Security
Biometric-based hand modality is considered as one of the most popular biometric technologies especially in forensic applications. Hand recognition is an active research topic in recent years and in order to promote hand’s recognition research, the REGIM-Lab.: REsearch Groups in Intelligent Machines, ENIS, University of Sfax, Tunisia provides the REgim Sfax Tunisian hand database (REST database) freely of charge to mainly hand and palmprint recognition researchers.
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Data set of 26/11 Mumbai attack is based on Mumbai Terrorist Attacks 2008 India Ministry of External Affairs Dossier and News reports. 10 terrorist operated in India distributed in five sub-groups, simultaneously 3 other person comes in light as per report those were having in continue touch with these terrorist from Pakistan and giving them instructions.
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A dataset of LDoS attacks against bottleneck links in software-defined networks. LDoS attacks are based on a flawed implementation of the TCP congestion control mechanism and can seriously affect legitimate traffic on bottlenecked or shared links in software-defined networks.
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This dataset contains RF signals from drone remote controllers (RCs) of different makes and models. The RF signals transmitted by the drone RCs to communicate with the drones are intercepted and recorded by a passive RF surveillance system, which consists of a high-frequency oscilloscope, directional grid antenna, and low-noise power amplifier. The drones were idle during the data capture process. All the drone RCs transmit signals in the 2.4 GHz band. There are 17 drone RCs from eight different manufacturers and ~1000 RF signals per drone RC, each spanning a duration of 0.25 ms.
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This is for BGP anomaly analysis
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Gaming consoles are very common connected devices which have evolved in functionality and applications (games and beyond) they support. This diversity of traffic generated from these consoles has diverse quality of service (QoS) requirements. However, in order to offer diverse QoS, ISPs and operators must be able to classify this traffic. To enable research in traffic classification (Machine Learning based or other), we have generated and collected this dataset. This is a labelled dataset collected from a gaming console, PlayStation 4.
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The data are four Xilinx ISE projects for Montgomery modualr multiplication and modular exponentiation.
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The CHU Surveillance Violence Dataset (CSVD) is a collection of CCTV footage of violent and non-violent actions aiming to characterize the composition of violent actions into more specific actions. We produced several simple action classes for violent and non-violent actions do add variety and better distribution among simple and complex action classes for RGB and Action Silhouette Videos (enhanced Optical Flow Images) with their localized actions.
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Due to the large number of vulnerabilities in information systems and the continuous activity of attackers, techniques for malicious traffic detection are required to identify and protect against cyber-attacks. Therefore, it is important to intentionally operate a cyber environment to be invaded and compromised in order to allow security professionals to analyze the evolution of the various attacks and exploited vulnerabilities.
This dataset includes 2016, 2017 and 2018 cyber attacks in the HoneySELK environment.
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