Browsing by Author "Kanhere, Salil S."
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- An Experimental Study for Tracking Crowd in Smart CitiesPublication . Li, Kai; Yuen, Chan; Kanhere, Salil S.; Hu, Kun; Zhang, Wei; Jiang, Fan; Liu, XiangKnowledge about people density and mobility patterns is the key element toward efficient urban development in smart cities. The main challenges in large-scale people tracking are the recognition of people density in a specific area and tracking the people flow path. To address these challenges, we present SenseFlow, a lightweight people tracking system for smart cities. SenseFlow utilizes off-the-shelf sensors that sniff probe requests periodically polled by user’s smartphones in a passive manner. We demonstrate the feasibility of SenseFlow by building a proof-of-concept prototype and undertaking extensive evaluations in real-world settings. We deploy the system in one laboratory to study office hours of researchers, a crowded public area in a city to evaluate the scalability and performance “in the wild,” and four classrooms in the university to monitor the number of students. We also evaluate SenseFlow with varying walking speeds and different models of smartphones to investigate the people flow tracking performance.
- Eavesdropping and Jamming Selection Policy for Suspicious UAVs Based on Low Power Consumption over Fading ChannelsPublication . Wang, Xiaoming; Li, Demin; Guo, Chang; Zhang, Xiaolu; Kanhere, Salil S.; Li, Kai; Tovar, EduardoTraditional wireless security focuses on preventing unmanned aerial vehicle (UAV) communications from suspicious eavesdropping and/or jamming attacks. However, there is a growing need for governments to keep malicious UAV communications under legitimate surveillance. This paper first investigates a new surveillance paradigm for monitoring suspicious UAV communications via jamming suspicious UAVs. Due to the power consumption limitation, the choice of eavesdropping and jamming will reflect the performance of the UAVs communication. Therefore, the paper analyses the UAV’s eavesdropping and jamming models in different cases, and then proposes the model to optimize the data package in the constraints of lower power consumption, which can be solved by the proposed selection policy. The simulation results validate our proposed selection policy in terms of power consumption and eavesdropped packets. In different fading models, power consumption increases with time, regardless of distances, and our proposed policy performs better in Weibull fading channels in terms of eavesdropped packets.
- Energy Efficient Legitimate Wireless Surveillance of UAV CommunicationsPublication . Li, Kai; Voicu, Razvan Christian; Kanhere, Salil S.; Ni, Wei; Tovar, EduardoUnmanned aerial vehicles (UAVs) enhance connectivity and accessibility for civilian and military applications. Criminals or terrorists can potentially use UAVs for committing crimes and terrorism, thus endangering public safety. In this paper, we consider that a legitimate UAV is employed to track flight of suspicious UAVs for preventing safety and security threats. To obtain flight information of the suspicious UAVs, the legitimate UAV intentionally jams the suspicious receiver so as to force the suspicious UAV to reduce its data rate, and hence increase the eavesdropping success. An energy-efficient jamming strategy is proposed for the legitimate UAV to maximize the amount of eavesdropped packets. Moreover, a tracking algorithm is developed for the legitimate UAV to track the suspicious flight by comprehensively utilizing eavesdropped packets, angle-of-arrival and received signal strength of the suspicious transmitter's signal. A new simulation framework is implemented to combine the complementary features of optimization toolbox with channel modeling (in MATLAB) and discrete event-driven mobility tracking (in NS3). Moreover, numerical results validate the proposed algorithms in terms of packet eavesdropping rate and tracking accuracy of the suspicious UAVs’ trajectory.
- PELE: Power Efficient Legitimate Eavesdropping via Jamming in UAV CommunicationsPublication . Wang, Xiaoming; Li, Kai; Kanhere, Salil S.; Li, Demin; Zhang, Xiaolu; Tovar, EduardoWe consider a wireless information surveillance in UAV network, where a legitimate unmanned aerial vehicle (UAV) proactively eavesdrops communication between two suspicious UAVs. However, challenges arise due to lossy airborne channels and limited power of the UAV. In this paper, we study an emerging legitimate eavesdropping paradigm that the legitimate UAV improves the eavesdropping performance via jamming the suspicious communication. Moreover, a power efficient legitimate eavesdropping scheme, PELE, is proposed to maximize the number of eavesdropped packets from the legitimate UAV while maintaining a target signal to interference plus noise ratio at the suspicious link. Numerical results are shown to validate the performance of PELE. Additionally, four typical fading channel models are applied to the network so as to investigate their impact on PELE.
- Proactive Eavesdropping via Jamming for Trajectory Tracking of UAVsPublication . Li, Kai; Kanhere, Salil S.; Ni, Wei; Tovar, Eduardo; Guizani, MohsenThis paper considers that a legitimate UAV tracks suspicious UAVs’ flight for preventing intended crimes and terror attacks. To enhance tracking accuracy, the legitimate UAV proactively eavesdrops suspicious UAVs’ communication via sending jamming signals. A tracking algorithm is developed for the legitimate UAV to track the suspicious flight by comprehensively utilizing eavesdropped packets, angle-of-arrival and received signal strength of the suspicious transmitter’s signal. A new co-simulation framework is implemented to combine the complementary features of optimization toolbox with channel modeling (in Matlab) and discrete event-driven mobility tracking (in NS3). Moreover, numerical results validate the proposed algorithms in terms of tracking accuracy of the suspicious UAVs’ trajectory