Biblio

Wireless Mesh Networks (WMN) are becoming inevitable in this world of high technology as it provides low cost access to broadband services. Moreover, the technologists are doing research to make WMN more reliable and secure. Subsequently, among wireless ad-hoc networking technologies, Bluetooth Low Energy (BLE) is gaining high degree of importance among researchers due to its easy availability in the gadgets and low power consumption. BLE started its journey from version 4.0 and announced the latest version 5 with mesh support capability. BLE being a low power and mesh supported technology is nowadays among the hot research topics for the researchers. Many of the researchers are working on BLE mesh technology to make it more efficient and smart. Apart from other variables of efficiency, like all communication networks, mesh network security is also of a great concern. In view of the aforesaid, this paper provides a comprehensive review on several works associated to the security in WMN and BLE mesh networks and the research related to the BLE security protocols. Moreover, after the detailed research on related works, this paper has discussed the pros and cons of the present developed mesh security mechanisms. Also, at the end after extracting the curx from the present research on WMN and BLE mesh security, this research study has devised some solutions as how to mitigate the BLE mesh network security lapses.

Data security is the main challenge in Internet of Things (IoT) applications. Security strength and the immunity to security attacks depend mainly on the available power budget. The power-security level trade-off is the main challenge for low power IoT applications, especially, energy limited IoT applications. In this paper, multiple encryption modes that provide different power consumption and security level values are hardware implemented. In other words, some modes provide high security levels at the expense of high power consumption and other modes provide low power consumption with low security level. Dynamic Partial Reconfiguration (DPR) is utilized to adaptively configure the hardware security module based on the available power budget. For example, for a given power constraint, the DPR controller configures the security module with the security mode that meets the available power constraint. ZC702 evaluation board is utilized to implement the proposed encryption modes using DPR. A Lightweight Authenticated Cipher (ACORN) is the most suitable encryption mode for low power IoT applications as it consumes the minimum power and area among the selected candidates at the expense of low throughput. The whole DPR system is tested with a maximum dynamic power dissipation of 10.08 mW. The suggested DPR system saves about 59.9% of the utilized LUTs compared to the individual implementation of the selected encryption modes.

We present an intelligent system that focus on how to ensure the stability of ZigBee network automatically. First, we discussed on the character of ZigBee compared with WIFI. Pointed out advantage of ZigBee resides in security, stability, low power consumption and better expandability. Second, figuring out the shortcomings of ZigBee on application is that physical limitation of the frequency band and weak ability on diffraction, especially coming across a wall or a door in the actual environment of home. The third, to put forward a method which can be used to ensure the strength of ZigBee signal. The method is to detect the strength of ZigBee relay in advance. And then, to compare it with the threshold value which had been defined in previous. The threshold value of strength of ZigBee is the minimal and tolerable value which can ensure stable transmission of ZigBee. If the detected value is out of the range of threshold, system will prompt up warning message which can be used to hint user to add ZigBee reply between the original ZigBee node and ZigBee gateway.

ARM devices (mobile phone, IoT devices) are getting more popular in our daily life due to the low power consumption and cost. These devices carry a huge number of user's private information, which attracts attackers' attention and increase the security risk. The operating systems (e.g., Android, Linux) works out many memory data protection strategies on user's private information. However, the monolithic OS may contain security vulnerabilities that are exploited by the attacker to get root or even kernel privilege. Once the kernel privilege is obtained by the attacker, all data protection strategies will be gone and user's private information can be taken away. In this paper, we propose a hardened memory data protection framework called H-Securebox to defeat kernel-level memory data stolen attacks. H-Securebox leverages ARM hardware virtualization technique to protect the data on the memory with hypervisor privilege. We designed three types H-Securebox for programing developers to use. Although the attacker may have kernel privilege, she can not touch private data inside H-Securebox, since hypervisor privilege is higher than kernel privilege. With the implementation of H-Securebox system assisting by a tiny hypervisor on Raspberry Pi2 development board, we measure the performance overhead of our system and do the security evaluations. The results positively show that the overhead is negligible and the malicious application with root or kernel privilege can not access the private data protected by our system.

Smart Grid cybersecurity is one of the key ingredients for successful and wide scale adaptation of the Smart Grid by utilities and governments around the world. The implementation of the Smart Grid relies mainly on the highly distributed sensing and communication functionalities of its components such as Wireless Sensor Networks (WSNs), Phasor Measurement Units (PMUs) and other protection devices. This distributed nature and the high number of connected devices are the main challenges for implementing cybersecurity in the smart grid. As an example, the North American Electric Reliability Corporation (NERC) issued the Critical Infrastructure Protection (CIP) standards (CIP-002 through CIP-009) to define cybersecurity requirements for critical power grid infrastructure. However, NERC CIP standards do not specify cybersecurity for different communication technologies such as WSNs, fiber networks and other network types. Implementing security mechanisms in WSNs is a challenging task due to the limited resources of the sensor devices. WSN security mechanisms should not only focus on reducing the power consumption of the sensor devices, but they should also maintain high reliability and throughput needed by Smart Grid applications. In this paper, we present a WSN cybersecurity mechanism suitable for smart grid monitoring application. Our mechanism can detect and isolate various attacks in a smart grid environment, such as denial of sleep, forge and replay attacks in an energy efficient way. Simulation results show that our mechanism can outperform existing techniques while meeting the NERC CIP requirements.

Tamper detection circuits provide the first and most important defensive wall in protecting electronic modules containing security data. A widely used procedure is to cover the entire module with a foil containing fine conductive mesh, which detects intrusion attempts. Detection circuits are further classified as passive or active. Passive circuits have the advantage of low power consumption, however they are unable to detect small variations in the conductive mesh parameters. Since modern tools provide an upper leverage over the passive method, the most efficient way to protect security modules is thus to use active circuits. The active tamper detection circuits are typically probing the conductive mesh with short pulses, analyzing its response in terms of delay and shape. The method proposed in this paper generates short pulses at one end of the mesh and analyzes the response at the other end. Apart from measuring pulse delay, the analysis includes a frequency domain characterization of the system, determining whether there has been an intrusion or not, by comparing it to a reference (un-tampered with) spectrum. The novelty of this design is the combined analysis, in time and frequency domains, of the small variations in mesh characteristic parameters.