The sound of communication in underwater acoustic sensor networks: (Position paper)

Underwater environments have never been much of a constraint to the rich animal life they support at all depths of our seas and oceans. Indeed, nature has taken advantage of this environment to develop a rich variety of efficient communication strategies through evolutionary change and adaptation. The wealth of knowledge to be discovered will continue to dazzle and fascinate the world. For underwater sensor network communication, acoustic signalling is the preferred choice for designers because sound propagation is the most efficient when compared to other forms, like thermal, light, and electromagnetic. It is within this acoustic environment that researchers have to innovate and develop new ideas and methodologies so as to advance the state-of-the-art. In this paper, several fundamental issues and connections are discussed that arise in the study of underwater wireless sensor networks. A variety of ideas and solutions for further research is proposed and fundamental issues in topology control, directional underwater transducers, and monitoring and surveillance are disc

Spatial networks with wireless applications

Many networks have nodes located in physical space, with links more common between closely spaced pairs of nodes. For example, the nodes could be wireless devices and links communication channels in a wireless mesh network. We describe recent work involving such networks, considering effects due to the geometry (convex,non-convex, and fractal), node distribution, distance-dependent link probability, mobility, directivity and interference.Comment: Review article- an amended version with a new title from the origina

Cyber-Attack Drone Payload Development and Geolocation via Directional Antennae

The increasing capabilities of commercial drones have led to blossoming drone usage in private sector industries ranging from agriculture to mining to cinema. Commercial drones have made amazing improvements in flight time, flight distance, and payload weight. These same features also offer a unique and unprecedented commodity for wireless hackers -- the ability to gain ‘physical’ proximity to a target without personally having to be anywhere near it. This capability is called Remote Physical Proximity (RPP). By their nature, wireless devices are largely susceptible to sniffing and injection attacks, but only if the attacker can interact with the device via physical proximity. A properly outfitted drone can increase the attack surface with RPP (adding a range of over 7 km using off-the-shelf drones), allowing full interactivity with wireless targets while the attacker can remain distant and hidden. Combined with the novel approach of using a directional antenna, these drones could also provide the means to collect targeted geolocation information of wireless devices from long distances passively, which is of significant value from an offensive cyberwarfare standpoint. This research develops skypie, a software and hardware framework designed for performing remote, directional drone-based collections. The prototype is inexpensive, lightweight, and totally independent of drone architecture, meaning it can be strapped to most medium to large commercial drones. The prototype effectively simulates the type of device that could be built by a motivated threat actor, and the development process evaluates strengths and shortcoming posed by these devices. This research also experimentally evaluates the ability of a drone-based attack system to track its targets by passively sniffing Wi-Fi signals from distances of 300 and 600 meters using a directional antenna. Additionally, it identifies collection techniques and processing algorithms for minimizing geolocation errors. Results show geolocation via 802.11 emissions (Wi-Fi) using a portable directional antenna is possible, but difficult to achieve the accuracy that GPS delivers (errors less than 5 m with 95% confidence). This research shows that geolocation predictions of a target cell phone acting as a Wi-Fi access point in a field from 300 m away is accurate within 70.1 m from 300 m away and within 76 meters from 600 m away. Three of the four main tests exceed the hypothesized geolocation error of 15% of the sensor-to-target distance, with tests 300 m away averaging 25.5% and tests 600 m away averaging at 34%. Improvements in bearing prediction are needed to reduce error to more tolerable quantities, and this thesis discusses several recommendations to do so. This research ultimately assists in developing operational drone-borne cyber-attack and reconnaissance capabilities, identifying limitations, and enlightening the public of countermeasures to mitigate the privacy threats posed by the inevitable rise of the cyber-attack drone

Robust, Resilient Networked Communication in Challenged Environments

In challenged environments, digital communication infrastructure may be difficult or even impossible to access. This is especially true in rural and developing regions, as well as in any region during a time of political or environmental crisis. We advance the state of the art in wireless networking and security to design networks and applications that rapidly assess changing networking conditions to restore communication and provide local situational awareness. This dissertation examines new systems for responding to current and emerging needs for wireless networks. This work looks across the wireless ecosystem of widely deployed standards. We develop new tools to improve network assessment and to provide robust and reliable network communication. By incorporating new technological breakthroughs, such as the wide commercial success of Unmanned Aircraft Systems (UAS), we introduce novel methods and systems for existing wireless standards for these challenged networks. We assess how existing technologies and standards function in difficult environments: lacking end-end Internet connectivity, experiencing overload or other resource constraints, and operating in three dimensional space. Through this lens, we demonstrate how to optimize networks to serve marginalized communities outside of first world urban cities and make our networks resilient to natural and political crisis that threaten communication

Wireless Sensor Localization: Error Modeling and Analysis for Evaluation and Precision

Wireless sensor networks (WSNs) have shown promise in a broad range of applications. One of the primary challenges in leveraging WSNs lies in gathering accurate position information for the deployed sensors while minimizing power cost. In this research, detailed background research is discussed regarding existing methods and assumptions of modeling methods and processes for estimating sensor positions. Several novel localization methods are developed by applying rigorous mathematical and statistical principles, which exploit constraining properties of the physical problem in order to produce improved location estimates. These methods are suitable for one-, two-, and three-dimensional position estimation in ascending order of difficulty and complexity. Unlike many previously existing methods, the techniques presented in this dissertation utilize practical, realistic assumptions and are progressively designed to mitigate incrementally discovered limitations. The design and results of a developed multiple-layered simulation environment are also presented that model and characterize the developed methods. The approach, developed methodologies, and software infrastructure presented in this dissertation provide a framework for future endeavors within the field of wireless sensor networks

Passive Radiolocation of IEEE 802.11 Emitters using Directional Antennae

Low-cost commodity hardware and cheaper, more capable consumer-grade drones make the threat of home-made, inexpensive drone-mounted wireless attack platforms (DWAPs) greater than ever. Fences and physical security do little to impede a drone from approaching private, commercial, or government wireless access points (WAPs) and conducting wireless attacks. At the same time, unmanned aerial vehicles (UAVs) present a valuable tool for network defenders conducting site surveys and emulating threats. These platforms present near-term dangers and opportunities for corporations and governments. Despite the vast leaps in technology these capabilities represent, UAVs are noisy and consequently difficult to conceal as they approach a potential target; stealth is a valuable asset to an attacker. Using a directional antenna instead of the typical omnidirectional antenna would significantly increase the distance from which a DWAP may conduct attacks and would improve their stealthiness and overall effectiveness. This research seeks to investigate the possibility of using directional antennae on DWAPs by resolving issues inhibiting directional antennae use on consumer and hobbyist drone platforms. This research presents the hypothesis that a DWAP equipped with a directional antenna can predict bearings and locations of WAPs within an acceptable margin of error

Development of a WiFi and RFID based indoor location and mobility tracking system

Ubiquitous positioning and people mobility tracking has become one of the critical parts of our daily life. As a core element of the Location Based Services (LBS), the ubiquitous positioning capability necessitates seamless positioning across both indoor and outdoor environments. Nowadays, tracking outdoor with a relatively high accuracy and reliability can be achieved using matured technologies such as Global Navigation Satellite Systems (GNSS). However, it is still challenging for tracking in indoor environments such as airports, shopping malls and museums. The demand for indoor tracking has driven the fast development of indoor positioning and tracking technologies, especially Wi-Fi, RFID and smartphone etc. All these technologies have significantly enhanced the convenience of people’s daily life and the competitiveness of business firms. With the rapidly increased ubiquity of Wi-Fi enabled mobile phones and tablets, developing a robust location and mobility tracking system utilising such technologies will have a great potential for industry innovation and applications. This research is part of an Australian Research Council (ARC) project that involves two universities and one industry partner who is a large global shopping mall management company located in Australia. The project aims to develop a smart system for robust modelling and analysing the shopping behaviours of customers so that value-added services can be effectively provided. A number of field tests have been conducted and a large amount of data has been acquired both in the shopping mall of interest and the RMIT Indoor Positioning Laboratory. A large cohort of real users in the shopping mall were recorded where only one Wi-Fi access point (AP) connection at a time for each mobile device user was provided for our research. This makes most of the conventional tracking and positioning methods inapplicable. To overcome this constraint, a new hybrid system for positioning and mobility tracking — called single AP-connection location tracking system (SCLTS) was developed, which utilised Wi-Fi, RFID and mobile device technologies and took advantage of both the cell of origin (CoO) and fingerprinting positioning methods. Three new algorithms for Wi-Fi based indoor positioning were developed during this research. They are the common handover point determination (CHOPD) algorithm for determining the boundary of the cell; the algorithm for positioning with the case of same-line-dual-connection (SLDC) in a long narrow space (e.g., a long corridor) and the algorithm for positioning with the case of perpendicular-dual-connection of APs in a T-shape corridor for improving the positioning accuracy. The architecture of the SCLTS system was also developed as part of the implementation of the SCLTS system. Various experiments were conducted in a simulated large shopping-mall-like environment (i.e., the RMIT Indoor Positioning Lab) and the results showed that the performance of the SCLTS developed was very promising and the original goal of the project has been achieved. In addition, the two most popular indoor positioning methods — trilateration and fingerprinting were also optimised and implemented in a real industrial product and promising results have been achieved

Passive Planar Microwave Devices

The aim of this book is to highlight some recent advances in microwave planar devices. The development of planar technologies still generates great interest because of their many applications in fields as diverse as wireless communications, medical instrumentation, remote sensing, etc. In this book, particular interest has been focused on an electronically controllable phase shifter, wireless sensing, a multiband textile antenna, a MIMO antenna in microstrip technology, a miniaturized spoof plasmonic antipodal Vivaldi antenna, a dual-band balanced bandpass filter, glide-symmetric structures, a transparent multiband antenna for vehicle communications, a multilayer bandpass filter with high selectivity, microwave planar cutoff probes, and a wideband transition from microstrip to ridge empty substrate integrated waveguide