Adversarial Machine Learning for NextG Covert Communications Using Multiple Antennas

This paper studies the privacy of wireless communications from an eavesdropper that employs a deep learning (DL) classifier to detect transmissions of interest. There exists one transmitter that transmits to its receiver in the presence of an eavesdropper. In the meantime, a cooperative jammer (CJ) with multiple antennas transmits carefully crafted adversarial perturbations over the air to fool the eavesdropper into classifying the received superposition of signals as noise. While generating the adversarial perturbation at the CJ, multiple antennas are utilized to improve the attack performance in terms of fooling the eavesdropper. Two main points are considered while exploiting the multiple antennas at the adversary, namely the power allocation among antennas and the utilization of channel diversity. To limit the impact on the bit error rate (BER) at the receiver, the CJ puts an upper bound on the strength of the perturbation signal. Performance results show that this adversarial perturbation causes the eavesdropper to misclassify the received signals as noise with a high probability while increasing the BER at the legitimate receiver only slightly. Furthermore, the adversarial perturbation is shown to become more effective when multiple antennas are utilized.     

Using Timeliness in Tracking Infections

We consider real-time timely tracking of infection status (e.g., COVID-19) of individuals in a population. In this work, a health care provider wants to detect both infected people and people who have recovered from the disease as quickly as possible. In order to measure the timeliness of the tracking process, we use the long-term average difference between the actual infection status of the people and their real-time estimate by the health care provider based on the most recent test results. We first find an analytical expression for this average difference for given test rates, infection rates and recovery rates of people. Next, we propose an alternating minimization-based algorithm to find the test rates that minimize the average difference. We observe that if the total test rate is limited, instead of testing all members of the population equally, only a portion of the population may be tested in unequal rates calculated based on their infection and recovery rates. Next, we characterize the average difference when the test measurements are erroneous (i.e., noisy). Further, we consider the case where the infection status of individuals may be dependent, which occurs when an infected person spreads the disease to another person if they are not detected and isolated by the health care provider. In addition, we consider an age of incorrect information-based error metric where the staleness metric increases linearly over time as long as the health care provider does not detect the changes in the infection status of the people. Through extensive numerical results, we observe that increasing the total test rate helps track the infection status better. In addition, an increased population size increases diversity of people with different infection and recovery rates, which may be exploited to spend testing capacity more efficiently, thereby improving the system performance. Depending on the health care provider’s preferences, test rate allocation can be adjusted to detect either the infected people or the recovered people more quickly. In order to combat any errors in the test, it may be more advantageous for the health care provider to not test everyone, and instead, apply additional tests to a selected portion of the population. In the case of people with dependent infection status, as we increase the total test rate, the health care provider detects the infected people more quickly, and thus, the average time that a person stays infected decreases. Finally, the error metric needs to be chosen carefully to meet the priorities of the health care provider, as the error metric used greatly influences who will be tested and at what test rate.     

Taylor's Decomposition on two points for one‐dimensional Bratu problem

In this article, Taylor's Decomposition method is introduced for solving one‐dimensional Bratu problem. The numerical scheme is based on the application of the Taylor's decomposition to the corresponding first order differential equation system. The technique is illustrated with different eigenvalues and the results show that the method converges rapidly and hence approximate the exact solution very accurately for relatively large step sizes. © 2009 Wiley Periodicals, Inc. Numer Methods Partial Differential Eq 2010     

A Mass Spectral Investigation of the RF Plasmas of Small Organic Compounds: An Investigation of the Plasma-Phase Reactions in the Plasma Deposition from Allyl Amine

Inductively coupled, radiofrequency-induced plasmas of allyl amine, operated at low values of electrical power P/ monomer flow rate (P/), have been investigated using mass spectrometry (MS) and deposition rate measurements. The solid, plasma deposit products were obtained as films and analyzed by X-ray photoelectron spectroscopy (XPS) and grazing angle infra-red (IR). The positiveion MS data indicate that species of the general types (nM – H)⁺, (nM+H)⁺, and nM⁺, where M represents a unit of the starting material (monomer), are present in the plasma. The relative abundance of these was monitored as a function of the electrical power supplied to the plasma. Mass spectrometry of the plasma neutrals revealed that only M and its fragments are present in the plasma: no neutral oligomeric species were detected. XPS analysis revealed that the plasma deposits contain at least three different nitrogen functional groups. The relative proportions of these were only marginally affected by plasma power. The deposition rate increased with P/. The observation of three classes of species in the plasma-phase sets allyl amine apart from other compounds previously studied. We believe that the plasma-phase chemistry accounts for the low retention of amine in the solid-phase plasma product and for the weak dependence of deposit chemistry on P/.