Biblio

This paper investigates the use of BeagleBone Black Wireless single-board Linux computers with Long Range (LoRa) transceivers to send and receive information in a mesh network while one of the transmitting/receiving nodes is acting as a relay in the system. An experiment is conducted to examine how long each LoRa node needed to learn the transmission intervals of any other transmitting nodes on the network and to synchronize with the other nodes prior to transmission. The spread factor, bandwidth, and coding rate are all varied for a total of 18 different combinations. A link to the Python code used on the BeagleBone Black is provided at the end of this paper. The best parameter combinations for each individual node and for the system as a whole is investigated. Additional experiments and applications of this technology are explored in the conclusions.

Wireless technology has seen a tremendous growth in the recent past. Orthogonal Frequency Division Multiplexing (OFDM) modulation scheme has been utilized in almost all the advanced wireless techniques because of the advantages it offers. Hence in this aspect, SystemVue based OFDM transceiver has been developed with AWGN as the channel noise. To mitigate the channel noise Convolutional code with Viterbi decoder has been depicted. Further to protect the information from the malicious users the data is scrambled with the aid of gold codes. The performance of the transceiver is analysed through various Bit Error Rate (BER) versus Signal to Noise Ratio (SNR) graphs.

Wireless Networks-on-Chips (NoCs) have emerged as a panacea to the non-scalable multi-hop data transmission paths in traditional wired NoC architectures. Using low-power transceivers in NoC switches, novel Wireless NoC (WiNoC) architectures have been shown to achieve higher energy efficiency with improved peak bandwidth and reduced on-chip data transfer latency. However, using wireless interconnects for data transfer within a chip makes the on-chip communications vulnerable to various security threats from either external attackers or internal hardware Trojans (HTs). In this work, we propose a mechanism to make the wireless communication in a WiNoC secure against persistent jamming based Denial-of-Service attacks from both external and internal attackers. Persistent jamming attacks on the on-chip wireless medium will cause interference in data transfer over the duration of the attack resulting in errors in contiguous bits, known as burst errors. Therefore, we use a burst error correction code to monitor the rate of burst errors received over the wireless medium and deploy a Machine Learning (ML) classifier to detect the persistent jamming attack and distinguish it from random burst errors. In the event of jamming attack, alternate routing strategies are proposed to avoid the DoS attack over the wireless medium, so that a secure data transfer can be sustained even in the presence of jamming. We evaluate the proposed technique on a secure WiNoC in the presence of DoS attacks. It has been observed that with the proposed defense mechanisms, WiNoC can outperform a wired NoC even in presence of attacks in terms of performance and security. On an average, 99.87% attack detection was achieved with the chosen ML Classifiers. A bandwidth degradation of \textbackslashtextless;3% is experienced in the event of internal attack, while the wireless interconnects are disabled in the presence of an external attacker.

This paper presents the relative merits of IR and microwave sensor technology and their combination with wireless camera for the development of a wall mounted wireless intrusion detection system and explain the phases by which the intrusion information are collected and sent to the central control station using wireless mesh network for analysis and processing the collected data. These days every protected zone is facing numerous security threats like trespassing or damaging of important equipments and a lot more. Unwanted intrusion has turned out to be a growing problem which has paved the way for a newer technology which detects intrusion accurately. Almost all organizations have their own conventional arrangement of protecting their zones by constructing high wall, wire fencing, power fencing or employing guard for manual observation. In case of large areas, manually observing the perimeter is not a viable option. To solve this type of problem we have developed a wall-mounted wireless fencing system. In this project I took the responsibility of studying how the different units could be collaborated and how the data collected from them could be further processed with the help of software, which was developed by me. The Intrusion detection system constitutes an important field of application for IR and microwave based wireless sensor network. A state of the art wall-mounted wireless intrusion detection system will detect intrusion automatically, through multi-level detection mechanism (IR, microwave, active RFID & camera) and will generate multi-level alert (buzzer, images, segment illumination, SMS, E-Mail) to notify security officers, owners and also illuminate the particular segment where the intrusion has happened. This system will enable the authority to quickly handle the emergency through identification of the area of incident at once and to take action quickly. IR based perimeter protection is a proven technology. However IR-based intrusion detection system is not a full-proof solution since (1) IR may fail in foggy or dusty weather condition & hence it may generate false alarm. Therefore we amalgamate this technology with Microwave based intrusion detection which can work satisfactorily in foggy weather. Also another significant arena of our proposed system is the Camera-based intrusion detection. Some industries require this feature to capture the snap-shots of the affected location instantly as the intrusion happens. The Intrusion information data are transmitted wirelessly to the control station via multi hop routing (using active RFID or IEEE 802.15.4 protocol). The Control station will receive intrusion information at real time and analyze the data with the help of the Intrusion software. It then sends SMS to the predefined numbers of the respective authority through GSM modem attached with the control station engine.