COSMOS: Collaborative, Seamless and Adaptive Sentinel for the Internet of Things

The Internet of Things (IoT) became established during the last decade as an emerging technology with considerable potentialities and applicability. Its paradigm of everything connected together penetrated the real world, with smart devices located in several daily appliances. Such intelligent objects are able to communicate autonomously through already existing network infrastructures, thus generating a more concrete integration between real world and computer-based systems. On the downside, the great benefit carried by the IoT paradigm in our life brings simultaneously severe security issues, since the information exchanged among the objects frequently remains unprotected from malicious attackers. The paper at hand proposes COSMOS (Collaborative, Seamless and Adaptive Sentinel for the Internet of Things), a novel sentinel to protect smart environments from cyber threats. Our sentinel shields the IoT devices using multiple defensive rings, resulting in a more accurate and robust protection. Additionally, we discuss the current deployment of the sentinel on a commodity device (i.e., Raspberry Pi). Exhaustive experiments are conducted on the sentinel, demonstrating that it performs meticulously even in heavily stressing conditions. Each defensive layer is tested, reaching a remarkable performance, thus proving the applicability of COSMOS in a distributed and dynamic scenario such as IoT. With the aim of easing the enjoyment of the proposed entinel, we further developed a friendly and ease-to-use COSMOS App, so that end-users can manage sentinel(s) directly using their own devices (e.g., smartphone).

• Autores: Nespoli, Pantaleone; Useche Pelaez, David; Díaz López, Daniel; Gómez Mármol, Felix
• Tipo de recurso: Article of investigation
• Fecha de publicación: 2019
• Institución: Escuela Colombiana de Ingeniería Julio Garavito
• Repositorio: Repositorio Institucional ECI
• Idioma: eng
• OAI Identifier: oai:repositorio.escuelaing.edu.co:001/1436
• Acceso en línea: https://repositorio.escuelaing.edu.co/handle/001/1436; https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6479720/pdf/sensors-19-01492.pdf
• Palabra clave: Internet de las cosas; Aprendizaje automático (Inteligencia artificial); Seguridad informática; Internet of Things; Sentinel for the IoT; Intrusion detection system; Smart home; Machine learning; Malware detection; Threat intelligence
• Rights: openAccess
• License: https://creativecommons.org/licenses/by/4.0/