LTE radio analytics made easy and accessible

Kumar, Swarun; Hamed, Ezzeldin; Katabi, Dina; Li, Li Erran

doi:10.1145/2619239.2626320

Cited by 85 publications

(64 citation statements)

References 15 publications

(14 reference statements)

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“…SAR has been widely used for radar imaging [9,17] and indoor positioning [19,18,36,12]. In contrast, this paper builds upon SAR to provide cyber-security to multi-robot networks.…”

Section: Related Workmentioning

confidence: 99%

Guaranteeing Spoof-Resilient Multi-Robot Networks

Gil

Kumar

Mazumder

et al. 2015

Robotics: Science and Systems XI

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Abstract-Multi-robot networks use wireless communication to provide wide-ranging services such as aerial surveillance and unmanned delivery. However, effective coordination between multiple robots requires trust, making them particularly vulnerable to cyber-attacks. Specifically, such networks can be gravely disrupted by the Sybil attack, where even a single malicious robot can spoof a large number of fake clients. This paper proposes a new solution to defend against the Sybil attack, without requiring expensive cryptographic key-distribution. Our core contribution is a novel algorithm implemented on commercial Wi-Fi radios that can "sense" spoofers using the physics of wireless signals. We derive theoretical guarantees on how this algorithm bounds the impact of the Sybil Attack on a broad class of robotic coverage problems. We experimentally validate our claims using a team of AscTec quadrotor servers and iRobot Create ground clients, and demonstrate spoofer detection rates over 96%.

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“…SAR has been widely used for radar imaging [9,17] and indoor positioning [19,18,36,12]. In contrast, this paper builds upon SAR to provide cyber-security to multi-robot networks.…”

Section: Related Workmentioning

confidence: 99%

Guaranteeing Spoof-Resilient Multi-Robot Networks

Gil

Kumar

Mazumder

et al. 2015

Robotics: Science and Systems XI

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“…The additional information that extra antennas provide can be used to determine the arrival angle of the radio waves. Along with MIMO systems, Synthetic-aperture Radar (SAR) is used in radiolocation techniques to simulate the MIMO design by moving the antenna [36,37,38,39]. The movement of the antenna during the signal reception augments the received information;…”

Section: Radiolocation Techniques Based On Angle Of Arrival Measurementsmentioning

confidence: 99%

A grid-based indoor radiolocation technique based on spatially coherent path loss model

Ambarkutuk

Furukawa

2017

2017 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI)

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(Academic)This thesis presents a grid-based indoor radiolocation technique based on a Spatially Coherent Path Loss Model (SCPL). SCPL is a path loss model which characterizes the radio wave propagation in an environment by solely using Received Signal Strength (RSS) fingerprints. The propagation of the radio waves is characterized by uniformly dividing the environment into grid cells, followed by the estimation of the propagation parameters for each grid cell individually. By using SCPL and RSS fingerprints acquired at an unknown location, the distance between an agent and all the access point in an indoor environment can be determined. A least-squares based trilateration is then used as the global fix of location the agent in the environment. The result of the trilateration is then represented in a probability distribution function over the grid cells induced by SCPL. Since the proposed technique is able to locally model the propagation accounting for attenuation of non-uniform environmental irregularities, the characterization of the path loss in the indoor environment This thesis presents a technique uses radio waves to localize an agent in an indoor environment. By characterizing the difference between transmitted and received power of the radio waves, the agent can determine how far it is away from the transmitting antennas, i.e. DedicationTo my loving parents, lovely sister, and my precious friend Isil Anakok.iv

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“…To the best of our knowledge the first non-commercial attempt to decode LTE control information has been LT-Eye [10]: DCI messages are not encrypted, but only the intended receiver can verify the successful decoding, because the CRC field of the message is scrambled (binary exclusive OR operation) with the UE's RNTI. To decode DCIs without knowledge of the destination RNTI, LTEye, first, assumes the decoding to be successful, then obtain the destination RNTI from the CRC field of the message XORed with the CRC computed on the decoded data.…”

Section: Related Workmentioning

confidence: 99%

Owl

Bui

Widmer

2016

Proceedings of the 5th Workshop on All Things Cellular: Operations, Applications and Challenges

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Reliable network measurements are a fundamental component of networking research as they enable network analysis, system debugging, performance evaluation and optimization. In particular, decoding the LTE control channel would give access to the full base station traffic at a 1 ms granularity, thus allowing for traffic profiling and accurate measurements. Although a few open-source implementations of LTE are available, they do not provide tools to reliably decoding the LTE control channel and, thus, accessing the scheduling information. In this paper, we present OWL, an Online Watcher for LTE that is able to decode all the resource blocks in more than 99% of the system frames, significantly outperforming existing non-commercial prior decoders. Compared to previous attempts, OWL grounds the decoding procedure on information obtained from the LTE random access mechanism. This makes it possible to run our software on inexpensive hardware coupled with almost any software defined radio capable of sampling the LTE signal with sufficient accuracy.

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LTE radio analytics made easy and accessible

Cited by 85 publications

References 15 publications

Guaranteeing Spoof-Resilient Multi-Robot Networks

Guaranteeing Spoof-Resilient Multi-Robot Networks

A grid-based indoor radiolocation technique based on spatially coherent path loss model

Owl

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