Security
Future wireless networks must incorporate awareness, adaptability, and intelligence as fundamental building elements in order to meet the wide range of requirements of the next-generation communication systems. Wireless sensing techniques can be used to gather awareness from the radio signals present in the surroundings. However, threats from hostile attackers, such as jamming, eavesdropping, and manipulation, are also present along with this. This paper describes in detail an RF-jamming detection test-bed and provides experimentally measured data.
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A real-world radio frequency (RF) fingerprinting dataset for commercial off-the-shelf (COTS) Bluetooth and WiFi emitters under challenging testbed setups is presented in this dataset. The chipsets within the devices (2 laptops and 8 commercial chips) are WiFi-Bluetooth combo transceivers. The emissions are captured with a National Instruments Ettus USRP X300 radio outfitted with a UBX160 daughterboard and a VERT2450 antenna. The receiver is tuned to record a 66.67 MHz bandwidth of the spectrum centered at the 2.414 GHz frequency.
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Microarchitectural attacks have become more threatening the society than before with the increasing diversity of attacks such as Spectre and Meltdown. Vendor patches cannot keep up with the pace of the new threats, which makes the dynamic anomaly detection tools more evident than before. Unfortunately, hardware performance counters (HPCs) utilized in previous works lead to high performance overhead and detection of a few microarchitectural attacks due to the small number of counters that can be profiled concurrently.
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The dataset includes processed sequences of optical time domain reflectometry (OTDR) traces incorporating different types of fiber faults namely fiber cut, fiber eavesdropping (fiber tapping), dirty connector and bad splice. The dataset can be used for developping ML-based approaches for optical fiber fault detection, localization, idenification, and characterization.
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CalibDB is a database collected and organized by the PKVIC tool,
which is part of the work of paper "Supplement Missing Software Package Information in Security Vulnerability Reports"
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Calculations to compute the expected Bitcoin transaction efficiency (measured in transactions per block) using CRYSTALS-Dilithium vs using Elliptic Curve Digital Signature Algorithm (ECDSA).
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To determine the effectiveness of any defense mechanism, there is a need for comprehensive real-time network data that solely references various attack scenarios based on older software versions or unprotected ports, and so on. This presented dataset has entire network data at the time of several cyber attacks to enable experimentation on challenges based on implementing defense mechanisms on a larger scale. For collecting the data, we captured the network traffic of configured virtual machines using Wireshark and tcpdump.
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The evolution of the Industrial Internet of Things (IIoT) introduces several benefits, such as real-time monitoring, pervasive control and self-healing. However, despite the valuable services, security and privacy issues still remain given the presence of legacy and insecure communication protocols like IEC 60870-5-104. IEC 60870-5-104 is an industrial protocol widely applied in critical infrastructures, such as the smart electrical grid and industrial healthcare systems.
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SCVIC-CIDS-2021 was created using the raw data in CIC-IDS-2018*, while this new dataset, SCVIC-CIDS-2022 is formed from NDSec-1** meta-data by following a similar procedure.
This dataset has been used in the following work:
J. Liu, M. Simsek, B. Kantarci, M. Bagheri, P. Djukic, "Bridging Networks and Hosts via Machine Learning-Based Intrusion Detection"; under review in IEEE Transactions on Dependable and Secure Computing.
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