Buried Object Sensing Considering Curved Pipeline

This letter presents design and implementation of a system solution, where light weight wireless devices are used to identify a moving object within underground pipeline for maintenance and inspection. The devices such as transceiver operating at S-band are deployed for underground settings. Finer-grained channel information in conjunction with leaky-wave cable (LWC) detects any moving entity. The processing of the measured data over time is analyzed and used for reporting the disturbances. Deploying an LWC as the receiver has benefits in terms of a wider coverage area, covering blind and semiblind zones. The system fully exploits the variances of both amplitude and phase information of channel information as the performance indicators for motion detection. The experimental results demonstrate greater level of accuracy

Reconfigurable antennas for wireless network security

Large scale proliferation of wireless technology coupled with the increasingly hostile information security landscape is of serious concern as organizations continue to widely adopt wireless networks to access and distribute critical and con dential information. Private users also face more risks than ever as they exchange more and more sensitive information over home and public networks through their ubiquitous wireless-enabled laptops and hand held devices. The fundamental broadcast nature of wireless data transmission aggravates the situation, since unlike wired networks, it introduces multiple avenues for attack and penetration into a network. Though several traditional mechanisms do exist to protect wireless networks against threats, such schemes are a carryover from the traditional wire based systems. Hence vulnerabilities continue to exist, and have been repeatedly demonstrated to be susceptible to failure under di erent circumstances.The resulting uncertainties have led to a signi cant paradigm shift in the design and implementation of wireless security in recent times, among which wireless channel based security schemes have shown the most promise. Channel based security schemes are rooted on the simple fact that a legitimate user and an adversary cannot be physically co-located and hence the underlying multi-path structure corresponding to the two links cannot be the same. However most wireless systems are constrained in terms of bandwidth, power and number of transceivers, which seriously limit the performance of such channel based security implementations. To overcome these limitations, this thesis proposes a new dimension to the channel based security approach by introducing the capabilities of recon gurable antennas. The main objective of this work is to demonstrate that the ability of recon gurable antennas to generate di erent channel realizations that are uncorrelated between di erent modes will lead to signi cant improvements in intrusion detection rates.To this end, two di erent schemes that make use of channels generated by a recon gurable antenna are proposed and evaluated through measurements. The rstscheme is based on associating a channel based ngerprint to the legitimate user to prevent intrusion. The three main components of this scheme are i ) a ngerprint derived from the di erent modes of the antenna, ii ) a metric to compare two ngerprints and iii ) a hypothesis test based on the proposed metric to classify intruders and legitimate transmitters. The second scheme relies on monitoring the statistics of the channels for the legitimate transmitters' links since any intrusion will result in an observable change in the channel's statistics. The problem is posed as a generalized likelihood ratio test (GLRT) which responds to any change in the channel statistics by a large spike in the likelihood ratio's value. The detector's performance is studied as a function of pattern correlation coe cient for both schemes to provide insights on designing appropriate antenna modes for better performance.Moreover this thesis takes a holistic approach to studying the antenna based security schemes. A novel channel modeling approach which combines the cluster channel model and site speci c ray tracer results is proposed and validated to facilitate the analysis of such schemes through simulations without resorting to comprehensive channel measurements. This approach is motivated by the lack of an intuitive and simple channel model to study systems that use recon gurable antennas for any application.Finally the design of a metamaterial based substrate that can help miniaturize antenna arrays and recon gurable antennas is presented. The magnetic permeabilityenhanced metamaterial's capability to miniaturize an antenna's size while maintaining an acceptable level of isolation between elements in an array is experimentallydemonstrated. The bene ts gained in a wireless communication system that uses a patch antenna arrray built on this substrate is quanti ed in terms of mean e ective gain, correlation between the antennas and channel capacity through channel measurements.Despite their capability to signi cantly improve spectral e ciency, the widespread adoption of recon gurable antennas in wireless devices has been hampered by their complexity, cost and size. The work presented in this thesis is therefore intended to serve as a catalyst to the widespread adoption of recon gurable antenna technology by i ) adding value to such antennas by utilizing them for enhancing system security and ii ) providing a mechanism to miniaturize them to facilitate their integration into modern space constrained wireless devices.Ph.D., Electrical Engineering -- Drexel University, 201

Flexible and scalable software defined radio based testbed for large scale body movement

Human activity (HA) sensing is becoming one of the key component in future healthcare system. The prevailing detection techniques for IHA uses ambient sensors, cameras and wearable devices that primarily require strenuous deployment overheads and raise privacy concerns as well. This paper proposes a novel, non-invasive, easily-deployable, flexible and scalable test-bed for identifying large-scale body movements based on Software Defined Radios (SDRs). Two Universal Software Radio Peripheral (USRP) models, working as SDR based transceivers, are used to extract the Channel State Information (CSI) from continuous stream of multiple frequency subcarriers. The variances of amplitude information obtained from CSI data stream are used to infer daily life activities. Different machine learning algorithms namely K-Nearest Neighbour, Decision Tree, Discriminant Analysis and Naïve Bayes are used to evaluate the overall performance of the test-bed. The training, validation and testing processes are performed by considering the time-domain statistical features obtained from CSI data. The K-nearest neighbour outperformed all aforementioned classifiers, providing an accuracy of 89.73%. This preliminary non-invasive work will open a new direction for design of scalable framework for future healthcare systems

Privacy-Preserving Non-Wearable Occupancy Monitoring System Exploiting Wi-Fi Imaging for Next-Generation Body Centric Communication

Nano-scaled structures, wireless sensing, wearable devices, and wireless communications systems are anticipated to support the development of new next-generation technologies in the near future. Exponential rise in future Radio-Frequency (RF) sensing systems have demonstrated its applications in areas such as wearable consumer electronics, remote healthcare monitoring, wireless implants, and smart buildings. In this paper, we propose a novel, non-wearable, device-free, privacy-preserving Wi-Fi imaging-based occupancy detection system for future smart buildings. The proposed system is developed using off-the-shelf non-wearable devices such as Wi-Fi router, network interface card, and an omnidirectional antenna for future body centric communication. The core idea is to detect presence of person along its activities of daily living without deploying a device on person's body. The Wi-Fi signals received using non-wearable devices are converted into time-frequency scalograms. The occupancy is detected by classifying the scalogram images using an auto-encoder neural network. In addition to occupancy detection, the deep neural network also identifies the activity performed by the occupant. Moreover, a novel encryption algorithm using Chirikov and Intertwining map-based is also proposed to encrypt the scalogram images. This feature enables secure storage of scalogram images in a database for future analysis. The classification accuracy of the proposed scheme is 91.1%

Advanced sensing techniques for intelligent human activity recognition using machine learning

No abstract available

Long-term moored array measurements of currents and hydrography over Georges Bank : 1994–1999

Author Posting. © The Author(s), 2009. This is the author's version of the work. It is posted here by permission of Elsevier B.V. for personal use, not for redistribution. The definitive version was published in Progress In Oceanography 82 (2009): 191-223, doi:10.1016/j.pocean.2009.07.004.In conjunction with the GLOBEC (Global Ocean Ecosystems Dynamics) program, measurements of moored currents, temperature and salinity were made during 1994-1999 at locations in 76 m of water along the Southern Flank of Georges Bank and at the Northeastern Peak. The measurements concentrate on the biologically crucial winter and spring periods, and coverage during the fall is usually poorer. Current time series were completely dominated by the semidiurnal M2 tidal component, while other tidal species (including the diurnal K1 component) were also important. There was a substantial wind-driven component of the flow, which was linked, especially during the summer, to regional–scale response patterns. The current response at the Northeast Peak was especially strong in the 3-4 day period band, and this response is shown to be related to an amplifying topographic wave propagating eastward along the northern flank. Monthly mean flows on the southern flank are southwestward throughout the year, but strongest in the summertime. The observed tendency for summertime maximum along-bank flow to occur at depth is rationalized in terms of density gradients associated with a near-surface freshwater tongue wrapping around the Bank. Temperature and salinity time series demonstrate the presence, altogether about 25% of the time, of a number of intruding water masses. These intrusions could last anywhere from a couple days up to about a month. The sources of these intrusions can be broadly classified as the Scotian Shelf (especially during the winter), the Western Gulf of Maine (especially during the summer), and the deeper ocean south of Georges Bank (throughout the year). On longer time scales, the temperature variability is dominated by seasonal temperature changes. During the spring and summer, these changes are balanced by local heating or cooling, but wintertime cooling involves advective lateral transports as well. Salinity variations have weak, if any, seasonal variability, but are dominated by interannual changes that are related to regional- or basin-scale changes. All considered, Georges Bank temperature and salinity characteristics are found to be highly dependent on the surrounding waters, but many questions remain, especially in terms of whether intrusive events leave a sustained impact on Bank waters.This work took place as part of the GLOBEC Northwest Atlantic/Georges Bank field project, and was sponsored through NSF Biological Oceanography grants OCE- 80644500 and OCE- 80644501

Security Hazards when Law is Code.

As software continues to eat the world, there is an increasing pressure to automate every aspect of society, from self-driving cars, to algorithmic trading on the stock market. As this pressure manifests into software implementations of everything, there are security concerns to be addressed across many areas. But are there some domains and fields that are distinctly susceptible to attacks, making them difficult to secure? My dissertation argues that one domain in particular—public policy and law— is inherently difficult to automate securely using computers. This is in large part because law and policy are written in a manner that expects them to be flexibly interpreted to be fair or just. Traditionally, this interpreting is done by judges and regulators who are capable of understanding the intent of the laws they are enforcing. However, when these laws are instead written in code, and interpreted by a machine, this capability to understand goes away. Because they blindly fol- low written rules, computers can be tricked to perform actions counter to their intended behavior. This dissertation covers three case studies of law and policy being implemented in code and security vulnerabilities that they introduce in practice. The first study analyzes the security of a previously deployed Internet voting system, showing how attackers could change the outcome of elections carried out online. The second study looks at airport security, investigating how full-body scanners can be defeated in practice, allowing attackers to conceal contraband such as weapons or high explosives past airport checkpoints. Finally, this dissertation also studies how an Internet censorship system such as China’s Great Firewall can be circumvented by techniques that exploit the methods employed by the censors themselves. To address these concerns of securing software implementations of law, a hybrid human-computer approach can be used. In addition, systems should be designed to allow for attacks or mistakes to be retroactively undone or inspected by human auditors. By combining the strengths of computers (speed and cost) and humans (ability to interpret and understand), systems can be made more secure and more efficient than a method employing either alone.PhDComputer Science and EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/120795/1/ewust_1.pd

Acoustic monitoring of earthquakes along the Blanco Transform Fault Zone and Gorda plate and their tectonic implications

Hydroacoustic tertiary (T-) waves are seismically generated acoustic waves that propagate over great distances in the ocean sound channel with little loss in signal strength. Hydrophone recorded T-waves can provide a lower earthquake detection threshold and an improved epicenter location accuracy for oceanic earthquakes than land-based seismic networks. Thus detection and location of NE Pacific ocean earthquakes along the Blanco Transform Fault (BTFZ) and Gorda plate using the U.S. Navy's SOSUS (SOund SUrveillance System) hydrophone arrays afford greater insight into the current state of stress and crustal deformation mechanics than previously available. Acoustic earthquake information combined with bathymetry, submersible observations, earthquake source-parameter estimates, petrologic samples, and water-column chemistry renders a new tectonic view of the southern Juan de Fuca plate boundaries. Chapter 2 discusses development of seismo-acoustic analysis techniques using the well-documented April 1992 Cape Mendocino earthquake sequence. Findings include a hydrophone detection threshold estimate (M~2.4), and T-wave propagation path modeling to approximate earthquake acoustic source energy. Empirical analyses indicate that acoustic energy provides a reasonable magnitude and seismic moment estimate of oceanic earthquakes not detected by seismic networks. Chapters 3 documents a probable volcanogenic T-wave event swarm along a pull-apart basin within the western BTFZ during January 1994. Response efforts yielded evidence of anomalous water-column ³He concentrations, pillow-lava volcanism, and the first discovery of active hydrothermal vents along an oceanic fracture zone. Chapter 4 discusses the detection of a NE-SW trending microearthquake band along the mid-Gorda plate which was active from initiation of SOSUS recording in August 1991 through July 1992, then abruptly ceased. It is proposed that eventual termination of the Gorda plate seismicity band is due to strain reduction associated with the Cape Mendocino earthquake sequence. Chapter 5 combines bathymetric, hydro-acoustic, seismic, submersible, and gravity data to investigate the active tectonics of the transform parallel Blanco Ridge (BR), along the eastern BTFZ. The BR formation mechanism preferred here is uplift through strike-slip motion (with a normal component) followed by formation and intrusion of mantle-derived serpentinized-peridotite into the shallow ocean crust. The conclusion considers a potential link between the deformation patterns observed along the BTFZ and Gorda plate regions