Abstract:<p>Jamming attacks significantly degrade the performance of wireless communication systems and can lead to significant overhead in terms of re-transmissions and increased power consumption. Although different jamming techniques are discussed in the literature, numerous open-source implementations have used expensive equipment in the range of thousands of dollars with the exception of a few. These implementations have also tended to be partial band, and do not cover the whole available bandwidth of the sy… Show more
“…In this section, we will first discuss the testbed design based on the jamming signal generated by the JamRF toolkit [3]. Next, we discuss how to implement the testbed design specified.…”
Section: Testbed Design and Implementationmentioning
confidence: 99%
“…The basic idea behind the testbed is to carry out jamming based on JamRF [3] implementation of a broadband jammer that can jam a portion of the spectrum thereby disrupting or corrupting user data. Here, by employing the JamRF toolkit, we jam all the available 2.4/5GHz channels sequentially.…”
Section: A Testbed Design Based On Jamrfmentioning
confidence: 99%
“…HackRF One is compatible with popular softwaredefined radio applications such as GNU Radio and SDR#. As described in Section II, we employ JamRF which is a jamming toolkit that implements different types of jammers and jammer strategies using HackRF and GNU radio [3].…”
Section: B Testbed Implementationmentioning
confidence: 99%
“…In contrast, intentional interference refers to hostile attacks on a victim receiver that is not in defensive mode [2]. In particular, the jamming attack is an active adversary attack that transmits energy to disrupt reliable data transmission or reception, and can drastically degrade system performance [3].…”
Section: Introductionmentioning
confidence: 99%
“…In contrast to earlier efforts, we provide an experimental testbed for performing spectrum scanning using the in-built wide local area network (WLAN) interface cards (NICs) of communication devices to collect data in different environments. Furthermore, using the testbed, we employ JamRF 2 a jamming toolkit developed in [3], we synthesize different jamming scenarios to generate RF jamming dataset. Particularly, we describe the methodology used for the development of the testbed and discuss the reasons behind the choices taken during its development to facilitate future improvement in the experimental exploration of jamming dataset production based on the spectral scan.…”
<p>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 testbed and provides experimentally measured data. The RF jamming detection testbed, in particular, makes use of the spectral scan capability of wireless network interfaces and JamRF, a jamming toolkit. In order to facilitate future progress in the experimentation of jamming detection and avoidance systems, we explain the methodology used for the development of our testbed and discuss the reasoning behind the choices made throughout its evolution. Furthermore, we provide various types of measurement data obtained with the testbed. The data set is expected to facilitate and promote the experimental evaluation of jamming detection, jamming avoidance, and anti-jamming schemes developed by the wireless security community. As an illustration, we trained five different machine learning algorithms and got results with an overall jamming detection accuracy of more than 90% for all algorithms.</p>
“…In this section, we will first discuss the testbed design based on the jamming signal generated by the JamRF toolkit [3]. Next, we discuss how to implement the testbed design specified.…”
Section: Testbed Design and Implementationmentioning
confidence: 99%
“…The basic idea behind the testbed is to carry out jamming based on JamRF [3] implementation of a broadband jammer that can jam a portion of the spectrum thereby disrupting or corrupting user data. Here, by employing the JamRF toolkit, we jam all the available 2.4/5GHz channels sequentially.…”
Section: A Testbed Design Based On Jamrfmentioning
confidence: 99%
“…HackRF One is compatible with popular softwaredefined radio applications such as GNU Radio and SDR#. As described in Section II, we employ JamRF which is a jamming toolkit that implements different types of jammers and jammer strategies using HackRF and GNU radio [3].…”
Section: B Testbed Implementationmentioning
confidence: 99%
“…In contrast, intentional interference refers to hostile attacks on a victim receiver that is not in defensive mode [2]. In particular, the jamming attack is an active adversary attack that transmits energy to disrupt reliable data transmission or reception, and can drastically degrade system performance [3].…”
Section: Introductionmentioning
confidence: 99%
“…In contrast to earlier efforts, we provide an experimental testbed for performing spectrum scanning using the in-built wide local area network (WLAN) interface cards (NICs) of communication devices to collect data in different environments. Furthermore, using the testbed, we employ JamRF 2 a jamming toolkit developed in [3], we synthesize different jamming scenarios to generate RF jamming dataset. Particularly, we describe the methodology used for the development of the testbed and discuss the reasons behind the choices taken during its development to facilitate future improvement in the experimental exploration of jamming dataset production based on the spectral scan.…”
<p>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 testbed and provides experimentally measured data. The RF jamming detection testbed, in particular, makes use of the spectral scan capability of wireless network interfaces and JamRF, a jamming toolkit. In order to facilitate future progress in the experimentation of jamming detection and avoidance systems, we explain the methodology used for the development of our testbed and discuss the reasoning behind the choices made throughout its evolution. Furthermore, we provide various types of measurement data obtained with the testbed. The data set is expected to facilitate and promote the experimental evaluation of jamming detection, jamming avoidance, and anti-jamming schemes developed by the wireless security community. As an illustration, we trained five different machine learning algorithms and got results with an overall jamming detection accuracy of more than 90% for all algorithms.</p>
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