IoTsafe, Decoupling Security from Applications for a Safer IoT

The use of robust security solutions is a must for the Internet of Things (IoT) devices and their applications: regulators in different countries are creating frameworks for certifying those devices with an acceptable security level. However, even for already certified devices, security protocols have to be updated when a breach is found or a certain version becomes obsolete. Many approaches for securing IoT applications are nowadays based on the integration of a security layer [e.g., using transport layer security, (TLS)], but this may result in difficulties when upgrading the security algorithms, as the whole application has to be updated. This fact may shorten the life of IoT devices. As a way to overcome these difficulties, this paper presents IoTsafe, a novel approach relying on secure socket shell (SSH), a feasible alternative to secure communications in IoT applications based on hypertext transfer protocol (HTTP and HTTP/2). In order to illustrate its advantages, a comparison between the traditional approach (HTTP with TLS) and our scheme (HTTP with SSH) is performed over low-power wireless personal area networks (6loWPAN) through 802.15.4 interfaces. The results show that the proposed approach not only provides a more robust and easy-To-update solution, but it also brings an improvement to the overall performance in terms of goodput and energy consumption. Core server stress tests are also presented, and the server performance is also analyzed in terms of RAM consumption and escalation strategies

Optimum parameter machine learning classification and prediction of Internet of Things (IoT) malwares using static malware analysis techniques

Application of machine learning in the field of malware analysis is not a new concept, there have been lots of researches done on the classification of malware in android and windows environments. However, when it comes to malware analysis in the internet of things (IoT), it still requires work to be done. IoT was not designed to keeping security/privacy under consideration. Therefore, this area is full of research challenges. This study seeks to evaluate important machine learning classifiers like Support Vector Machines, Neural Network, Random Forest, Decision Trees, Naive Bayes, Bayesian Network, etc. and proposes a framework to utilize static feature extraction and selection processes highlight issues like over-fitting and generalization of classifiers to get an optimized algorithm with better performance. For background study, we used systematic literature review to find out research gaps in IoT, presented malware as a big challenge for IoT and the reasons for applying malware analysis targeting IoT devices and finally perform classification on malware dataset. The classification process used was applied on three different datasets containing file header, program header and section headers as features. Preliminary results show the accuracy of over 90% on file header, program header, and section headers. The scope of this document just discusses these results as initial results and still require some issues to be addressed which may effect on the performance measures

loTsafe: Método y sistema de comunicaciones seguras para ecosistemas loT

La presente tesis se desarrolla en el sector de las telecomunicaciones y está relacionada particularmente con el campo de la Ingeniería Telemática. De forma más específica, el trabajo persigue diseñar y validar una tecnología de red mejorada de comunicación segura que pueda constituirse como alternativa a las existentes actualmente en determinados escenarios. El objetivo primario de esta red es desacoplar la seguridad de las aplicaciones de los dispositivos IoT a partir de la definición de contextos de seguridad, y facilitar las comunicaciones entre procesos remotos de forma cuasi-transparente. Estos contextos se configuran a partir de la separación de privilegios de entornos de tipo Portable Operating System Interface (POSIX), junto con marcado y filtrado de paquetes locales Internet Protocol (IP). Esta configuración se puede implementar fácilmente aprovechando el protocolo Secure Socket Shell (SSH) y tomando ciertas ideas de Multi Protocol Label Switching (MPLS), pero también de conmutación de circuitos. El campo inmediato de aplicación abarca las infraestructuras y ecosistemas del Internet de las Cosas (IoT) que cuenten con dispositivos POSIX con capacidad para soportar SSH, algo bastante factible en una mayoría de los entornos IoT. Los principales beneficios de esta solución persiguen acortar los tiempos de desarrollo, facilitar la conectividad y simplificar el mantenimiento y las actualizaciones de seguridad. <br /