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Journal articles on the topic 'Risk of loss of privavy'

Author: Grafiati

Published: 2 June 2025

Last updated: 31 July 2025

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1

Asma, javed, and Mehmood Babak. "A Study of Risks Factors Affecting Online Shopping in Faisalabad." International Journal of Business, Economics and Management Works 2, no. 11 (2015): 75–84. https://doi.org/10.5281/zenodo.34011.

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This is the era of technology and companies are becoming globalized. Now companies are facing tougher competition. This is their need to be innovative if they want to be in the competition. Technologies not only provide benefits to users but also have negativity. Shopping through the internet is very common now days. It not only made shopping tasks easy but also has many risks. The study explores the risks of online shopping. Population was selected from Faisalabad city and two hundred and fifty respondents were selected as sample. Different data analyses techniques were used to find out the F

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2

Chen, Ya-Ling, Bo-Chao Cheng, Hsueh-Lin Chen, et al. "A Privacy-Preserved Analytical Method for eHealth Database with Minimized Information Loss." Journal of Biomedicine and Biotechnology 2012 (2012): 1–9. http://dx.doi.org/10.1155/2012/521267.

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Digitizing medical information is an emerging trend that employs information and communication technology (ICT) to manage health records, diagnostic reports, and other medical data more effectively, in order to improve the overall quality of medical services. However, medical information is highly confidential and involves private information, even legitimate access to data raises privacy concerns. Medical records provide health information on an as-needed basis for diagnosis and treatment, and the information is also important for medical research and other health management applications. Tra

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3

Lavelle, Bridget, and Pamela J. Smock. "Divorce and Women’s Risk of Health Insurance Loss." Journal of Health and Social Behavior 53, no. 4 (2012): 413–31. http://dx.doi.org/10.1177/0022146512465758.

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This article bridges the literatures on the economic consequences of divorce for women with that on marital transitions and health by focusing on women’s health insurance. Using a monthly calendar of marital status and health insurance coverage from 1,442 women in the Survey of Income and Program Participation, we examine how women’s health insurance changes after divorce. Our estimates suggest that roughly 115,000 American women lose private health insurance annually in the months following divorce and that roughly 65,000 of these women become uninsured. The loss of insurance coverage we obse

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4

Oliveira, Juliana Santos de, Liliane Barbosa Rodrigues, Fernanda Soares Aurélio, and Virgínia Braz da Silva. "Risk factors and prevalence of newborn hearing loss in a private health care system of Porto Velho, Northern Brazil." Revista Paulista de Pediatria 31, no. 3 (2013): 299–305. http://dx.doi.org/10.1590/s0103-05822013000300005.

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OBJECTIVE: To determine the prevalence of hearing loss and to analyze the results of newborn hearing screening and audiological diagnosis in private health care systems. METHODS Cross-sectional and retrospective study in a database of newborn hearing screening performed by a private clinic in neonates born in private hospitals of Porto Velho, Rondônia, Northern Brazil. The screening results, the risk for hearing loss, the risk indicators for hearing loss and the diagnosis were descriptively analyzed. Newborns cared in rooming in with their mothers were compared to those admitted to the Intensi

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Samad, Zeeshan, Myrna Wooders, Bradley Malin, and Yevgeniy Vorobeychik. "Risk, trust, and altruism in genetic data sharing." Journal of Public Economic Theory 25, no. 6 (2023): 1251–69. http://dx.doi.org/10.1111/jpet.12678.

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AbstractHow does concern about genetic data privacy compare with other concerns? We conduct behavioral experiments to compare risk attitudes towards sharing genetic data with a healthcare provider with risk attitudes towards sharing financial data with a money manager. Both scenarios involve identical decisions and monetary stakes, permitting us to focus on how the framing of data sharing influences attitudes. To delve deeper into individual motivations to share data, we provide treatments that study how data sharers' altruism and trust affect their decisions. Our findings (with 162 subjects)

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6

Crowcroft, Jon. "On the duality of resilience and privacy." Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences 471, no. 2175 (2015): 20140862. http://dx.doi.org/10.1098/rspa.2014.0862.

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Protecting information has long been an important problem. We would like to protect ourselves from the risk of loss: think of the library of Alexandria; and from unauthorized access: consider the very business of the ‘Scandal Sheets’, going back centuries. This has never been more true than today when vast quantities of data (dare one say lesser quantities of information) are stored on computer systems, and routinely moved around the Internet, at almost no cost. Computer and communication systems are both fragile and vulnerable, and so the risk of catastrophic loss or theft is potentially much

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7

Joseph, Nithya Sara. "Collaborative data sharing in online social network resolving privacy risk and sharing loss." IOSR Journal of Computer Engineering 16, no. 5 (2014): 55–61. http://dx.doi.org/10.9790/0661-16565561.

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8

Kumar, Mohit, Bernhard A. Moser, and Lukas Fischer. "On Mitigating the Utility-Loss in Differentially Private Learning: A New Perspective by a Geometrically Inspired Kernel Approach." Journal of Artificial Intelligence Research 79 (February 11, 2024): 515–67. http://dx.doi.org/10.1613/jair.1.15071.

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Privacy-utility tradeoff remains as one of the fundamental issues of differentially private machine learning. This paper introduces a geometrically inspired kernel-based approach to mitigate the accuracy-loss issue in classification. In this approach, a representation of the affine hull of given data points is learned in Reproducing Kernel Hilbert Spaces (RKHS). This leads to a novel distance measure that hides privacy-sensitive information about individual data points and improves the privacy-utility tradeoff via significantly reducing the risk of membership inference attacks. The effectivene

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9

Chu, Xiaolin. "Risk Sharing Method of PPP Model for Rural Sewage Treatment – Based on Interval Fuzzy Shapley Value." Proceedings of Business and Economic Studies 4, no. 5 (2021): 93–97. http://dx.doi.org/10.26689/pbes.v4i5.2605.

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Rural sewage treatment is in need of more capital investment, in which the financing model of PPP (public-private partnership) is able to encourage the investment of social capital in this sector. Risk sharing is one of the core features in the PPP model. In view that the risk loss of projects cannot be accurately estimated, this article describes the uncertainty of risk loss with fuzzy numbers and allocates the distribution of risk loss among the participants of rural sewage treatment PPP projects with interval fuzzy Shapley value to ensure a more reasonable and effective risk distribution.

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10

Snigdha, Esrat Zahan, Muhammad Saqib Jalil, Fares Mohammed Dahwal, et al. "Cybersecurity in Healthcare IT Systems: Business Risk Management and Data Privacy Strategies." American Journal of Engineering and Technology 07, no. 03 (2025): 163–84. https://doi.org/10.37547/tajet/volume07issue03-15.

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The security threats against healthcare IT systems create multiple significant hazards to patient data purity together with compliance requirements and ongoing organizational operations. These days growing healthcare digitization has caused cyberattacks like ransomware and data breaches and phishing attacks to increase sharply while creating financial damage and reputation loss for healthcare facilities. The research will examine how business risk management combines with data privacy strategies to safeguard healthcare cybersecurity structures through analysis of risk mitigation plans and regu

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Wang, Bing, Linna Geng, Robert Moehler, and Vivian W. Y. Tam. "ATTRACTING PRIVATE INVESTMENT IN PUBLIC-PRIVATE-PARTNERSHIP: TAX REDUCTION OR RISK SHARING." JOURNAL OF CIVIL ENGINEERING AND MANAGEMENT 30, no. 7 (2024): 581–99. http://dx.doi.org/10.3846/jcem.2024.21749.

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With the financial burden of government increasing, the Public-Private-Partnership (PPP) model has become an alternative method to develop public infrastructure. To efficiently promote the private sector to participate in PPP, making a proper incentive policy is critical for the government. This paper examined the effects of two governmental support policies, i.e., tax reduction and risk-sharing, on the investment decision of the private sector, and further compared the relative efficacy of these two policies. The results manifest that: first, both tax reduction and risk-sharing policies motiv

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12

Roisse Rodrigues Ferreira, Jean. "Decision-Making under Risk: Conditions Affecting the Risk Preferences of Politicians in Digitalization." International Journal of Environmental Research and Public Health 19, no. 5 (2022): 3036. http://dx.doi.org/10.3390/ijerph19053036.

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Public officials are constantly facing decisions under risk, particularly in digitalization policies, the consequences of which are hard to predict given their multiple dimensional nature. Since scholarly research has not yet addressed this phenomenon, we do not know what influences the risk preferences of politicians in digitalization policies. Prospect theory—widely used to explain political decisions—can help us describe politicians’ potential risk references and the conditions affecting their decisions. Accordingly, this paper aims to answer the following question: what are the conditions

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13

Zhang, Meng, Ermin Wei, Randall Berry, and Jianwei Huang. "Age-Dependent Differential Privacy." ACM SIGMETRICS Performance Evaluation Review 50, no. 1 (2022): 115–16. http://dx.doi.org/10.1145/3547353.3526953.

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The proliferation of real-time applications has motivated extensive research on analyzing and optimizing data freshness in the context of age of information. However, classical frameworks of privacy (e.g., differential privacy (DP)) have overlooked the impact of data freshness on privacy guarantees, and hence may lead to unnecessary accuracy loss when trying to achieve meaningful privacy guarantees in time-varying databases. In this work, we introduce age-dependent DP, taking into account the underlying stochastic nature of a time-varying database. In this new framework, we establish a connect

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14

Zhang, Ruijia, Mingxi Lei, Meng Ding, Zihang Xiang, Jinhui Xu, and Di Wang. "Improved Rates of Differentially Private Nonconvex-Strongly-Concave Minimax Optimization." Proceedings of the AAAI Conference on Artificial Intelligence 39, no. 21 (2025): 22524–32. https://doi.org/10.1609/aaai.v39i21.34410.

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In this paper, we study the problem of (finite sum) minimax optimization in the Differential Privacy (DP) model. Unlike most of the previous studies on the (strongly) convex-concave settings or loss functions satisfying the Polyak-Lojasiewicz condition, here we mainly focus on the nonconvex-strongly-concave one, which encapsulates many models in deep learning such as deep AUC maximization. Specifically, we first analyze a DP version of Stochastic Gradient Descent Ascent (SGDA) and show the utility bound in terms of the Euclidean norm of the gradient for the empirical risk function. We then pro

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15

Fan, Chiang Ku, Chen Mei Fan Chiang, and Yu Hsuang Lee. "Risk Analysis for Utilizing Cloud Computing - In Perspectives of Legality, Hardware and Non-Hardware." Advanced Materials Research 628 (December 2012): 380–85. http://dx.doi.org/10.4028/www.scientific.net/amr.628.380.

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There is little objective, scientific research focused on evaluating the loss exposure that results from cloud computing. In this study, a modified Delphi method and the analytic hierarchy process were employed to identify and evaluate risks of cloud computing. The findings of this study are: (1) Loss exposures attributable to Jurisdiction, Burglary, Natural disaster, Normal wear and tear or malfunctions are characterized by high frequency but relatively low severity. (2) Loss exposures attributable to Privacy, Damaged or spoiled by employees intentionally or accidentally, and System vulnerabi

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16

Shetty, Nisha P., Balachandra Muniyal, Nandini Proothi, and Bhavya Gopal. "Collusion-resistant multiparty data sharing in social networks." International Journal of Electrical and Computer Engineering (IJECE) 14, no. 2 (2024): 1996. http://dx.doi.org/10.11591/ijece.v14i2.pp1996-2013.

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The number of users on online social networks (OSNs) has grown tremendously over the past few years, with sites like Facebook amassing over a billion users. With the popularity of OSNs, the increase in privacy risk from the large volume of sensitive and private data is inevitable. While there are many features for access control for an individual user, most OSNs still need concrete mechanisms to preserve the privacy of data shared between multiple users. The proposed method uses metrics such as identity leakage (IL) and strength of interaction (SoI) to fine-tune the scenarios that use privacy

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Shetty, Nisha P., Balachandra Muniyal, Nandini Proothi, and Bhavya Gopal. "Collusion-resistant multiparty data sharing in social networks." International Journal of Electrical and Computer Engineering (IJECE) 14, no. 2 (2024): 1996–2013. https://doi.org/10.11591/ijece.v14i2.pp1996-2013.

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The number of users on online social networks (OSNs) has grown tremendously over the past few years, with sites like Facebook amassing over a billion users. With the popularity of OSNs, the increase in privacy risk from the large volume of sensitive and private data is inevitable. While there are many features for access control for an individual user, most OSNs still need concrete mechanisms to preserve the privacy of data shared between multiple users. The proposed method uses metrics such as identity leakage (IL) and strength of interaction (SoI) to fine-tune the scenarios that use privacy

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18

Kim, Soonseok. "Optimizing Privacy in Set-Valued Data: Comparing Certainty Penalty and Information Gain." Electronics 13, no. 23 (2024): 4842. https://doi.org/10.3390/electronics13234842.

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The increase in set-valued data such as transaction records and medical histories has introduced new challenges in data anonymization. Traditional anonymization techniques targeting structured microdata comprising single-attribute- rather than set-valued records are often insufficient to ensure privacy protection in complex datasets, particularly when re-identification attacks leverage partial background knowledge. To address these limitations, this study proposed the Local Generalization and Reallocation (LGR) + algorithm to replace the Normalized Certainty Penalty loss measure (hereafter, NC

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19

Chinh, Do, Nguyen Dung, Animesh Gain, and Heidi Kreibich. "Flood Loss Models and Risk Analysis for Private Households in Can Tho City, Vietnam." Water 9, no. 5 (2017): 313. http://dx.doi.org/10.3390/w9050313.

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20

Wang, Yi-Ren, and Yun-Cheng Tsai. "The Protection of Data Sharing for Privacy in Financial Vision." Applied Sciences 12, no. 15 (2022): 7408. http://dx.doi.org/10.3390/app12157408.

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The primary motivation is to address difficulties in data interpretation or a reduction in model accuracy. Although differential privacy can provide data privacy guarantees, it also creates problems. Thus, we need to consider the noise setting for differential privacy is currently inconclusive. This paper’s main contribution is finding a balance between privacy and accuracy. The training data of deep learning models may contain private or sensitive corporate information. These may be dangerous to attacks, leading to privacy data leakage for data sharing. Many strategies are for privacy protect

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21

Zhang, Qiming, Xuemeng Guo, and Hongchang Li. "The Impact of Financial Risks on Financial Investment in Infrastructure: Based on a Two-Factor Stochastic Differential Equation." Discrete Dynamics in Nature and Society 2021 (October 21, 2021): 1–14. http://dx.doi.org/10.1155/2021/9112739.

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Financial risks, such as inflation and interest rate changes, significantly affect the costs and benefits of infrastructure projects. Nevertheless, there is a dearth of research concerning financial investment (government subsidies) for infrastructure projects in the context of inflation and interest rate changes. Accordingly, this study builds a stochastic differential equation model based on inflation rate and interest rate, through which the expression of government subsidies in public-private partnership is optimised. Specifically, the Monte Carlo simulation was used to undertake a calcula

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22

Wang, Di, and Jinhui Xu. "Differentially Private Empirical Risk Minimization with Smooth Non-Convex Loss Functions: A Non-Stationary View." Proceedings of the AAAI Conference on Artificial Intelligence 33 (July 17, 2019): 1182–89. http://dx.doi.org/10.1609/aaai.v33i01.33011182.

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In this paper, we study the Differentially Private Empirical Risk Minimization (DP-ERM) problem with non-convex loss functions and give several upper bounds for the utility in different settings. We first consider the problem in low-dimensional space. For DP-ERM with non-smooth regularizer, we generalize an existing work by measuring the utility using ℓ2 norm of the projected gradient. Also, we extend the error bound measurement, for the first time, from empirical risk to population risk by using the expected ℓ2 norm of the gradient. We then investigate the problem in high dimensional space, a

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23

Bhattarai, Seema. "Factors Affecting Credit Risk in Nepalese Commercial Banks." Economic Journal of Development Issues 36, no. 1-2 (2023): 79–97. http://dx.doi.org/10.3126/ejdi.v36i1-2.63909.

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This study analyzes the factors affecting credit risk in Nepalese commercial banks. The study comprises data from 27 commercial banks from 2002 to 2020 A.D. For analysis, the Least Square Dummy Variable (LSDV) Regression for model I and Random Effect (RE) Regression Analysis for model II were performed. The effect of the independent variables on credit risk, using loan loss provision and non-performing loans, as proxies of it was examined. While comparing both models, the loan loss provisioning was found to better explain the credit risk. The growth rate of GDP, a macroeconomic variable, had a

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Déroche, Madeleine-Sophie. "Invited perspectives: An insurer's perspective on the knowns and unknowns in natural hazard risk modelling." Natural Hazards and Earth System Sciences 23, no. 1 (2023): 251–59. http://dx.doi.org/10.5194/nhess-23-251-2023.

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Abstract. This paper analyses how the current loss modelling framework that was developed in the 1990s to respond to Hurricane Andrew market crisis falls short in dealing with today's complexity. In effect, beyond reflecting and supporting the current understanding and knowledge of risks, data and models are used in the assessment of situations that have not been experienced yet. To address this question, we considered the (re)insurance market's current body of knowledge on natural hazard loss modelling, the fruit of over 30 years of research conducted by (re)insurers, brokers, modelling firms

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Yang, Ming, Tilei Gao, Rong Jiang, Li Jia, and Di Yang. "Comprehensive Assessment of Mobile Service Privacy Security Based on FAHP and D–S Theory." Wireless Communications and Mobile Computing 2022 (February 23, 2022): 1–20. http://dx.doi.org/10.1155/2022/9547533.

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As an indispensable medium for people’s daily life and communication, mobile applications provide users with a variety of services. In order to enjoy these services, users inevitably need to provide personal privacy information or authorization to application providers in the process of use. In the case of insufficient privacy security evaluation, even if users use the applications verified by the application market, their privacy security will be threatened because of their weak awareness of privacy protection. Therefore, in order to ensure the privacy security of users, this paper establishe

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Fried, Jeremy S., Greg J. Winter, and J. Keith Gilless. "Assessing the benefits of reducing fire risk in the Wildland-urban interface: a contingent valuation approach." International Journal of Wildland Fire 9, no. 1 (1999): 9. http://dx.doi.org/10.1071/wf99002.

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Wildland-urban interface (WUI) residents in Michigan were interviewed using a contingent valuation protocol to assess their willingness-to-pay (WTP) for incremental reductions in the risk of losing their homes to wild-fire. WTP was elicited using a probability model which segments the risk of structure loss into &ldquo;public&rdquo; and &ldquo;private&rdquo; components. Most respondents expressed positive WTP for publicly funded risk reduction activities. These respondents were characterized by tolerance for property taxes, perception of significant risk, high ranking of fire r

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Boutchaktchiev, Vilislav. "Inferred Loss Rate as a Credit Risk Measure in the Bulgarian Banking System." Mathematics 13, no. 9 (2025): 1462. https://doi.org/10.3390/math13091462.

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The loss rate of a bank’s portfolio traditionally measures what portion of the exposure is lost in the case of a default. To overcome the difficulties involved in its computation due to, e.g., the lack of private data, one can utilize an inferred loss rate (ILR). In the existing literature, it has been demonstrated that this indicator has sufficiently close properties to the actual loss rate to facilitate capital adequacy analysis. The current study provides complete mathematical proof of an earlier-stated conjecture, that ILR can be instrumental in identifying a conservative upper bound of th

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Li, Xiaohui, Yuliang Bai, Yajun Wang, and Bo Li. "A trajectory data publishing algorithm satisfying local suppression." International Journal of Distributed Sensor Networks 17, no. 2 (2021): 155014772199340. http://dx.doi.org/10.1177/1550147721993402.

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Suppressing the trajectory data to be released can effectively reduce the risk of user privacy leakage. However, the global suppression of the data set to meet the traditional privacy model method reduces the availability of trajectory data. Therefore, we propose a trajectory data differential privacy protection algorithm based on local suppression Trajectory privacy protection based on local suppression (TPLS) to provide the user with the ability and flexibility of protecting data through local suppression. The main contributions of this article include as follows: (1) introducing privacy pro

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Krohne, Nina, Tina Podlogar, Vanja Gomboc, et al. "Risk of Job Loss During the COVID-19 Pandemic Predicts Anxiety in Women." Medicina 61, no. 2 (2025): 178. https://doi.org/10.3390/medicina61020178.

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Background and Objective: During the COVID-19 pandemic, women faced unique employment-related stressors, including higher exposure to unstable working conditions, increased workload changes due to motherhood, and greater risk of infection in certain jobs. This study explores how these factors influence women’s anxiety and subjective well-being, aiming to identify vulnerable groups. Materials and Methods: 230 employed Slovene women, aged from 19 to 64 years (M = 32.60, SD = 10.41), participated in an online survey containing a State-Trait Anxiety Inventory (STAI-6), WHO-5 Well-being Index, and

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Sultana, Afrin, and Talatu Jalloh. "Loan Loss Provisioning and Profitability of the Private Commercial Banks of Bangladesh." International Journal of Advanced Studies of Economics and Public Sector Management 13, no. 1 (2025): 88–98. https://doi.org/10.48028/iiprds/ijasepsm.v13.i1.07.

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Loan Loss Provisioning is a major regulatory requirement for banks to maintain the stability of financial performance. In Bangladesh, non- performing loans (NPLs), are considered as the biggest challenge of the banking sector. Thus, loan loss provisioning has been an obligatory as well as financial risk management tool for the banks. This study aims to find out the impact of loan loss provisioning on the banks' profitability measured in terms of ROA and ROE. The study covers twenty private commercial banks operating in Bangladesh. The study concentrated the bank specific variables such as bank

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Sultana, Afrin, and Talatu Jalloh. "Loan Loss Provisioning and Profitability of the Private Commercial Banks of Bangladesh." International Journal of Economics and Financial Issues 15, no. 2 (2025): 39–45. https://doi.org/10.32479/ijefi.17439.

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Loan Loss Provisioning is a major regulatory requirement for banks to maintain the stability of financial performance. In Bangladesh, non-performing loans (NPLs), are considered as the biggest challenge of the banking sector. Thus, loan loss provisioning has been an obligatory as well as financial risk management tool for the banks. This study aims to find out the impact of loan loss provisioning on the banks’ profitability measured in terms of ROA and ROE. The study covers twenty private commercial banks operating in Bangladesh. The study concentrated the bank specific variables such as bank

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Esquivel, Luz del Carmen Vilchis. "Plagiarism and loss of identity." South Florida Journal of Development 4, no. 6 (2023): 2553–64. http://dx.doi.org/10.46932/sfjdv4n6-027.

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The widespread plagiarism in various European and eastern countries of Latin American handicrafts can no longer be ignored. This puts at serious risk the design in the areas that are subject to the crude imitation, since patents, not fought for ignorance, ignorance or apathy of the governments, gradually take away the opportunity that local designers, graphics, industrial, textiles, etc., are able to claim the formal codes originating from their regions. This is a niche of research and debate, which should not be ignored, because it is a subject that refers to the legitimacy, origins, identity

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Wang, Ji, Weidong Bao, Lichao Sun, Xiaomin Zhu, Bokai Cao, and Philip S. Yu. "Private Model Compression via Knowledge Distillation." Proceedings of the AAAI Conference on Artificial Intelligence 33 (July 17, 2019): 1190–97. http://dx.doi.org/10.1609/aaai.v33i01.33011190.

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The soaring demand for intelligent mobile applications calls for deploying powerful deep neural networks (DNNs) on mobile devices. However, the outstanding performance of DNNs notoriously relies on increasingly complex models, which in turn is associated with an increase in computational expense far surpassing mobile devices’ capacity. What is worse, app service providers need to collect and utilize a large volume of users’ data, which contain sensitive information, to build the sophisticated DNN models. Directly deploying these models on public mobile devices presents prohibitive privacy risk

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Savic, Ana. "Managing IT-related operational risks." Ekonomski anali 53, no. 176 (2008): 88–109. http://dx.doi.org/10.2298/eka0876088s.

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Not so long ago, information technology (IT) risk occupied a small corner of operational risk - the opportunity loss from a missed IT development deadline. Today, the success of an entire financial institution may lay on managing a broad landscape of IT risks. IT risk is a potential damage to an organization's value, resulting from inadequate managing of processes and technologies. IT risk includes the failure to respond to security and privacy requirements, as well as many other issues such as: human error, internal fraud through software manipulation, external fraud by intruders, obsolesce i

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Modica, Marco, and Roberto Zoboli. "Vulnerability, resilience, hazard, risk, damage, and loss: a socio-ecological framework for natural disaster analysis." Web Ecology 16, no. 1 (2016): 59–62. http://dx.doi.org/10.5194/we-16-59-2016.

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Abstract. Evaluating socio-economic losses due to natural disasters is a challenging task because of the combined complexity of the social and ecological systems affected. However, also under pressure from the expected effects of climate change, evaluating the socio-economic costs of natural catastrophes has become a vital need for policy makers, urban planners, and private agents (such as insurance companies and banks). This paper suggests a general framework encompassing all the important concepts which should be taken into account by the above agents in the assessment of natural disasters.

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Yan, Bin, and Qing Hua Zhao. "Influence Analysis to Beneficial Period and Pricing of Hydraulic Project Based on Risk Allocation." Advanced Materials Research 594-597 (November 2012): 2963–67. http://dx.doi.org/10.4028/www.scientific.net/amr.594-597.2963.

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The public department and the private investor is the commonly contractual subjects of the chartered operating project. Risk sharing idea is an important manifestation to contract justification. The public department determines the compensate degree to private investor through controlling the project’s beneficial period or the chartered operating price. Aim at part of the risk loss that the public department should undertake after risk events had happened; two flexible process models were studied. The adjustment to project beneficial period or product purchasing price was put forward in allusi

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Xiao, Taihong, Yi-Hsuan Tsai, Kihyuk Sohn, Manmohan Chandraker, and Ming-Hsuan Yang. "Adversarial Learning of Privacy-Preserving and Task-Oriented Representations." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 07 (2020): 12434–41. http://dx.doi.org/10.1609/aaai.v34i07.6930.

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Data privacy has emerged as an important issue as data-driven deep learning has been an essential component of modern machine learning systems. For instance, there could be a potential privacy risk of machine learning systems via the model inversion attack, whose goal is to reconstruct the input data from the latent representation of deep networks. Our work aims at learning a privacy-preserving and task-oriented representation to defend against such model inversion attacks. Specifically, we propose an adversarial reconstruction learning framework that prevents the latent representations decode

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Granaturov, V. M., and I. A. Korablinova. "FEATURES AND CONSEQUENCES OF MANIFESTATION OF INFORMATION RISKS AT THE GLOBAL LEVEL IN MODERN CONDITIONS." Proceedings of the O.S. Popov ОNAT 1, no. 1 (2020): 108–19. http://dx.doi.org/10.33243/2518-7139-2020-1-1-108-119.

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The article is devoted to the risk analysis associated with the use of information and information technologies. Activation and deployment of “digital transformation programs” are accompanied by the emergence of new or unfamiliar challenges and threats; they have a significant negative impact on all aspects of society and are called as “information risks”. It has been shown that any modern entity with social and economic relations provides a wide range of information risks. The purpose of the research is to identify and substantiate the existing problems of qualitative analysis of the emergenc

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Abdel-Khalik, A. Rashad. "Why Do Private Companies Demand Auditing? A Case for Organizational Loss of Control." Journal of Accounting, Auditing & Finance 8, no. 1 (1993): 31–52. http://dx.doi.org/10.1177/0148558x9300800103.

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The objective of this paper is to explain the motivation for owners of private companies to voluntarily demand audit (positive) assurance. It is hypothesized that the owner/manager seeks audits as compensatory control systems for the organizational loss of control inherent in hierarchical organizations. Thus, the expected value of wealth at risk due to loss of control sets a lower limit on the amount owners would be willing to pay for audits to compensate for that loss. The hypothesized relationship was tested using information for 103 private companies demanding audit (positive) assurance. Th

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Pramuki, Ni Made Wisni Arie, Bambang Subroto, and Imam Subekti. "Do investors become risk takers after receiving MLA and accounting information?" Journal of Economics, Business & Accountancy Ventura 19, no. 2 (2016): 283. http://dx.doi.org/10.14414/jebav.v19i2.464.

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This study aimed to find out, empirically, the effect of myopic loss aversion and accounting information on the behavior of investors. The method used is pure experiment by using a 2×2 factorial design between subjects. The results show that myopic loss aversion and accounting information positively affects investor behavior. Another result reveals that there is a difference in treatment (frequent and infrequent) that was equally given accounting information. There is a difference of treatment (frequent and infrequent) that was not given accounting information, but the results return obtained

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Ian, Wilbert Raema, and Faturohman Taufik. "Risk Assessment Analysis for the Merger of Online Platform Companies." International Journal of Current Science Research and Review 06, no. 07 (2023): 5259–67. https://doi.org/10.5281/zenodo.8196426.

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Abstract : The risks connected to the merger of Company X and Y, a well-known online platform company, are examined in this research, along with suggestions for efficient risk management tactics. The study identifies potential risks like revenue loss, increased debt, compliance with regulations, conflicts between corporate cultures, and data privacy issues. The research suggests strategies to reduce the identified risks and guarantee a successful merger process after thoroughly analyzing these risks. The recommendations cover the creation of strong risk management strategies, efficient coordin

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He, Yizhang, Kai Wang, Wenjie Zhang, Xuemin Lin, Ying Zhang, and Wei Ni. "Robust Privacy-Preserving Triangle Counting under Edge Local Differential Privacy." Proceedings of the ACM on Management of Data 3, no. 3 (2025): 1–26. https://doi.org/10.1145/3725348.

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Counting the number of triangles in a graph is a fundamental task and has been extensively studied recently. In real-world applications, continuously releasing the triangle count of a graph poses a significant privacy risk for users. To protect sensitive edge information from a central server, we study the problem of estimating the number of triangles under edge local differential privacy (edge LDP). Existing approaches adopt a multi-round computing scheme, allowing the vertices to perform local triangle counting using the noisy graph constructed in the previous round. However, these algorithm

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Donald, L. Buresh Ph.D. Esq. "Should the Private Sector and Prime Contractors Adhere to the Federal FASC and FedRAMP Regulations?" International Journal of Social Science And Human Research 05, no. 12 (2022): 5851–62. https://doi.org/10.5281/zenodo.7472547.

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This article argues that it is in the best interest of private sector organizations and prime contractors to adhere to the Federal Acquisition Supply Chain Security (FASC) and the Federal Risk and Authorization Management Program (FedRAMP) regulations. The paper opines that an organization should follow a supply chain security program, whether from the federal government or otherwise, because such obedience tends to reduce the risk of loss from various factors, including cybercrime. In the modern world, where cyber-attacks from threat actors are common, and the illicit profits gained from such

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Hope, Ole-Kristian, and John Christian Langli. "Auditor Independence in a Private Firm and Low Litigation Risk Setting." Accounting Review 85, no. 2 (2010): 573–605. http://dx.doi.org/10.2308/accr.2010.85.2.573.

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ABSTRACT: We examine the issue of auditor independence in a unique setting. Specifically, we test for auditor independence impairment among (1) private client firms, for which the risk of auditor reputation loss is lower than for publicly traded firms, and (2) in a low litigation environment (i.e., Norway) that further reduces the expected costs to the auditor associated with independence impairment. We have thus chosen a setting that gives independence impairment its best chance of being detected if it exists. Using a large sample of private Norwegian firms, we analyze whether auditors who re

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Zhan, Yuting, Hamed Haddadi, and Afra Mashhadi. "Privacy-Aware Adversarial Network in Human Mobility Prediction." Proceedings on Privacy Enhancing Technologies 2023, no. 1 (2023): 556–70. http://dx.doi.org/10.56553/popets-2023-0032.

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As mobile devices and location-based services are increasingly developed in different smart city scenarios and applications, many unexpected privacy leakages have arisen due to geolocated data collection and sharing. User re-identification and other sensitive inferences are major privacy threats when geolocated data are shared with cloud-assisted applications. Significantly, four spatio-temporal points are enough to uniquely identify 95% of the individuals, which exacerbates personal information leakages. To tackle malicious purposes such as user re-identification, we propose an LSTM-based adv

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Desfontaines, Damien, Andreas Lochbihler, and David Basin. "Cardinality Estimators do not Preserve Privacy." Proceedings on Privacy Enhancing Technologies 2019, no. 2 (2019): 26–46. http://dx.doi.org/10.2478/popets-2019-0018.

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Abstract Cardinality estimators like HyperLogLog are sketching algorithms that estimate the number of distinct elements in a large multiset. Their use in privacy-sensitive contexts raises the question of whether they leak private information. In particular, can they provide any privacy guarantees while preserving their strong aggregation properties? We formulate an abstract notion of cardinality estimators, that captures this aggregation requirement: one can merge sketches without losing precision. We propose an attacker model and a corresponding privacy definition, strictly weaker than differ

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Morgan, Jill, and Mark Stallworthy. "Indemnifying against flood loss in a changing environment." Legal Studies 33, no. 2 (2013): 239–63. http://dx.doi.org/10.1111/j.1748-121x.2012.00245.x.

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The UK, as elsewhere, faces new environmental uncertainties, especially from climate change. The sustainability of the UK's existing flood loss indemnity regime in respect of property harm is threatened by factors that include greater ecological awareness on the part of policy makers, pressures to limit public commitments to flood defence, and insurers' increasing technical capacities to differentiate risk exposure across particular locations. The basis of current reliance on the commercial insurance market is called into question, as general levels of insurance availability and affordability

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Sayan Basak, Mayur Jadhav, Suraj Choudhary, Pranjal Kadam, and Sheetal P. Gawande. "Web Application Security: A Survey." International Research Journal on Advanced Engineering and Management (IRJAEM) 2, no. 08 (2024): 2694–98. http://dx.doi.org/10.47392/irjaem.2024.0390.

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Web applications play a crucial role in modern digital interactions by supporting a wide range of online activities, from social networking to e-commerce. However, the widespread use of web applications has also made security flaws visible and important. This article explores the complex topic of web application security, examining common attack paths, their effects, and the need for strong security measures. Phishing, XSS, and SQL Injection are some common web application attacks that provide a serious risk of financial loss, reputational loss, and privacy violations. The study emphasizes the

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Lowy, Andrew, and Meisam Razaviyayn. "Private Stochastic Optimization with Large Worst-Case Lipschitz Parameter." Journal of Privacy and Confidentiality 15, no. 1 (2025). https://doi.org/10.29012/jpc.909.

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We study differentially private (DP) stochastic optimization (SO) with loss functions whose worst-case Lipschitz parameter over all data points may be huge or infinite. To date, the most work on DP SO assumes that the loss is uniformly Lipschitz continuous over data (i.e. stochastic gradients are uniformly bounded over all data points). While this assumption is convenient, it often leads to pessimistic excess risk bounds. In practical problems, the worst-case Lipschitz parameter of the loss over all data points may be huge due to outliers and/or heavy-tailed data. In such cases, the error boun

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Jia, Ruo, Jieyu Lin, Michael R. Powers, and Hanyang Wang. "Catastrophe risk sharing among individuals, private insurance, and government." Journal of Risk and Insurance, January 29, 2025. https://doi.org/10.1111/jori.12506.

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AbstractLimited research has been conducted on the optimal public–private risk‐sharing for catastrophe risks. This paper develops a theoretical framework to study the risk‐sharing decisions and interactions of three types of catastrophe‐market participants: a large number of individuals, a large number of private insurers in a competitive market, and a government that can choose between alternatives of re/insurance or ex post relief. Our analysis shows that the optimal government intervention varies depending on the correlation levels among individual losses. For moderately positive levels of

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