Biblio

This work introduces a new microcomputing node with long-term resistant data security, based on asymmetric and symmetric encryption combined with the modern and established scripting language Python. The presented microcomputing node integrates a MicroPython runtime environment to address a wide audience of application engineers as user base instead of a selected group of embedded engineers, who have deep knowledge in programming IoT devices using C/C++. It combines its scripting capabilities with security features of modern smartcards and secure cellular networking based on 4G.

The present work describes a remote environment monitoring system based on the paradigms of mesh networks and opportunistic networks, whereby a sensor node can explore “con-nectivity windows” to transmit information that will eventually reach another network participants. We discuss the threats to the system's security and propose security mechanisms for the system ensuring the integrity and availability of monitoring information, something identified as critical to its proper operation.

Wireless sensor network (WSN) is a wireless self-organizing multi-hop network that can sense and collect the information of the monitored environment through a certain number of sensor nodes which deployed in a certain area and transmit the collected information to the client. Due to the limited power and data capacity stored by the micro sensor, it is weak in communication with other nodes, data storage and calculation, and is very vulnerable to attack and harm to the entire network. The Sybil attack is a classic example. Sybil attack refers to the attack in which malicious nodes forge multiple node identities to participate in network operation. Malicious attackers can forge multiple node identities to participate in data forwarding. So that the data obtained by the end user without any use value. In this paper, we propose a three-tier detection scheme for the Sybil node in the severe environment. Every sensor node will determine whether they are Sybil nodes through the first-level and second-level high-energy node detection. Finally, the base station determines whether the Sybil node detected by the first two stages is true Sybil node. The simulation results show that our proposed scheme significantly improves network lifetime, and effectively improves the accuracy of Sybil node detection.

Network lifetime and energy consumption of sensor nodes have an inversely proportional relationship. Thus, it is important to ensure source location privacy (SLP) routing schemes are energy-efficient. This work performs an experimental evaluation of some existing routing schemes and proposes a new angle-based routing algorithm to modify the schemes. The dynamic route creation process of the modified schemes is characterized by processes which include determination of route and banned regions and computation of control angle and lead factor parameters. Results of the analysis show that the modified schemes are effective at obfuscating the adversaries to provide strong SLP protection. Furthermore, the modified schemes consume relatively lower energy and guarantee longer network lifetime.

In order to be more environmentally friendly, a lot of parts and aspects of life become electrified to reduce the usage of fossil fuels. This can be seen in the increased number of electrical vehicles in everyday life. This of course only makes a positive impact on the environment, if the electricity is produced environmentally friendly and comes from renewable sources. But when the green electrical power is produced, it still needs to be transported to where it's needed, which is not necessarily near the production site. In China, one of the ways to do this transport is to use High Voltage Direct Current (HVDC) technology. This of course means, that the current has to be converted to DC before being transported to the end user. That implies that the converter stations are of great importance for the grid security. Therefore, a precise monitoring of the stations is necessary. Ideally, this could be accomplished with wireless sensor nodes with an autarkic energy supply. A role in this energy supply could be played by a thermoelectrical generator (TEG). But to assess the power generated in the specific environment, a simulation would be highly desirable, to evaluate the power gained from the temperature difference in the converter station. This paper proposes a method to simulate the generated power by combining a model for the generator with a Computational Fluid Dynamics (CFD) model converter.

Trust management is a promising alternative solution to different complex security algorithms for Underwater Wireless Sensor Networks (UWSN) applications due to its several resource constraint behaviour. In this work, we have proposed a trust management model to improve location privacy of the UWSN. Adaptive Neuro Fuzzy Inference System (ANFIS) has been exploited to evaluate trustworthiness of a sensor node. Also Markov Decision Process (MDP) has been considered. At each state of the MDP, a sensor node evaluates trust behaviour of forwarding node utilizing the FIS learning rules and selects a trusted node. Simulation has been conducted in MATLAB and simulation results show that the detection accuracy of trustworthiness is 91.2% which is greater than Knowledge Discovery and Data Mining (KDD) 99 intrusion detection based dataset. So, in our model 91.2% trustworthiness is necessary to be a trusted node otherwise it will be treated as a malicious or compromised node. Our proposed model can successfully eliminate the possibility of occurring any compromised or malicious node in the network.

Radio-frequency identification (RFID) are becoming a part of our everyday life with a wide range of applications such as labeling products and supply chain management and etc. These smart and tiny devices have extremely constrained resources in terms of area, computational abilities, memory, and power. At the same time, security and privacy issues remain as an important problem, thus with the large deployment of low resource devices, increasing need to provide security and privacy among such devices, has arisen. Resource-efficient cryptographic incipient become basic for realizing both security and efficiency in constrained environments and embedded systems like RFID tags and sensor nodes. Among those primitives, lightweight block cipher plays a significant role as a building block for security systems. In 2014 Manoj Kumar et al proposed a new Lightweight block cipher named as FeW, which are suitable for extremely constrained environments and embedded systems. In this paper, we simulate and synthesize the FeW block cipher. Implementation results of the FeW cryptography algorithm on a FPGA are presented. The design target is efficiency of area and cost.