SDN), Network Functions Virtualization (NFV), and a brief overview of ML-based network security. Important future research challenges are identified and presented to help stir further research in key areas in this direction

Guidelines for secure cloud-based personal health records

Traditionally, health records have been stored in paper folders at the physician’s consulting rooms – or at the patient’s home. Some people stored the health records of their family members, so as to keep a running history of all the medical procedures they went through, and what medications they were given by different physicians at different stages of their lives. Technology has introduced better and safer ways of storing these records, namely, through the use of Personal Health Records (PHRs). With time, different types of PHRs have emerged, i.e. local, remote server-based, and hybrid PHRs. Web-based PHRs fall under the remote server-based PHRs; and recently, a new market in storing PHRs has emerged. Cloud computing has become a trend in storing PHRs in a more accessible and efficient manner. Despite its many benefits, cloud computing has many privacy and security concerns. As a result, the adoption rate of cloud services is not yet very high. A qualitative and exploratory research design approach was followed in this study, in order to reach the objective of proposing guidelines that could assist PHR providers in selecting a secure Cloud Service Provider (CSP) to store their customers’ health data. The research methods that were used include a literature review, systematic literature review, qualitative content analysis, reasoning, argumentation and elite interviews. A systematic literature review and qualitative content analysis were conducted to examine those risks in the cloud environment that could have a negative impact on the secure storing of PHRs. PHRs must satisfy certain dimensions, in order for them to be meaningful for use. While these were highlighted in the research, it also emerged that certain risks affect the PHR dimensions directly, thus threatening the meaningfulness and usability of cloud-based PHRs. The literature review revealed that specific control measures can be adopted to mitigate the identified risks. These control measures form part of the material used in this study to identify the guidelines for secure cloud-based PHRs. The guidelines were formulated through the use of reasoning and argumentation. After the guidelines were formulated, elite interviews were conducted, in order to validate and finalize the main research output: i.e. guidelines. The results of this study may alert PHR providers to the risks that exist in the cloud environment; so that they can make informed decisions when choosing a CSP for storing their customers’ health data

The First 25 Years of the Bled eConference: Themes and Impacts

The Bled eConference is the longest-running themed conference associated with the Information Systems discipline. The focus throughout its first quarter-century has been the application of electronic tools, migrating progressively from Electronic Data Interchange (EDI) via Inter-Organisational Systems (IOS) and eCommerce to encompass all aspects of the use of networking facilities in industry and government, and more recently by individuals, groups and society as a whole. This paper reports on an examination of the conference titles and of the titles and abstracts of the 773 refereed papers published in the Proceedings since 1995. This identified a long and strong focus on categories of electronic business and corporate perspectives, which has broadened in recent years to encompass the democratic, the social and the personal. The conference\u27s extend well beyond the papers and their thousands of citations and tens of thousands of downloads. Other impacts have included innovative forms of support for the development of large numbers of graduate students, and the many international research collaborations that have been conceived and developed in a beautiful lake-side setting in Slovenia

GVSU Undergraduate and Graduate Catalog, 2012-2013

Grand Valley State University 2012-2013 undergraduate and/or graduate course catalog published annually to provide students with information and guidance for enrollment.https://scholarworks.gvsu.edu/course_catalogs/1087/thumbnail.jp

XXI Workshop de Investigadores en Ciencias de la Computación - WICC 2019: libro de actas

Trabajos presentados en el XXI Workshop de Investigadores en Ciencias de la Computación (WICC), celebrado en la provincia de San Juan los días 25 y 26 de abril 2019, organizado por la Red de Universidades con Carreras en Informática (RedUNCI) y la Facultad de Ciencias Exactas, Físicas y Naturales de la Universidad Nacional de San Juan.Red de Universidades con Carreras en Informátic

XXI Workshop de Investigadores en Ciencias de la Computación - WICC 2019: libro de actas

Trabajos presentados en el XXI Workshop de Investigadores en Ciencias de la Computación (WICC), celebrado en la provincia de San Juan los días 25 y 26 de abril 2019, organizado por la Red de Universidades con Carreras en Informática (RedUNCI) y la Facultad de Ciencias Exactas, Físicas y Naturales de la Universidad Nacional de San Juan.Red de Universidades con Carreras en Informátic