2,582 research outputs found

    Wireless and Physical Security via Embedded Sensor Networks

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    Wireless Intrusion Detection Systems (WIDS) monitor 802.11 wireless frames (Layer-2) in an attempt to detect misuse. What distinguishes a WIDS from a traditional Network IDS is the ability to utilize the broadcast nature of the medium to reconstruct the physical location of the offending party, as opposed to its possibly spoofed (MAC addresses) identity in cyber space. Traditional Wireless Network Security Systems are still heavily anchored in the digital plane of "cyber space" and hence cannot be used reliably or effectively to derive the physical identity of an intruder in order to prevent further malicious wireless broadcasts, for example by escorting an intruder off the premises based on physical evidence. In this paper, we argue that Embedded Sensor Networks could be used effectively to bridge the gap between digital and physical security planes, and thus could be leveraged to provide reciprocal benefit to surveillance and security tasks on both planes. Toward that end, we present our recent experience integrating wireless networking security services into the SNBENCH (Sensor Network workBench). The SNBENCH provides an extensible framework that enables the rapid development and automated deployment of Sensor Network applications on a shared, embedded sensing and actuation infrastructure. The SNBENCH's extensible architecture allows an engineer to quickly integrate new sensing and response capabilities into the SNBENCH framework, while high-level languages and compilers allow novice SN programmers to compose SN service logic, unaware of the lower-level implementation details of tools on which their services rely. In this paper we convey the simplicity of the service composition through concrete examples that illustrate the power and potential of Wireless Security Services that span both the physical and digital plane.National Science Foundation (CISE/CSR 0720604, ENG/EFRI 0735974, CIES/CNS 0520166, CNS/ITR 0205294, CISE/ERA RI 0202067

    Brain-Like Two-Layer Learning based Efficient Attack Detection for Wireless Sensor Networks

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    Wireless Sensor Networks - An Introduction

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    A wireless sensor and actuator network for improving the electrical power grid dependability

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    This paper presents an overview of a Wireless Sensor and Actuator Network (WSAN) used to monitor an electrical power grid distribution infrastructure. The WSAN employs appropriate sensors to monitor key grid components, integrating both safety and security services, which improve the grid distribution dependability. The supported applications include, among others, video surveillance of remote secondary substations, which imposes special requirements from the point of view of quality of service and reliability. The paper presents the hardware and software architecture of the system together with performance results

    6G White Paper on Machine Learning in Wireless Communication Networks

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    The focus of this white paper is on machine learning (ML) in wireless communications. 6G wireless communication networks will be the backbone of the digital transformation of societies by providing ubiquitous, reliable, and near-instant wireless connectivity for humans and machines. Recent advances in ML research has led enable a wide range of novel technologies such as self-driving vehicles and voice assistants. Such innovation is possible as a result of the availability of advanced ML models, large datasets, and high computational power. On the other hand, the ever-increasing demand for connectivity will require a lot of innovation in 6G wireless networks, and ML tools will play a major role in solving problems in the wireless domain. In this paper, we provide an overview of the vision of how ML will impact the wireless communication systems. We first give an overview of the ML methods that have the highest potential to be used in wireless networks. Then, we discuss the problems that can be solved by using ML in various layers of the network such as the physical layer, medium access layer, and application layer. Zero-touch optimization of wireless networks using ML is another interesting aspect that is discussed in this paper. Finally, at the end of each section, important research questions that the section aims to answer are presented

    Fault location in an electrical energy distribution infrastructure with a wireless sensor network

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    This paper presents a detailed analysis of the applicability of wireless systems in the localization of faults in the energy distribution network. The hardware and software architectures of the envisaged sensor solution will also be described and finally, the integration of this system into Smart Grids will be discussed in terms of automatic fault analysis. A pilot system has been tested in a subset of the Portuguese energy distribution infrastructure operated by EDP Energias de Portugal. It presents a new approach to a fault locator system for the power network. The purpose is to obtain faster and more reliable information about the disruptions in the power distribution network and their location. Furthermore, the wireless sensors allow remote detection of medium and low voltage (MV/LV) power transformer hotspots in order to identify emerging malfunction as well as detection of intrusion in the MV/LV power transformers

    Determining Enclosure Breach Electromagnetically

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    A structure breach may be determined. A sensor, provided in the structure, may be driven with a constant frequency signal. The sensor may comprise a first conductive element and a second conductive element. The first conductive element may be substantially parallel with the second conductive element. A standing wave pattern may be induced on the sensor by the constant frequency signal reflecting off a termination point of the sensor. A least one characteristic of the sensor caused by the voltage standing wave pattern may be measured. A breach occurrence in the structure may be determined when the measured at least one characteristic varies from a previously determined value by a predetermined amount. The first conductive element and the second conductive element may be sandwiched between two layers comprising the structure. The structure may comprise a shipping container floor. The detected breach may comprise an opening greater than nine square inches.Georgia Tech Research Corporatio

    RIDA: Robust Intrusion Detection in Ad Hoc Networks

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    We focus on detecting intrusions in wireless ad hoc networks using the misuse detection technique. We allow for detection modules that periodically fail to detect attacks and also generate false positives. Combining theories of hypothesis testing and approximation algorithms, we develop a framework to counter different threats while minimizing the resource consumption. We obtain computationally simple optimal rules for aggregating and thereby minimizing the errors in the decisions of the nodes executing the intrusion detection software (IDS) modules. But, we show that the selection of the optimal set of nodes for executing the IDS is an NP-hard problem. We present a polynomial complexity selection algorithm that attains a guaranteeable approximation bound. We also modify this algorithm to allow for seamless operation in time varying topologies, and evaluate the efficacy of the approximation algorithm and its modifications using simulation. We identify a selection algorithm that attains a good balance between performance and complexity for attaining robust intrusion detection in ad hoc networks
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