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In this paper, we propose a scheme for classification of maritime targets through fusion of images collected from dissimilar sensors with an objective to improve maritime domain awareness. Low- and medium-level fusion methods are applied to three types of image data—visual, thermal, multi-spectral—using features obtained from the speeded-up robust features algorithm. The goal was to implement the...
A generalized Hough transform-based classification scheme for an object-of-interest in maritime-domain images is proposed in this paper. The scheme explores the use of Hough features and neural networks to classify large sets of image objects collected in the maritime domain environment. The object edge points are extracted and used to generate the generalized Hough coordinate tables. The Hough coordinates...
Challenges in static analysis of mobile malware have stimulated the need for emulated, dynamic analysis techniques. Unfortunately, emulating mobile devices is nontrivial because of the different types of hardware features onboard (e.g., sensors) and the manner in which users interact with their devices as compared to traditional computing platforms. To test this, our research focuses on the enumeration...
Software-defined networks (SDNs) offer network defenders the opportunity to choose from a variety of protection techniques in response to different threats. In contrast, traditional network architectures often lack the flexibility to implement threat-specific security controls. This research was conducted on a hardware SDN test bed running custom security applications to demonstrate techniques that...
Wireless mobile ad hoc networks have multiple civilian and military applications. Because these networks are ad hoc and may not interact with fixed infrastructure, central nodes called cluster heads need to be assigned to manage a set of devices in the network. The cluster head needs to be assigned dynamically for two reasons. First, the cluster spends more time active, and the assignment of cluster...
In many densely populated environments, there is an abundance of base stations by which a mobile station may be passively geographically located (geolocated) using various techniques that require multiple base stations. Areas in which base station density is sparse may not possess the requisite number of base stations to perform such techniques and, therefore, require different methods by which to...
In this paper, we provide an analysis of fixed-position communication nodes in a network for maintaining availability during robot exploration of unknown environments. Based on realistic wireless propagation models in different environments, the communication path loss as the robot moves is characterized. The nodes are then described, and we discuss a simple scalable policy for their deployment. The...
Security is challenging for wireless networks, in part because signals radiate outwards and can be intercepted easily and unobtrusively. Because of this, security cannot be provided simply by protecting the hardware, and must be supported by the communication protocol and implementation.
This paper examines a possible vulnerability with the potential for a malicious entity to prevent a mobile device from handing over from a global system for mobile communications (GSM) to universal mobile telecommunications system (UMTS) network because the GSM network maintains the stand-alone dedicated control channel (SDCCH) uplink time slots. The process of testing this vulnerability requires...
We present a simple and effective means for position estimation designed to be deployed in urban and dense multipath environments characteristic of 4G wireless networks. To address the multipath channel of such environments a fingerprinting scheme is proposed. One of the drawbacks to this class of methods is the large initial cost associated with establishing a database matrix. This issue is addressed...
Many network models are too complex to readily identify which structural aspects of a network are most influential on robustness. To analyze the dynamics and robustness of a network, many of the protocol details can be reduced to a graph theory representation of nodes, links and link weights. Our method uses the spectral analysis of the Laplacian matrix to decouple the interactions between nodes to...
To maximize the performance of a software-defined network, a network observer must develop a state that can be tracked and controlled. We propose a novel method that uses the entire eigenspace of the Laplacian matrix to determine the state of a SDN. Our approach exploits the double orthogonality of the Laplacian matrix in order to define the dual basis. Each basis uses the entire reachability space...
Software-defined networks (SDN) are an emerging technology that offers to simplify networking devices by centralizing the network layer functions and allowing adaptively programmable traffic flows. We propose using spectral graph theory methods to identify and locate congestion in a network. The analysis of the balanced traffic case yields an efficient solution for congestion identification. The unbalanced...
Techniques for extracting traffic patterns from ship position data to generate atlases of expected ocean travel are developed in this paper. An archive of historical data is used to develop a traffic density grid. The Hough transformation is used to extract linear patterns of elevated density from the traffic density grid, which can be considered the ??highways?? of the oceans. These highways collectively...
To meet government requirements for positioning emergency services, Long Term Evolution (LTE), the latest generation of mobile communications popular in North America and Europe, incorporates the ability to ascertain the position of the user equipment via the network. This additional signaling means that there is also the chance that the user position may be vulnerable to being intercepted by unauthorized...
Hidden-Markov Models (HMM) have shown promise as viable solutions to providing location based services (LBS) within cellular networks. Previously established work includes a scheme to merge the stochastic contribution of the HMM and maximum likelihood decisions based on signal strength measurements and timing adjust parameters. A novel scalable positioning algorithm that utilizes the aforementioned...
A novel scheme for mobile subscriber positioning is proposed based on the hidden-Markov model (HMM) and the cell-ID maximum-likelihood database correlation method also known as fingerprinting. Using a simulated channel environment, based on the Clearwire deployment of WiMAX base stations in San Jose, CA, we show that matching the right configuration of the model to the deployment environment can realize...
Source localization and tracking of a Cognitive Radio (CR) is a significant challenge because of the dynamic opportunistic behavior of the radio across the spatial, frequency, and temporal domains. For any localization or tracking scheme to be effective, it must be able to adapt as a CR adapts to its surroundings. The extended semi range-based (ESRB) localization scheme was proposed as a solution...
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