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Fingerprinting Wi-Fi Devices Using Software Defined Radios
2016
Proceedings of the 9th ACM Conference on Security & Privacy in Wireless and Mobile Networks - WiSec '16
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In this work, we show that RF fingerprinting of Wi-Fi devices is feasible using commodity software defined radio platforms. ...
In order to assess the potential of the proposed techniques on similar devices, we used 3 sets of 26 Wi-Fi devices of identical model. ...
This material is based upon work supported by the National Science Foundation under Grant No. NSF/CNS-1409453. ...
doi:10.1145/2939918.2939936
dblp:conf/wisec/Vo-HuuVN16
fatcat:fmdzdyg7nnelllm6rayxllvqkq
Fingerprinting Software-Defined Networks
2015
2015 IEEE 23rd International Conference on Network Protocols (ICNP)
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Introduction • Software-defined networking (SDN): • Separates data plane from control plane. • Software controls the network. • Packet processing • Fast at data plane (hardware) • Slow at control plane ...
SDN Controller
Problem Statement • Feasibility of fingerprinting an SDN network? • Accuracy of fingerprinting an SDN network? • Impact of number of switches in an SDN network? ...
. • Harms network performance • Delay the first few packets of old flows. • Minor impact on network performance. • The amount of delay can be determined from our observations. • Obscure attacker whether ...
doi:10.1109/icnp.2015.26
dblp:conf/icnp/BifulcoCKK15
fatcat:ss2d55owwjh77deg6pakxans5y
SoftMF: A Software Defined Moving Fingerprinting Framework for Proactive Security Policies Enforcement
2016
DEStech Transactions on Engineering and Technology Research
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This work combines flow watermarking with software-defined technology to propose a novel watermarking-based dynamic fingerprinting framework, called SoftMF (Software-defined Moving Fingerprinting), which ...
Networks such as in campuses and enterprises are suffering enormous attacks and threats. ...
One is flow table that defines the common network actions and the other is fingerprint table that defines the MF-based security actions. ...
doi:10.12783/dtetr/iect2016/3816
fatcat:vzzretpxrnhhpde4ytvv25rcna
Fingerprinting Software-defined Networks
[article]
2015
arXiv
pre-print
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Software-defined networking (SDN) eases network management by centralizing the control plane and separating it from the data plane. ...
Our results demonstrate the effectiveness of our countermeasure in deterring fingerprinting attacks on SDN networks. ...
ACKNOWLEDGMENTS This research was partly performed within the 5G-ENSURE project (www.5GEnsure.eu) and received funding from the EU Framework Programme for Research and Innovation Horizon 2020 under grant ...
arXiv:1512.06585v1
fatcat:lzh3c2z7sjak5oq6xjltam5vxu
Smart in-network deduplication for storage-aware SDN
2013
Proceedings of the ACM SIGCOMM 2013 conference on SIGCOMM - SIGCOMM '13
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In order to efficiently handle the rapid growth of data and reduce the overhead of network transmission, we propose an in-network deduplication for storage-aware Software Defined Network (SDN), called ...
Experimental results demonstrate the efficiency and efficacy of SMIND. ...
Software defined network (SDN) [4, 5] offers an opportunity to implement an in-network deduplication. The in-network scheme allows the deduplication to be executed within the network. ...
doi:10.1145/2486001.2491714
dblp:conf/sigcomm/HuaLF13
fatcat:7irqyxnnnbe6thrn4omoskq7yq
Smart in-network deduplication for storage-aware SDN
2013
Computer communication review
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In order to efficiently handle the rapid growth of data and reduce the overhead of network transmission, we propose an in-network deduplication for storage-aware Software Defined Network (SDN), called ...
Experimental results demonstrate the efficiency and efficacy of SMIND. ...
Software defined network (SDN) [4, 5] offers an opportunity to implement an in-network deduplication. The in-network scheme allows the deduplication to be executed within the network. ...
doi:10.1145/2534169.2491714
fatcat:5h4dahvfsba23i7npvlmagy36m
Integrated Software Fingerprinting via Neural-Network-Based Control Flow Obfuscation
2016
IEEE Transactions on Information Forensics and Security
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Leveraging the rich entropy in the outputs of these neural networks, Neuroprint embeds software fingerprints such that a one-time construction of the networks serves both purposes of obfuscation and fingerprinting ...
We then provide the first implementation of integrated fingerprinting called Neuroprint on top of a control flow obfuscator that replaces program's conditional structures with neural networks trained to ...
the designing of software fingerprinting. ...
doi:10.1109/tifs.2016.2555287
fatcat:lweugzs5pzhltpf3dfi42hzm4e
Attacking software-defined networks
2013
Proceedings of the second ACM SIGCOMM workshop on Hot topics in software defined networking - HotSDN '13
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In this paper, for the first time we show a new attack to fingerprint SDN networks and further launch efficient resource consumption attacks. ...
We provide the first feasibility study of such attack and hope to stimulate further studies in SDN security research. ...
INTRODUCTION In this work, we demonstrate an effective and efficient attack against software-defined networks with the knowledge of some basic characteristics of the SDN technology. ...
doi:10.1145/2491185.2491220
dblp:conf/sigcomm/ShinG13
fatcat:mac34lblo5a7tb4o5kov6ru3zy
ETGuard: Detecting D2D Attacks using Wireless Evil Twins
2019
Computers & security
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2019 pre-print arXiv:1903.05843v1 fatcat:yiiwnryyenajffmmjvs46iip5a
The fingerprints are constructed from the beacon frames transmitted by the wireless APs periodically to inform client devices of their presence and capabilities in a network. ...
We configure an ET to launch a malicious component of an already installed app in the device on submission of the portal page. ...
The fingerprint of the AP is constructed as:
• Unregistered on the network If the extracted fingerprint does not match with any of the stored fingerprints, ETGuard compares the SSID to confirm intention ...
doi:10.1016/j.cose.2019.02.014
fatcat:vg3h63grzveixmazkdqtecdqlu
Fingerprint Recognition System Using Artificial Neural Network as Feature Extractor: Design and Performance Evaluation
2016
Tatra Mountains Mathematical Publications
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Problems start to arise in low quality conditions where majority of the traditional methods based on analyzing texture of fingerprint cannot tackle this problem so effectively as artificial neural networks ...
The result of this research is a fully functional software system for fingerprint recognition that consists of fingerprint sensing module using high resolution sensor, image enhancement module responsible ...
Figure 7 on the page 128 shows the screens of graphical user interface of our software.
Neural network training We used two instances of neural networks in our software. ...
doi:10.1515/tmmp-2016-0035
fatcat:dqkawpizkjg3ro75qbrpuhzqk4
A Technique of Fingerprint Recognition using Artificial Neural Network
2018
International Journal of Electronics Communication & Instrumentation Engineering Research and Development
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Firstly we used filter and histogram process of the input image than we trained artificial neural network on the input image. ...
This paper is present fingerprint recognition with the technique of artificial neural network. Fingerprint is widely accepted for personnel identification. ...
Circularity of the shape of the region is defined by the value of compactness, M, as defined using the following equation. ...
doi:10.24247/ijecierdfeb20181
fatcat:m2pjbrtvw5hjrpkoralykqk2bq
Towards Improving the NIST Fingerprint Image Quality (NFIQ) Algorithm (Extended Version)
[article]
2010
arXiv
pre-print
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In this publication, we report on our efforts to optimize the NFIQ algorithm by a re-training of the underlying neural network based on a large fingerprint image database. ...
The NIST Fingerprint Image Quality (NFIQ) algorithm has become a standard method to assess fingerprint image quality. ...
Defining the Normalized Match Score The definition of NIST for the normalized match score (1) was based on the limitation that only one genuine score is available per fingerprint. ...
arXiv:1008.0781v2
fatcat:hlsnzkjc7fcc5jieqo6xakdx64
DCNN Architecture Based Accurate Fingerprint Model Localization for Massive MIMO-OFDM System
2020
International journal of recent technology and engineering
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In this essay discuss the origin of the vast multifaceted frequency-division (OFDM) multiplexing structures with deep-convolution neural networks (DCNNs) centered on the fingerprint. ...
A DCNN-enabled localization method is then proposed to overcome the modeling error for calculating fingerprint similarity. The definition of DCNN is known as well as DCNN regression. ...
Deep convolution neural networks (DCNNs) are trained based on identified fingerprints in the database and a fingerprint clustering hierarchy is defined.
III. ...
doi:10.35940/ijrte.e7020.018520
fatcat:ll6oqe6zfrfzdpipm3jwmz7ply
A Prototype of Fingerprint and ZigBee Based Train Ignition System
2012
Advanced Engineering Forum
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Fingerprints are the most widely used form of biometric identification overtime and the critical step in exploring its advantages is to adopt it for use as a form of security in already existing systems ...
At present, number of vehicles is successfully implementing fingerprint system for authentic ignition. By this system unauthorized accessing of the train or mishandlings can be avoided. ...
Software: The program codes driving the fingerprint recognition software for ignition system control was written in visual basic and ran on a PC. ...
doi:10.4028/www.scientific.net/aef.6-7.1129
fatcat:qnmsmgi43vc35bdi76ibulkh7y
Fingerprint recognition based on collected images using deep learning technology
2022
IAES International Journal of Artificial Intelligence (IJ-AI)
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However, during the scanning process of the fingerprint, the generated image using the fingerprint scanner may differ slightly during each scan. ...
This paper proposes an efficient matching model for fingerprint authentication using deep learning based deep convolutional neural network (CNN or ConvNet). ...
Software part of the CNN The basic steps of the software part of the fingerprint identification system using CNN based multi layers are presented in flowchart in Figure 6 . ...
doi:10.11591/ijai.v11.i1.pp81-88
fatcat:c5slp3hscbhy3isbwsyxbvhgba
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