Security
Five well-known Border Gateway Anomalies (BGP) anomalies:
WannaCrypt, Moscow blackout, Slammer, Nimda, Code Red I, occurred in May 2017, May 2005, January 2003, September 2001, and July 2001, respectively.
The Reseaux IP Europeens (RIPE) BGP update messages are publicly available from the Network Coordination Centre (NCC) and contain:
WannaCrypt, Moscow blackout, Slammer, Nimda, Code Red I, and regular data: https://www.ripe.net/analyse/.
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1. Folder “1.SlibCrypto 4DIAC project” includes 4DIAC (1.10.3) project that can be added into the workspace of 4DIAC. It contains the various standalone applications representing security mechanisms and the extended one shown in Fig. 5.
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BS-HMS-Dataset is a dataset of the users' brainwave signals and the corresponding hand movement signals from a large number of volunteer participants. The dataset has two parts; (1) Neurosky based Dataset (collected over several months in 2016 from 32 volunteer participants), and (2) Emotiv based Dataset (collected from 27 volunteer participants over several months in 2019).
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Normal
0
false
false
false
EN-US
X-NONE
AR-SA
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The dataset contains measurement results of Radar Cross Section of different Unmanned Aerial Vehicles at 26-40 GHz. The measurements have been performed fro quasi-monostatic case (when the transmitter and receiver are spatially co-located) in the anechoic chamber. The data shows how radio waves are scattered by different UAVs at the specified frequency range.
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The proliferation of IoT systems, has seen them targeted by malicious third parties. To address this challenge, realistic protection and investigation countermeasures, such as network intrusion detection and network forensic systems, need to be effectively developed. For this purpose, a well-structured and representative dataset is paramount for training and validating the credibility of the systems. Although there are several network datasets, in most cases, not much information is given about the Botnet scenarios that were used.
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One of the major research challenges in this field is the unavailability of a comprehensive network based data set which can reflect modern network traffic scenarios, vast varieties of low footprint intrusions and depth structured information about the network traffic. Evaluating network intrusion detection systems research efforts, KDD98, KDDCUP99 and NSLKDD benchmark data sets were generated a decade ago. However, numerous current studies showed that for the current network threat environment, these data sets do not inclusively reflect network traffic and modern low footprint attacks.
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The modified CASIA dataset is created for research topics like: perceptual image hash, image tampering detection, user-device physical unclonable function and so on.
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Dataset contains ten days real-world DNS traffic captured from campus network comprising of 4000 hosts in peak load hours. Dataset also contains labelled features.
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This dataset is in support of my 3 research papers - 'Comparative SoC Analysis using Non-Linear Kalman Estimation in 8RC ECM of 72Ah LIB - Part I', ' Comparative SoC Analysis using Non-Linear Kalman Estimation in 8RC ECM of 72Ah LIB - Part II' , and 'Comparative SoC Analysis using Non-Linear Kalman Estimation in 8RC ECM of 72Ah LIB - Part III'.
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