Proficient Approach for Intrusion Detection using Behaviour Profiling Algorithm and Prevention Using Statistical Model in Cloud Networks

Objectives: The objective of the paper is to discuss the proposed dynamic software model to detect and prevent intrusion in the cloud network. Methods: The Behavior Profiling Algorithm (BPA) has been used to detect the intrusion in cloud network. For finding the intruder in the network the Event Log Entries and the network Unique Identification Address (UIA) has been fetched from the server and then the collected attribute values have been transferred to prevention module.  In the prevention module the dynamic statistical approach model has been used to prevent the network systems and data which are available in the Cloud Network. Findings: For testing the proposed model the 100 cloud network systems were taken and based on the loss of packets (in MB) ranges the samples were classified as 0-100, 101-200, 201-300, 301-400, 401-500, 501-600, 601-700 respectively. The range of data loss is assumed to be an interval of 100 Mbps. It is assumed that the higher the data loss ranges, the more data is lost. The mean, variance, and standard deviation were calculated to verify the data loss ranges. The mean (average) of the data loss in the ranges 0-100 is 060.77 and the mean in the ranges 101-200 is 144.714 data losses, which gradually increases in proportion to the data loss ranges, and in the ranges 601-700 it is 665.769 data losses. From the statistical approach model, the differences between mean and variance indicated that the intruder attacked the files during the data transformation in the network. Therefore, the administrator has to monitor the warning message from the proposed IPS model and get data packet losses in the transformation. If the frequency of data loss is low, the administrator can assume that the data flow is low due to network problems. On the other hand, if the frequency of data loss in the network system is high, he can block the transformation and protect the data file. This paper concludes that the behavioral profiling algorithm combined with a statistical model achieves an efficiency of over 96% in wired networks, over 97.6% in wireless networks, and over 98.7% in cloud networks. Novelty: In the previous paper discussed the approach which has been implemented with 40 nodes and the result of the proposed algorithm produced above 90%, 96% and 98% in the wired, wireless and cloud network respectively. Now, the model has been implemented with 100 nodes the result has been increased. This study concluded that, the efficient algorithm to detect the intrusion is behaviour profiling algorithm, while join with the statistical approach model, it produces efficient result

Estado del arte de los métodos de seguridad de datos aplicados en internet de las cosas

El propósito de esta investigación es crear el estado del arte de técnicas y procesos usados en el ámbito de la ingeniería, utilizando un mapeo sistemático enfocado a los métodos de seguridad de datos aplicados en Internet de las Cosas. El trabajo recopila documentos a partir del 2017 utilizando mapeo sistemático de literatura y una revisión sistemática aplicando el método PRISMA, cumpliendo el rigor metodológico y de la calidad. Obteniendo uno de los métodos más usados como cifrado utilizado en un 52,8% en las empresas, también la monitorización de anomalías y detección de intrusiones, el control de acceso basado en roles, gestión de claves y autenticación de dispositivos y usuarios, además protocolos que se utilizan para establecer la comunicación y la transferencia de información de manera segura entre distintos dispositivos, como MQTT, que es utilizado por el 38.3% para la comunicación de datos en tiempo real, JWT, AMQP, DDS y HTTP, que es utilizado por el 70% de los desarrolladores de IoT, acompañando estos mecanismos con buenas prácticas y ser conscientes de las consecuencias negativas de la mala práctica, garantizando la seguridad de datos en los dispositivos IoT.The purpose of this research is to create the state of the art of techniques and processes used in the field of engineering, using a systematic mapping focused on data security methods applied in the Internet of Things. The work collects documents from 2017 using systematic literature mapping and a systematic review applying the PRISMA method, complying with methodological rigor and quality. Obtaining one of the most used methods as used by 52.8% in companies, also anomaly monitoring and intrusion detection, rolebased access control, key management and device and user authentication, in addition protocols used to establish communication and transfer information securely between different devices, such as MQTT, which is used by 38.3% for real-time data communication, JWT, AMQP, DDS and HTTP, which is used by 70% of IoT developers, accompanying these mechanisms with good practices and being aware of the negative consequences of bad practice, guaranteeing data security in IoT devices

Revisión sistemática de s.o iot agrícolas: un caso práctico en una empresa Florícola de Cotopaxi

At present, agriculture has been productively affected due to different climatic factors, or in turn due to the management of traditional agriculture, considering that the use of technology can help automate cultivation processes. This research is aimed at conducting a systematic review of IoT operating systems through a practical case applied to the "Alexander Greenhouse" in the province of Cotopaxi. For the preparation of this systematic review, the methodology of Bárbara Kitchenham was used, where a total of 165 articles were identified based on the literature on IoToperating systems in the agricultural sector of digital databases: IEEE Xplore, Scopus, Web Science and Google Scholar and after following the review protocol of this methodology, these were reduced to 17 articles. In addition, for the construction of the prototype, two open source IoT operating systems such as FreeRTOS and RIOT, an ESP32 module, a Raspberry Pi 3 microcomputer, humidity and temperature sensors were used to capture the data. Finally, acomparison was made between the FreeRTOS and RIOT operating systems, where FreeRTOS was chosen since it has an independent interface from other applications and, in turn, allows planning execution times and concurrent tasks, in such a way that improved the cultivation process by measuring soil moisture in real time, thus obtaining the satisfaction of greenhouse customers.En la actualidad la agricultura se ha visto afectada productivamente debido a los diferentes factores climáticos, o a su vez por el manejo de la agricultura tradicional considerando que el uso de la tecnología puede ayudar a automatizar los procesos de cultivo. Esta investigación está orientada a realizar una revisión sistemática acerca de los sistemas operativos IoT a través de un caso práctico aplicado al “Invernadero Alexander” de la provincia de Cotopaxi. Para la elaboración de esta revisión sistemática se empleó la metodología de Bárbara Kitchenham, en donde, se identificaron un total de 165 artículos en base a la literatura sobre sistemas operativos IoT en el sector agrícola de las bases de datos digitales: IEEE Xplore, Scopus, Web Science y Google académico y tras seguir el protocolo de revisión de esta metodología, estos se redujeron a 17 artículos. Además, para la construcción del prototipo se emplearon dos sistemas operativos de IoT de código abierto como el FreeRTOS y RIOT, un módulo ESP32, micrordenador Raspberry Pi 3, sensores de humedad y temperatura para la captura de los datos. Finalmente, se realizó una comparación entre los sistemas operativos FreeRTOS y RIOT, en donde, se optó por FreeRTOS ya que cuenta con una interfaz independiente de otras aplicaciones y a su vez permite planificar los tiempos de ejecución y tareas concurrentes, de tal manera, que se mejoró el proceso de cultivo midiendo la humedad del suelo en tiempo real, obteniendo así la satisfacción de los clientes del invernadero