Do you want to publish a course? Click here

CLIMEX: A Wireless Physical Layer Security Protocol Based on Clocked Impulse Exchanges

81   0   0.0 ( 0 )
 Added by Satyam Dwivedi
 Publication date 2017
and research's language is English




Ask ChatGPT about the research

A novel method and protocol establishing common secrecy based on physical parameters between two users is proposed. The four physical parameters of users are their clock frequencies, their relative clock phases and the distance between them. The protocol proposed between two users is backed by theoretical model for the measurements. Further, estimators are proposed to estimate secret physical parameters. Physically exchanged parameters are shown to be secure by virtue of their non-observability to adversaries. Under a simplified analysis based on a testbed settings, it is shown that 38 bits of common secrecy can be derived for one run of the proposed protocol among users. The method proposed is also robust against various kinds of active timing attacks and active impersonating adversaries.



rate research

Read More

Consider impersonation attack by an active malicious nano node (Eve) on a diffusion based molecular communication (DbMC) system---Eve transmits during the idle slots to deceive the nano receiver (Bob) that she is indeed the legitimate nano transmitter (Alice). To this end, this work exploits the 3-dimensional (3D) channel impulse response (CIR) with $L$ taps as device fingerprint for authentication of the nano transmitter during each slot. Specifically, Bob utilizes the Alices CIR as ground truth to construct a binary hypothesis test to systematically accept/reject the data received in each slot. Simulation results highlight the great challenge posed by impersonation attack--i.e., it is not possible to simultaneously minimize the two error probabilities. In other words, one needs to tolerate on one error type in order to minimize the other error type.
Network-connected unmanned aerial vehicle (UAV) communications is a common solution to achieve high-rate image transmission. The broadcast nature of these wireless networks makes this communication vulnerable to eavesdropping. This paper considers the problem of compressed secret image transmission between two nodes, in the presence of a passive eavesdropper. In this paper, we use auto encoder/decoder convolutional neural networks, which by using deep learning algorithms, allow us to compress/decompress images. Also we use network physical layer features to generate high rate artificial noise to secure the data. Using features of the channel with applying artificial noises, reduce the channel capacity of the unauthorized users and prevent eavesdropper from detecting received data. Our simulation experiments show that for received data with SNR fewer than 5 in the authorized node, the MSE is less than 0.05.
Secure and scalable device provisioning is a notorious challenge in Wi-Fi. WPA2/WPA3 solutions take user interaction and a strong passphrase for granted. However, the often weak passphrases are subject to guessing attacks. Notably, there has been a significant rise of cyberattacks on Wi-Fi home or small office networks during the COVID-19 pandemic. This paper addresses the device provisioning problem in Wi-Fi (personal mode) and proposes ComPass protocol to supplement WPA2/WPA3. ComPass replaces the pre-installed or user-selected passphrases with automatically generated ones. For this, ComPass employs Physical Layer Security and extracts credentials from common random physical layer parameters between devices. Two major features make ComPass unique and superior compared to previous proposals: First, it employs phase information (rather than amplitude or signal strength) to generate the passphrase so that it is robust, scaleable, and impossible to guess. Our analysis showed that ComPass generated passphrases have 3 times more entropy than human generated passphrases (113-bits vs. 34-bits). Second, ComPass selects parameters such that two devices bind only within a certain proximity (less than 3m), hence providing practically useful in-build PLS-based authentiation. ComPass is available as a kernel module or as full firmware.
In this preliminary work, we study the problem of {it distributed} authentication in wireless networks. Specifically, we consider a system where multiple Bob (sensor) nodes listen to a channel and report their {it correlated} measurements to a Fusion Center (FC) which makes the ultimate authentication decision. For the feature-based authentication at the FC, channel impulse response has been utilized as the device fingerprint. Additionally, the {it correlated} measurements by the Bob nodes allow us to invoke Compressed sensing to significantly reduce the reporting overhead to the FC. Numerical results show that: i) the detection performance of the FC is superior to that of a single Bob-node, ii) compressed sensing leads to at least $20%$ overhead reduction on the reporting channel at the expense of a small ($<1$ dB) SNR margin to achieve the same detection performance.
In this paper, we introduce an intelligent reflecting surface (IRS) to provide a programmable wireless environment for physical layer security. By adjusting the reflecting coefficients, the IRS can change the attenuation and scattering of the incident electromagnetic wave so that it can propagate in a desired way toward the intended receiver. Specifically, we consider a downlink multiple-input single-output (MISO) broadcast system where the base station (BS) transmits independent data streams to multiple legitimate receivers and keeps them secret from multiple eavesdroppers. By jointly optimizing the beamformers at the BS and reflecting coefficients at the IRS, we formulate a minimum-secrecy-rate maximization problem under various practical constraints on the reflecting coefficients. The constraints capture the scenarios of both continuous and discrete reflecting coefficients of the reflecting elements. Due to the non-convexity of the formulated problem, we propose an efficient algorithm based on the alternating optimization and the path-following algorithm to solve it in an iterative manner. Besides, we show that the proposed algorithm can converge to a local (global) optimum. Furthermore, we develop two suboptimal algorithms with some forms of closed-form solutions to reduce the computational complexity. Finally, the simulation results validate the advantages of the introduced IRS and the effectiveness of the proposed algorithms
comments
Fetching comments Fetching comments
mircosoft-partner

هل ترغب بارسال اشعارات عن اخر التحديثات في شمرا-اكاديميا