Network traffic analysis for threats detection in the Internet of Things

As the prevalence of the Internet of Things (IoT) continues to increase, cyber criminals are quick to exploit the security gaps that many devices are inherently designed with. Users cannot be expected to tackle this threat alone, and many current solutions available for network monitoring are simply not accessible or can be difficult to implement for the average user, which is a gap that needs to be addressed. This article presents an effective signature-based solution to monitor, analyze, and detect potentially malicious traffic for IoT ecosystems in the typical home network environment by utilizing passive network sniffing techniques and a cloud application to monitor anomalous activity. The proposed solution focuses on two attack and propagation vectors leveraged by the infamous Mirai botnet, namely DNS and Telnet. Experimental evaluation demonstrates the proposed solution can detect 98.35 percent of malicious DNS traffic and 99.33 percent of Telnet traffic for an overall detection accuracy of 98.84 percent

Outdoor performance of a thin-film gallium-arsenide photovoltaic module

We deployed a 855 cm2 thin-film, single-junction gallium arsenide (GaAs) photovoltaic (PV) module outdoors. Due to its fundamentally different cell technology compared to silicon (Si), the module responds differently to outdoor conditions. On average during the test, the GaAs module produced more power when its temperature was higher. We show that its maximum-power temperature coefficient, while actually negative, is several times smaller in magnitude than that of a Si module used for comparison. The positive correlation of power with temperature in GaAs is due to temperature-correlated changes in the incident spectrum. We show that a simple correction based on precipitable water vapor (PWV) brings the photocurrent temperature coefficient into agreement with that measured by other methods and predicted by theory. The low operating temperature and small temperature coefficient of GaAs give it an energy production advantage in warm weather

A Service-Oriented Approach for Sensing in the Internet of Things: Intelligent Transportation Systems and Privacy Use Cases

This paper presents a Sensing-as-a-Service run-time Service Oriented Architecture (SOA), called 3SOA, for the development of Internet of Things (IoT) applications. 3SOA aims to allow interoperability among various IoT platforms and support service-oriented modelling at high levels of abstraction where fundamental SOA theories and techniques are fully integrated into a practical software engineering approach. 3SOA abstracts the dependencies of the middleware programming model from the application logic. This abstraction allows the development efforts to focus on writing the application logic independently from hardware platforms, middleware, and languages in which applications are programmed. To achieve this result, IoT objects are treated as independent entities that may interact with each other using a well-defined message exchange sequence. Each object is defined by the services it provides and the coordination protocol it supports. Objects are then able to coordinate their resources to address the global objectives of the system. To practically validate our proposals, we demonstrate an intelligent transportation system and data privacy functional prototypes as proof of concepts. The use cases show that 3SOA and the presented abstraction language allow the amalgamation of macroprogramming and node-centric programming to develop real-time and efficient applications over IoT

Network Traffic Analysis for Threats Detection in the Internet of Things

As the prevalence of the Internet of Things (IoT) continues to increase, cyber criminals are quick to exploit the security gaps that many devices are inherently designed with. Whilst users can not be expected to tackle this threat alone, many current solutions available for network monitoring are simply not accessible or can be difficult to implement for the average user and is a gap that needs to be addressed. This paper presents an effective signature-based solution to monitor, analyse and detect potentially malicious traffic for IoT ecosystems in the typical home network environment by utilising passive network sniffing techniques and a cloud-application to monitor anomalous activity. The proposed solution focuses on two attack and propagation vectors leveraged by the infamous Mirai botnet, namely DNS and Telnet. Experimental evaluation demonstrates the proposed solution can detect 98.35% of malicious DNS traffic and 99.33% of Telnet traffic respectively; for an overall detection accuracy of 98.84%

Flexible Dye-Sensitized Solar Cell Based on Vertical ZnO Nanowire Arrays

Flexible dye-sensitized solar cells are fabricated using vertically aligned ZnO nanowire arrays that are transferred onto ITO-coated poly(ethylene terephthalate) substrates using a simple peel-off process. The solar cells demonstrate an energy conversion efficiency of 0.44% with good bending tolerance. This technique paves a new route for building large-scale cost-effective flexible photovoltaic and optoelectronic devices