Rogers Communications (Canada)

Welcome Message from the ChairsOn behalf of the organizing committee and the technical program committee, we warmly welcome all of you to the 19th International Conference on Privacy, Security and Trust (PST 2022).The PST 2022 continues the tradition of bringing together researchers around the three themes of privacy, security, and trust, together with a new blockchain special theme to present their latest findings and discuss their results and application in practice.It has certainly been a challenge arranging a conference of this scale while dealing with the global response to the COVID pandemic and the resultant uncertainties, and while a physical, in-person conference was much preferred, we have successfully managed to make arrangements to hold this as a combination of in-person Cybersecurity Industry Summit on August 22, 2022, virtual main conference on August 23-24, 2022, and hybrid workshops on August 25, 2022 while still covering the intended topics.The PST 2022 covers both industry and academic discussions with a balanced program covering a variety of cybersecurity topics.The conference features keynote speakers from the academic, government, and industry sectors.

Due to the scarcity of labeled faulty data, Unsupervised Learning (UL) methods have gained great traction for anomaly detection and localization in Network Functions Virtualization (NFV) systems. In a UL approach, training is performed on only normal data for learning normal data patterns, and deviation from the norm is considered as an anomaly. However, it has been shown that even small percentages of anomalous samples in the training data (referred to as contamination) can significantly degrade the performance of UL methods. To address this issue, we propose an anomaly-detection approach based on the Noisy-Student technique, which was originally introduced for leveraging unlabeled datasets in computer-vision classification problems. Our approach not only provides robustness against training-data contamination, but also can leverage this contamination to improve anomaly-detection accuracy. Moreover, after an anomaly is detected, localization of the anomalous virtualized network functions in an unsupervised manner is a challenging task in the absence of labeled data. For anomaly localization in NFV systems, we propose to exploit existing local AI-explainability methods to achieve a high localization performance and propose our own novel AI-explainability method, specifically designed for the anomaly-localization problem in NFV, to improve the performance further. We perform a comprehensive experimental analysis on two datasets collected on different NFV testbeds and show that our proposed solutions outperform the existing methods by up to 22% in anomaly detection and up to 19% in anomaly localization in terms of F1-score.

Urban agriculture is receiving increased attention not only for food security and public health but for mitigating the impacts of urbanization and climate change. In cities, rooftop urban farms provide a solution for the limited space at the ground level. However, rooftop urban farming poses several challenges, including an increased need for workforce and site visits and a demand for efficient water use. Recent advancements in information and communication technology (ICT) and the Internet of Things (IoT) have enabled a tremendous suite of low-cost, wireless sensor nodes. In this work, an IoT-enabled approach is introduced to improve water management in an urban rooftop farm in downtown Toronto, Canada. Low-cost resistive water level sensors were calibrated and integrated into wireless sensor nodes to send data through LoRaWAN, an IoT protocol, to The Things Network (TTN) console, after which the processed data are visualized in the user dashboard. This paper addresses the main design stages, field deployment, and suggestions for maintenance learned through monitoring the growing season of 2021. The combination of low-cost sensors, user-friendly microcontrollers and open-source platforms provides an opportunity to improve decision-making, lower costs and reduce reliance on labor.

Public-use survey data are an important source of information for researchers in social science and health studies to build statistical models and make inferences on the target finite population. This paper presents two general inferential tools through the pseudo empirical likelihood and the sample empirical likelihood methods. Theoretical results on point estimation and linear or nonlinear hypothesis tests involving parameters defined through estimating equations are established, and practical issues with the implementation of the proposed methods are discussed. Results from simulation studies and an application to the 2016 General Social Survey dataset of Statistics Canada show that the proposed methods work well under different scenarios. The inferential procedures and theoretical results presented in the paper make the empirical likelihood a practically useful tool for users of complex survey data.

This environmental telephone interview scan was designed to identify: (1) how hospitals in one Canadian province incorporated tobacco use identification/documentation systems into practice; and, (2) challenges/issues with tobacco identification/documentation. Participants included 36/139 hospitals previously identified to offer cessation services. Results showed hospitals aided by researchers monitored and tracked tobacco use; those not aligned with researchers did not. The wording of tobacco items most commonly included use within the last 6-months (42%), 30-days (39%), or 7-days (33%), or use without reference to time (e.g., “Do you smoke?”; 39%); wording sometimes depended on admitting form space limitations. The admission process determined where the tobacco item appeared, which differed by hospital—75% included it on an admitting form (75%) and/or nursing assessment (56%); the item sometimes varied by unit. There were also different processes by which the item triggered delivery of cessation interventions; most frequently (69%), staff nurses were triggered to provide an intervention. The findings suggest that adding a tobacco use question to a hospital’s admitting process is potentially not that simple. Deciding on the purpose of the question, when it will be asked and by whom, space allotted on the form, and how it will trigger an intervention are important considerations that can affect the question wording, form/location, systems required, data extraction, and resources.

This paper argues that the challenges like poverty, inequality, debt crisis, recession or environmental damage faced by our current world are created because of the individuals who hold the control of our capitalists institutions are in dilemma similar to prisoner’s dilemma. It tells that a capitalist’s growth compulsion is driven by his competitors’ profit maximisation goal. Whatever the crisis, poor people are the most affected. The subset of the population becoming poorer can be tracked by measuring their Real Income to Contribution Ratio (RICR). The answer to poverty lies in gradually improving their average RICR from a benchmark position. The concept of Greenhouse Care Economics (GhCE) suggests that this can be achieved by bringing them together under a common framework. If the framework is implemented across a country and eventually across the world to solve poverty problems, it will act against the capitalist’s dilemma through a vertical learning process and will pave the way toward green economics.

The fundamental theorems of welfare economics are not designed to represent the real world. Instead, they tell us about certain conditions under which general equilibrium will be efficient. This paper introduces a new concept ‘biased equilibrium’ based on information economics and consolidates neoclassical economics and institutional economics together. In the real world economy, the probability of achieving Pareto efficiency for a subset of the population is much higher than that for the whole population. This model is enhanced to describe that our market is not uniform, but distributed in layers of energy states. A money market dynamics describes how our global economy has achieved prosperity over the time. If this is not balanced, it will create a market loop that may potentially put debt pressure on the economy or may cause poverty and hinder any green initiative.

In 2002, a small population of Indo-Pacific humpback dolphins, Sousa chinensis, was discovered in the coastal waters of the eastern Taiwan Strait. Serious conservation concerns about this population led to a survey of most of the coastal waters of western Taiwan to better understand the status of this population. Surveys were conducted from boats (inshore waters) and a sea-kayak or land-based platforms (littoral waters inshore of large sandbars). Humpback dolphins were sighted 35 times, all within a stretch of inshore waters approximately 100 km (linear distance) and within 2 km from shore (none were observed in littoral waters). Including consideration of other records of this species, the main distribution of these dolphins was estimated to be approximately 515 km2 of water off central western Taiwan, where industrialization is a serious and rapidly increasing issue. The population's abundance and density were estimated to be 99 individuals (coefficient of variation 51.6%) and 19.3 individuals/100 km2, respectively, which is quite low when compared to the Pearl River estuary population. Assessing this population using the IUCN Red List criteria resulted in a “Critically Endangered” categorization, reinforcing the urgency of the situation.

The spatio-temporal array-receiver (STAR) decomposes generic wideband CDMA channel responses across various parameter dimensions (e.g., time-delays, multipath components, etc...) and extracts the associated time-varying parameters (i.e., analysis) before reconstructing the channel (i.e., synthesis) with increased accuracy. This work verifies the performance of STAR by comparing the results achieved with generic and measured channels for an average multipath power profile of [0, -4, -8] dB and a vehicular speed below 30 Km/h. The results suggest that losses due to operations with real 5 MHz channels are only 1 dB in SNR and 20-30% in capacity with DBPSK and single transmit and receive antennas. The corresponding SNR threshold for operation with real channels is about 5 dB.

A metal coating is applied to a vacuum tube covering the tube envelope and the shell of the base by successive operations of sand blasting and spraying metal from an oxyacetylene blow torch which produces a coating which is in intimate contact with the glass envelope. A negative potential is applied to the metal spray shield when the tube is operated which prevents cathode rays, which are not intercepted by the anode, from reaching the interior surface of the glass envelope. Secondary emission of electrons from the glass wall is avoided. Localized heating of the glass is prevented and the fluctuation component of anode current is suppressed. It is pointed out that a tube structure coöperating with the spray shield is more economical and the apparatus associated with the tube can be simplified in design.