Privacy Assessment on Reconstructed Images: Are Existing Evaluation Metrics Faithful to Human Perception?

Hand-crafted image quality metrics, such as PSNR and SSIM, are commonly used to evaluate model privacy risk under reconstruction attacks. Under these metrics, reconstructed images that are determined to resemble the original one generally indicate more privacy leakage. Images determined as overall dissimilar, on the other hand, indicate higher robustness against attack. However, there is no guarantee that these metrics well reflect human opinions, which, as a judgement for model privacy leakage, are more trustworthy. In this paper, we comprehensively study the faithfulness of these hand-crafted metrics to human perception of privacy information from the reconstructed images. On 5 datasets ranging from natural images, faces, to fine-grained classes, we use 4 existing attack methods to reconstruct images from many different classification models and, for each reconstructed image, we ask multiple human annotators to assess whether this image is recognizable. Our studies reveal that the hand-crafted metrics only have a weak correlation with the human evaluation of privacy leakage and that even these metrics themselves often contradict each other. These observations suggest risks of current metrics in the community. To address this potential risk, we propose a learning-based measure called SemSim to evaluate the Semantic Similarity between the original and reconstructed images. SemSim is trained with a standard triplet loss, using an original image as an anchor, one of its recognizable reconstructed images as a positive sample, and an unrecognizable one as a negative. By training on human annotations, SemSim exhibits a greater reflection of privacy leakage on the semantic level. We show that SemSim has a significantly higher correlation with human judgment compared with existing metrics. Moreover, this strong correlation generalizes to unseen datasets, models and attack methods.Comment: 15 pages, 9 figures and 3 table

Probabilistic Dataset Reconstruction from Interpretable Models

Interpretability is often pointed out as a key requirement for trustworthy machine learning. However, learning and releasing models that are inherently interpretable leaks information regarding the underlying training data. As such disclosure may directly conflict with privacy, a precise quantification of the privacy impact of such breach is a fundamental problem. For instance, previous work have shown that the structure of a decision tree can be leveraged to build a probabilistic reconstruction of its training dataset, with the uncertainty of the reconstruction being a relevant metric for the information leak. In this paper, we propose of a novel framework generalizing these probabilistic reconstructions in the sense that it can handle other forms of interpretable models and more generic types of knowledge. In addition, we demonstrate that under realistic assumptions regarding the interpretable models' structure, the uncertainty of the reconstruction can be computed efficiently. Finally, we illustrate the applicability of our approach on both decision trees and rule lists, by comparing the theoretical information leak associated to either exact or heuristic learning algorithms. Our results suggest that optimal interpretable models are often more compact and leak less information regarding their training data than greedily-built ones, for a given accuracy level

Sharing of Encrypted files in Blockchain Made Simpler

Recently, blockchain technology has attracted much attention of the research community in several domains requiring transparency of data accountability, due to the removal of intermediate trust assumptions from third parties. One such application is enabling file sharing in blockchain enabled distributed cloud storage. Proxy re-encryption is a cryptographic primitive that allows such file sharing by re-encrypting ciphertexts towards legitimate users via semi-trusted proxies, without them learning any information about the underlying message. To facilitate secure data sharing in the distributed cloud, it is essential to construct efficient proxy re-encryption protocols. In this paper, we introduce the notion of proxy self re-encryption (SE-PRE) that is highly efficient, as compared to the existing PRE schemes in the literature. We show that our self encryption scheme is provably CCA secure based on the DLP assumption and our proxy re-encryption scheme with self encryption is CCA secure under the hardness of the Computational Diffie Hellman (CDH) and Discrete Logarithm (DLP) assumption. Our novel encryption scheme, called self encryption, has no exponentiation or costly pairing operation. Even the re-encryption in SE-PRE does not have such operations and this facilitates the service provider with efficiency gain

implications to CRM and public policy

Thesis(Doctoral) --KDI School:Ph.D in Public Policy,2017With the advent of the Internet and Mobile Communications, the nature of communication has changed significantly over the past few decades .The promotion of technologies among the common people has been found to be an important element of public policy to reduce the digital divide. The rapid advancement of information technology (IT), automation systems and data communications systems leads to improvement of intelligent transport systems (ITS). ITS covers all branches of transportation and involves all dynamically interacting elements of transportation system, i.e. transport means, infrastructure, drivers and commuters. However, few researches have been carried out in the context of public sectors, especially that involving ITS. The purpose of this study is to investigate the justice dimensions that influence satisfaction and public confidence in the context of ITS and to explore implications to Citizen/Customer Relationship Management (CRM) and public policy. This study investigates the following research questions: i) Do levels of perceived justice (distributive, procedural and interactional) in ITS environment affect levels of satisfaction/dissatisfaction? ii) Do levels of satisfaction form ITS affect levels of public confidence? iii) Do levels of dissatisfaction form ITS affect levels of willingness to complain? iv) Do levels of dissatisfaction form ITS affect levels of complaining behavior? v) Do levels of complaining behavior in ITS environment affect levels of satisfaction with complaint handling when the complaints are resolved based on three dimensions (distributive, procedural and interactional)of justice? vi) Do levels of willingness to complain in ITS environment affect levels of public confidence? vii) Do levels of satisfaction with complaint handling in ITS environment affect levels of public confidence? The findings of this study imply that ITS users are more importantly perceive to equity and equality issues, or distributive justice. The employment of ITS should not be limited to the technical aspects of ITS, but should focus more attention on the subjective domain of justice. The results of this study also have important implications for public complaint handling in terms of increasing public satisfaction with ITS, which is crucial for CRM.Part I: Exploring Satisfaction/Dissatisfaction and Public Confidence in the ITS Environment; Implications to CRM and Public Policy Part II: ComparingSatisfaction/Dissatisfaction and Public Confidence in the ITS Environment in Public and Private Transportation Part III: Implementation Strategy of ITS in Developing CountriesdoctoralpublishedA. K. M. Anisur RAHMAN

Review of Alternatives to Incarceration Efforts Worldwide

Despite global interest in treating substance use disorders as a health issue, many countries choose a criminal justice response instead. The goal of this project was to research the readiness of countries to establish or expand alternatives to incarceration (ATIs) for persons with substance use disorders (SUDs) in countries around the globe. This report gathers, compiles and analyzes information on alternatives to incarceration for persons involved in the criminal justice with substance use disorders, worldwide (193 UN Member States plus Greenland, Kosovo, Palestine and Taiwan). As such, this report presents the first attempt to compile this information globally and completely. A video of the webinar meeting with the presentation of results is available at: https://www.youtube.com/watch?v=p3_h6hMOvTc

Impact of Ubiquitous Real-Time Information on Bus Passenger Route Choice

Over the last decade, Ubiquitous Real-time Passenger Information (URTPI) has become popular among public transport passengers. The effectiveness of URTPI and hence the value of the investments into the necessary systems can be increased with a clear understanding of how URTPI influences passenger behaviour. However, such an understanding is still limited and fragmented. In particular, very little is known about the impact of URTPI on route choice. This study fills this gap evaluating the impact of URTPI on bus passengers’ route choice.A revealed preference survey methodology was adopted for data collection and two questionnaire surveys targeting bus users were carried out. Categorical Regression and discrete choice models, such as Binary Logit Model and Multinomial Logit Model, have been applied to analyse the survey data.The study reveals that trip length, passenger age and profession are the main factors influencing the use of URTPI.Having access toURTPI, the frequency of its use is strongly influenced by the attributes of information and social norms. Bus arrival time and bus stop location are the two most important contents of information. Changing time ofdeparture from the start and the boarding time are the two most popular actions taken by bus passengers after consulting URTPI. Passengers’ decisions are influenced by information on bus arrival time, bus route, and walking distance. As a result of the impact of URTPI on passengers’ choices, the demand distribution for bus runs could potentially be changed by 33% and for bus lines by 22%. The overall network demand distribution could be affected in 42% of cases as a result of consulting URTPI.This study implicates that while investing in tailoring the sources of URTPI, passengers’ preferred attributes and contents of information should be considered. Transport planners and operators should take the potential impact of URTPI into account to make better predictions of the PT demand distribution

Sustainable social work : a response to the climate emergency from social work education and practice in Aotearoa, New Zealand : a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Social Work at Massey University, Albany, New Zealand

Listed in 2020 Dean's List of Exceptional ThesesEvidence of the climate emergency is apparent in changing weather systems, rising sea levels, temperature extremes and challenges to food, energy and water security. These physical impacts have health and social implications that increase resource pressures and exacerbate inequities across all social systems. Those tasked with supporting the most vulnerable in the community must plan to face these challenges. Social workers in practice and education across Aotearoa New Zealand need to better understand the relevance of climate change impacts on their practice and prepare for a resilient future. The climate emergency has arrived and the time for action is now. This educational action research, informed by Transformative learning theory and the Transtheoretical model of change, engages social workers, students and educators across Aotearoa New Zealand in a process of transformative learning about the climate change impacts on their work. Transformative learning theory informs the design and interpretation of qualitative data generated through three action research cycles. These include educational workshops, individual interviews and focus groups. Working in collaboration with key stakeholders this thesis identifies the educational and support needs of future social workers. From the findings emerge a working definition of Sustainable Social Work, an educational framework for the future social work curriculum and a Model of Sustainable Action. Each creates a practice-based response to the climate emergency underway in Aotearoa New Zealand

Toward a Bio-Inspired System Architecting Framework: Simulation of the Integration of Autonomous Bus Fleets & Alternative Fuel Infrastructures in Closed Sociotechnical Environments

Cities are set to become highly interconnected and coordinated environments composed of emerging technologies meant to alleviate or resolve some of the daunting issues of the 21st century such as rapid urbanization, resource scarcity, and excessive population demand in urban centers. These cybernetically-enabled built environments are expected to solve these complex problems through the use of technologies that incorporate sensors and other data collection means to fuse and understand large sums of data/information generated from other technologies and its human population. Many of these technologies will be pivotal assets in supporting and managing capabilities in various city sectors ranging from energy to healthcare. However, among these sectors, a significant amount of attention within the recent decade has been in the transportation sector due to the flood of new technological growth and cultivation, which is currently seeing extensive research, development, and even implementation of emerging technologies such as autonomous vehicles (AVs), the Internet of Things (IoT), alternative xxxvi fueling sources, clean propulsion technologies, cloud/edge computing, and many other technologies. Within the current body of knowledge, it is fairly well known how many of these emerging technologies will perform in isolation as stand-alone entities, but little is known about their performance when integrated into a transportation system with other emerging technologies and humans within the system organization. This merging of new age technologies and humans can make analyzing next generation transportation systems extremely complex to understand. Additionally, with new and alternative forms of technologies expected to come in the near-future, one can say that the quantity of technologies, especially in the smart city context, will consist of a continuously expanding array of technologies whose capabilities will increase with technological advancements, which can change the performance of a given system architecture. Therefore, the objective of this research is to understand the system architecture implications of integrating different alternative fueling infrastructures with autonomous bus (AB) fleets in the transportation system within a closed sociotechnical environment. By being able to understand the system architecture implications of alternative fueling infrastructures and AB fleets, this could provide performance-based input into a more sophisticated approach or framework which is proposed as a future work of this research