2,375 research outputs found
PRIVACYāS NEXT ACT
This Article identifies and describes three data privacy policy developments from recent legislative sessions that may seem unrelated, but which I contend together offer clues about privacy lawās future over the short-to-medium term.
The first is the proliferation, worldwide and in U.S. states, of legislative proposals and statutes referred to as āage-appropriate design codes.ā Originating in the United Kingdom, age-appropriate design codes typically apply to online services ādirected to childrenā and subject such services to transparency, default settings, and other requirements. Chief among them is an implied obligation to conduct ongoing assessments of whether a service could be deemed ādirected to childrenā such that it triggers application of the codes.
The second development is a well-documented push for responsible artificial intelligence (āAIā) practices in the form of new transparency and accountability frameworks. The most comprehensive such framework is the European Unionās AI Act, although similar reforms in Canada, as well as nascent reforms here in the United States, address analogous topics. Among these are requirements for AI developers to assess, document, and, in some instances, report to regulators the existence of potential harms and plans to mitigate them prior to launching a new AI-driven product or service.
The third development, certain reforms to competition policies, is least likely to be traditionally counted among āprivacyā laws. However, I argue that two recent reforms in Europeāthe Digital Services Act and the Digital Markets Actāimplicate data privacy concerns and should be viewed as imposing privacy-related compliance obligations. For instance, these frameworks address the use of personal data, including sensitive personal information, for online advertising purposes.
My argument is that common threads across these developments underscore the dynamism of privacy law at a critical moment in its development and highlight the increased public awareness of the benefitsāāand risksāāof a data-driven economy and society. To that end, I identify three specific trends among these developments that I anticipate recurring in data privacy policy proposals over privacyās ānext act.ā First, legislators and regulators alike appear increasingly focused on age verification technologies as a mechanism for distinguishing between internet users and determining to whom they must provide certain protections. Second, there is a growing appetite for shifting assessment obligations onto regulated entities, albeit with guidance, and requiring that the results of such assessments are affirmatively disclosed to regulators. Third, privacy obligations are no longer limited to data privacy laws. They are increasingly found in other types of policy proposalsāāand detecting them will require a broader view of what constitutes a āprivacyā law than typical among privacy professionals
Digitalization and Development
This book examines the diffusion of digitalization and Industry 4.0 technologies in Malaysia by focusing on the ecosystem critical for its expansion. The chapters examine the digital proliferation in major sectors of agriculture, manufacturing, e-commerce and services, as well as the intermediary organizations essential for the orderly performance of socioeconomic agents.
The book incisively reviews policy instruments critical for the effective and orderly development of the embedding organizations, and the regulatory framework needed to quicken the appropriation of socioeconomic synergies from digitalization and Industry 4.0 technologies. It highlights the importance of collaboration between government, academic and industry partners, as well as makes key recommendations on how to encourage adoption of IR4.0 technologies in the short- and long-term.
This book bridges the concepts and applications of digitalization and Industry 4.0 and will be a must-read for policy makers seeking to quicken the adoption of its technologies
Introduction to Presentation Attacks in Signature Biometrics and Recent Advances
Applications based on biometric authentication have received a lot of
interest in the last years due to the breathtaking results obtained using
personal traits such as face or fingerprint. However, it is important not to
forget that these biometric systems have to withstand different types of
possible attacks. This chapter carries out an analysis of different
Presentation Attack (PA) scenarios for on-line handwritten signature
verification. The main contributions of this chapter are: i) an updated
overview of representative methods for Presentation Attack Detection (PAD) in
signature biometrics; ii) a description of the different levels of PAs existing
in on-line signature verification regarding the amount of information available
to the impostor, as well as the training, effort, and ability to perform the
forgeries; and iii) an evaluation of the system performance in signature
biometrics under different scenarios considering recent publicly available
signature databases, DeepSignDB and SVC2021_EvalDB. This work is in line with
recent efforts in the Common Criteria standardization community towards
security evaluation of biometric systems.Comment: Chapter of the Handbook of Biometric Anti-Spoofing (Third Edition
Privacy-preserving artificial intelligence in healthcare: Techniques and applications
There has been an increasing interest in translating artificial intelligence (AI) research into clinically-validated applications to improve the performance, capacity, and efficacy of healthcare services. Despite substantial research worldwide, very few AI-based applications have successfully made it to clinics. Key barriers to the widespread adoption of clinically validated AI applications include non-standardized medical records, limited availability of curated datasets, and stringent legal/ethical requirements to preserve patients' privacy. Therefore, there is a pressing need to improvise new data-sharing methods in the age of AI that preserve patient privacy while developing AI-based healthcare applications. In the literature, significant attention has been devoted to developing privacy-preserving techniques and overcoming the issues hampering AI adoption in an actual clinical environment. To this end, this study summarizes the state-of-the-art approaches for preserving privacy in AI-based healthcare applications. Prominent privacy-preserving techniques such as Federated Learning and Hybrid Techniques are elaborated along with potential privacy attacks, security challenges, and future directions. [Abstract copyright: Copyright Ā© 2023 The Author(s). Published by Elsevier Ltd.. All rights reserved.
2023-2024 Catalog
The 2023-2024 Governors State University Undergraduate and Graduate Catalog is a comprehensive listing of current information regarding:Degree RequirementsCourse OfferingsUndergraduate and Graduate Rules and Regulation
Implementation of ISO Frameworks to Risk Management in IPv6 Security
The Internet of Things is a technology wave sweeping across various industries and sectors. It promises to improve productivity and efficiency by providing new services and data to users. However, the full potential of this technology is still not realized due to the transition to IPv6 as a backbone. Despite the security assurances that IPv6 provides, privacy and concerns about the Internet of Things remain. This is why it is important that organizations thoroughly understand the protocol and its migration to ensure that they are equipped to take advantage of its many benefits. Due to the lack of available IPv4 addresses, organizations are in an uncertain situation when it comes to implementing IoT technologies.
The other aim is to fill in the gaps left by the ISO to identify and classify the risks that are not yet apparent. The thesis seeks to establish and implement the use of ISO to manage risks. It will also help to align security efforts with organizational goals. The proposed solution is evaluated through a survey that is designed to gather feedback from various levels of security and risk management professionals. The suggested modifications are also included in the study.
A survey on the implementation of ISO frameworks to risk management in IPv6 was conducted and with results as shown in the random sampling technique that was used for conducting the research a total of 75 questionnaires were shared online, 50 respondents returned responses online through emails and social media platforms. The result of the analysis shows that system admin has the highest pooling 26% of all the overall participants, followed by network admin with 20%, then cybersecurity specialists with 16%. 14% of the respondents were network architects while senior management and risk management professionals were 4% and 2% respectively. The majority of the respondents agreed that risk treatment enhances the risk management performance of the IPv6 network resulting from the proper selection and implementation of correct risk prevention strategies
Cognitive Machine Individualism in a Symbiotic Cybersecurity Policy Framework for the Preservation of Internet of Things Integrity: A Quantitative Study
This quantitative study examined the complex nature of modern cyber threats to propose the establishment of cyber as an interdisciplinary field of public policy initiated through the creation of a symbiotic cybersecurity policy framework. For the public good (and maintaining ideological balance), there must be recognition that public policies are at a transition point where the digital public square is a tangible reality that is more than a collection of technological widgets. The academic contribution of this research project is the fusion of humanistic principles with Internet of Things (IoT) technologies that alters our perception of the machine from an instrument of human engineering into a thinking peer to elevate cyber from technical esoterism into an interdisciplinary field of public policy. The contribution to the US national cybersecurity policy body of knowledge is a unified policy framework (manifested in the symbiotic cybersecurity policy triad) that could transform cybersecurity policies from network-based to entity-based. A correlation archival data design was used with the frequency of malicious software attacks as the dependent variable and diversity of intrusion techniques as the independent variable for RQ1. For RQ2, the frequency of detection events was the dependent variable and diversity of intrusion techniques was the independent variable. Self-determination Theory is the theoretical framework as the cognitive machine can recognize, self-endorse, and maintain its own identity based on a sense of self-motivation that is progressively shaped by the machineās ability to learn. The transformation of cyber policies from technical esoterism into an interdisciplinary field of public policy starts with the recognition that the cognitive machine is an independent consumer of, advisor into, and influenced by public policy theories, philosophical constructs, and societal initiatives
Advances and Applications of DSmT for Information Fusion. Collected Works, Volume 5
This ļ¬fth volume on Advances and Applications of DSmT for Information Fusion collects theoretical and applied contributions of researchers working in different ļ¬elds of applications and in mathematics, and is available in open-access. The collected contributions of this volume have either been published or presented after disseminating the fourth volume in 2015 in international conferences, seminars, workshops and journals, or they are new. The contributions of each part of this volume are chronologically ordered.
First Part of this book presents some theoretical advances on DSmT, dealing mainly with modiļ¬ed Proportional Conļ¬ict Redistribution Rules (PCR) of combination with degree of intersection, coarsening techniques, interval calculus for PCR thanks to set inversion via interval analysis (SIVIA), rough set classiļ¬ers, canonical decomposition of dichotomous belief functions, fast PCR fusion, fast inter-criteria analysis with PCR, and improved PCR5 and PCR6 rules preserving the (quasi-)neutrality of (quasi-)vacuous belief assignment in the fusion of sources of evidence with their Matlab codes.
Because more applications of DSmT have emerged in the past years since the apparition of the fourth book of DSmT in 2015, the second part of this volume is about selected applications of DSmT mainly in building change detection, object recognition, quality of data association in tracking, perception in robotics, risk assessment for torrent protection and multi-criteria decision-making, multi-modal image fusion, coarsening techniques, recommender system, levee characterization and assessment, human heading perception, trust assessment, robotics, biometrics, failure detection, GPS systems, inter-criteria analysis, group decision, human activity recognition, storm prediction, data association for autonomous vehicles, identiļ¬cation of maritime vessels, fusion of support vector machines (SVM), Silx-Furtif RUST code library for information fusion including PCR rules, and network for ship classiļ¬cation.
Finally, the third part presents interesting contributions related to belief functions in general published or presented along the years since 2015. These contributions are related with decision-making under uncertainty, belief approximations, probability transformations, new distances between belief functions, non-classical multi-criteria decision-making problems with belief functions, generalization of Bayes theorem, image processing, data association, entropy and cross-entropy measures, fuzzy evidence numbers, negator of belief mass, human activity recognition, information fusion for breast cancer therapy, imbalanced data classiļ¬cation, and hybrid techniques mixing deep learning with belief functions as well
Recommended from our members
Paradigm Shift from Vague Legal Contracts to Blockchain-Based Smart Contracts
In this dissertation, we address the problem of vagueness in traditional legal contracts by presenting novel methodologies that aid in the paradigm shift from traditional legal contracts to smart contracts. We discuss key enabling technologies that assist in converting the traditional natural language legal contract, which is full of vague words, phrases, and sentences to the blockchain-based precise smart contract, including metrics evaluation during our conversion experiment. To address the challenge of this contract-transformation process, we propose four novel proof-of-concept approaches that take vagueness and different possible interpretations into significant consideration, where we experiment with popular vendors' existing vague legal contracts. We show through experiments that our proposed methodologies are able to study the degree of vagueness in every interpretation and demonstrate which vendor's translated-smart contract can be more accurate, optimized, and have a lesser degree of vagueness. We also incorporated the method of fuzzy logic inside the blockchain-based smart contract, to successfully model the semantics of linguistic expressions. Our experiments and results show that the smart contract with the higher degrees of truth can be very complex technically but more accurate at the same time. By using fuzzy logic inside a smart contract, it becomes easier to solve the problem of contractual ambiguities as well as expedite the process of claiming compensation when implemented in a blockchain-based smart contract
- ā¦