scholarly journals Joint optimisation of privacy and cost of in-app mobile user profiling and targeted ads

2020 ◽  
Author(s):  
Imdad Ullah
Keyword(s):  
User Behavior ◽  
Personal Data ◽  
Cost Effective ◽  
Mobile User ◽  
User Profiling ◽  
Mixed Integer ◽  
Time Varying ◽  
User Privacy ◽  
Equivalent Problem ◽  
Dynamic Optimisation

Online mobile advertising ecosystems provide advertising and analytics services that collect, aggregate, process and trade rich amount of consumer's personal data and carries out interests-based ads targeting, which raised serious privacy risks and growing trends of users feeling uncomfortable while using internet services. In this paper, we address user's privacy concerns by developing an optimal dynamic optimisation cost-effective framework for preserving user privacy for profiling, ads-based inferencing, temporal apps usage behavioral patterns and interest-based ads targeting. A major challenge in solving this dynamic model is the lack of knowledge of time-varying updates during profiling process. We formulate a mixed-integer optimisation problem and develop an equivalent problem to show that proposed algorithm does not require knowledge of time-varying updates in user behavior. Following, we develop an online control algorithm to solve equivalent problem using Lyapunov optimisation and to overcome difficulty of solving nonlinear programming by decomposing it into various cases and achieve trade-off between user privacy, cost and targeted ads. We carry out extensive experimentations and demonstrate proposed framework's applicability by implementing its critical components using POC `System App'. We compare proposed framework with other privacy protecting approaches and investigate that it achieves better privacy and functionality for various performance parameters.<br>

scholarly journals Joint optimisation of privacy and cost of in-app mobile user profiling and targeted ads

2020 ◽  
Author(s):  
Imdad Ullah
Keyword(s):  
User Behavior ◽  
Personal Data ◽  
Cost Effective ◽  
Mobile User ◽  
User Profiling ◽  
Mixed Integer ◽  
Time Varying ◽  
User Privacy ◽  
Equivalent Problem ◽  
Dynamic Optimisation

Online mobile advertising ecosystems provide advertising and analytics services that collect, aggregate, process and trade rich amount of consumer's personal data and carries out interests-based ads targeting, which raised serious privacy risks and growing trends of users feeling uncomfortable while using internet services. In this paper, we address user's privacy concerns by developing an optimal dynamic optimisation cost-effective framework for preserving user privacy for profiling, ads-based inferencing, temporal apps usage behavioral patterns and interest-based ads targeting. A major challenge in solving this dynamic model is the lack of knowledge of time-varying updates during profiling process. We formulate a mixed-integer optimisation problem and develop an equivalent problem to show that proposed algorithm does not require knowledge of time-varying updates in user behavior. Following, we develop an online control algorithm to solve equivalent problem using Lyapunov optimisation and to overcome difficulty of solving nonlinear programming by decomposing it into various cases and achieve trade-off between user privacy, cost and targeted ads. We carry out extensive experimentations and demonstrate proposed framework's applicability by implementing its critical components using POC `System App'. We compare proposed framework with other privacy protecting approaches and investigate that it achieves better privacy and functionality for various performance parameters.<br>

scholarly journals METHOD OF MARKETPLACE LEGITIMATE USER AND ATTACKER PROFILING

2021 ◽  
Vol 2 (14) ◽  
pp. 50-67
Author(s):  
Diana Tsyrkaniuk ◽  
Volodymyr Sokolov ◽  
Nataliia Mazur ◽  
Valerii Kozachok ◽  
Volodymyr Astapenya
Keyword(s):  
Linear Regression ◽  
User Behavior ◽  
Personal Data ◽  
User Profiling ◽  
Linear Regression Method ◽  
Error Matrix ◽  
Legitimate User ◽  
Online Stores ◽  
Python Programming

The number and complexity of cybercrime are constantly growing. New types of attacks and competition are emerging. The number of systems is growing faster than new cybersecurity professionals are learning, making it increasingly difficult to track users' actions in real-time manually. E-commerce is incredibly active. Not all retailers have enough resources to maintain their online stores, so they are forced to work with intermediaries. Unique trading platforms increasingly perform the role of intermediaries with their electronic catalogs (showcases), payment and logistics services, quality control - marketplaces. The article considers the problem of protecting the personal data of marketplace users. The article aims to develop a mathematical behavior model to increase the protection of the user's data to counter fraud (antifraud). Profiling can be built in two directions: profiling a legitimate user and an attacker (profitability and scoring issues are beyond the scope of this study). User profiling is based on typical behavior, amounts, and quantities of goods, the speed of filling the electronic cart, the number of refusals and returns, etc. A proprietary model for profiling user behavior based on the Python programming language and the Scikit-learn library using the method of random forest, linear regression, and decision tree was proposed, metrics were used using an error matrix, and algorithms were evaluated. As a result of comparing the evaluation of these algorithms of three methods, the linear regression method showed the best results: A is 98.60%, P is 0.01%, R is 0.54%, F is 0.33%. 2% of violators have been correctly identified, which positively affects the protection of personal data.

Strategy evolution of information diffusion under time-varying user behavior in generalized networks

2017 ◽  
Vol 100 ◽  
pp. 91-103 ◽  
Author(s):  
Eleni Stai ◽  
Vasileios Karyotis ◽  
Antonia-Chrysanthi Bitsaki ◽  
Symeon Papavassiliou
Keyword(s):  
Information Diffusion ◽  
User Behavior ◽  
Time Varying ◽  
Generalized Networks

scholarly journals Online Privacy Analysis and Hints for Its Improvement

10.28945/3216 ◽  
2008 ◽  
Author(s):  
Tanja Krunic ◽  
Ljiljana Ruzic-Dimitrijevic
Keyword(s):  
Personal Data ◽  
Online Privacy ◽  
Short Report ◽  
User Privacy ◽  
Data Collecting ◽  
Privacy Analysis ◽  
The Web ◽  
The Eu

The idea of the paper is to investigate how much the online user privacy is respected by website owners, and how online privacy can be improved. We first focus ourselves on issues like possibilities of misusing personal data, data collecting and user-tracking. Then we give a short report about legislation in the EU concerning user privacy. Some facts about user confidence are given as well. They are follows by a brief list of hints for the users to protect their personal data when surfing the Web. Then we give an overview of actions website owners should take in order to support user privacy. Finally, we present the results of our investigation of the condition of user privacy in practice, and give some suggestions on its improvement.

scholarly journals Design parameters influencing the operation of a CHP plant within a micro-grid: application of the ANOVA test

2020 ◽  
Vol 197 ◽  
pp. 01002
Author(s):  
Alberto Fichera ◽  
Arturo Pagano ◽  
Rosaria Volpe
Keyword(s):  
Power Systems ◽  
Programming Model ◽  
Cost Effective ◽  
Combined Heat And Power ◽  
Mixed Integer ◽  
Design Parameters ◽  
Statistical Tool ◽  
Cogeneration System ◽  
Micro Grid ◽  
Cost Parameters

Combined heat and power systems are widely recognized as a cost-effective solution for the achievement of sustainable and energy efficiency goals. During the last decade, cogeneration systems have been extensively studied from both the technological and operational viewpoints. However, the operation of a cogeneration system is a topic still worth of investigation. In fact, along with the determination of the optimal configurations of the combined heat and power systems, it is likewise fundamental to increase the awareness on the design and cost parameters affecting the operation of cogeneration systems, especially if considering the micro-grid in which they are inserted. In this direction, this paper proposed a mixed integer linear programming model with the objective of minimizing the total operational costs of the micro-grid. Different scenarios include the satisfaction of the cooling demands of the micro-grid as well as the opportuneness to include a heat storage. The influence of the main design and cost parameters on the operation of the micro-grid has been assessed by adopting the statistical tool ANOVA (Analysis Of Variance). The model and the experimental application of the ANOVA have been applied to a micro-grid serving a hospital located in the South of Italy.

Mobile User Behaviors in China

2015 ◽  
pp. 1110-1128
Author(s):  
Minglong Lei ◽  
Weidong Liu ◽  
Yusong Gao ◽  
Tingshao Zhu
Keyword(s):  
Mobile Phones ◽  
User Behavior ◽  
Mobile User ◽  
User Behavior Analysis ◽  
Related Literature ◽  
User Behaviors ◽  
Analysis Process ◽  
Mobile Industry ◽  
The Mainland Of China ◽  
The Relationship

The development of the mobile industry makes it necessary for scholars to study mobile user behaviors in the mainland of China. This article is divided into three main parts after a brief introduction of the current Chinese mobile phone market. The first part is to demonstrate mobile use and its influencing factors in the mainland of China, and then to determine the mostly studied mobile usages among those articles. The second part pays attention to the effect brought by the use of mobile phones, and then checks the relationship between mobile addiction and other social behaviors. The last part is to illustrate the methods employed in the mobile user behavior analysis. After stating the analysis process of user behaviors, the authors attempted to summarize the main features extracted from data mining technology. Finally, the authors put forward some possible directions under the topic of mobile user behavior after careful review of the related literature.

Theft Preventive Measures for Interconnected Personal Computer Devices as Proactive Physical Security of Data

2021 ◽  
pp. 337-352
Author(s):  
Ekaterina Pshehotskaya ◽  
Oleg Mikhalsky
Keyword(s):  
User Behavior ◽  
Personal Data ◽  
Data Access ◽  
Security And Privacy ◽  
Portable Devices ◽  
Physical Security ◽  
Security Risks ◽  
Portable Computer ◽  
Relative Risks ◽  
And Control

This article is concerned with the arising problems and implications of physical security and privacy of personal and control data on portable computer devices, especially smartphones. The authors consider various classifications of portable computer devices, isolate smartphones as a most common device, and study types of user behavior regarding the involved security risks of unauthorized access to the data stored both locally and remotely with accent of physical data access via device theft. Based on provided categorization the researchers discuss the factors and criteria suitable to generalize user patterns and evaluate the corresponding vulnerability level against specified statistics. The considered statistical criteria can be formulated as a mathematical model of relative risks and implemented as a service or an application to be used for improving user awareness on current threats to his personal data and respective interconnected personal portable devices.

scholarly journals A Green Demand-Responsive Airport Shuttle Service Problem with Time-Varying Speeds

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Ming Wei ◽  
Binbin Jing ◽  
Jian Yin ◽  
Yang Zang
Keyword(s):  
Time Windows ◽  
Operating Cost ◽  
Model Performance ◽  
Path Selection ◽  
Mixed Integer ◽  
Time Varying ◽  
Alternative Fuel Vehicles ◽  
Nsga Ii ◽  
The Difference ◽  
On The Road

This study proposes a multiobjective mixed integer linear programming (MOMILP) model for a demand-responsive airport shuttle service. The approach aims to assign a set of alternative fuel vehicles (AFVs) located at different depots to visit each demand point within the specified time and transport all of them to the airport. The proposed model effectively captures the interactions between path selection and environmental protection. Moreover, users with flexible pick-up time windows, the time-varying speed of vehicles on the road network, and the limited fuel for the route duration are also fully considered in this model. The work aims at simultaneously minimizing the operating cost, vehicle fuel consumption, and CO2 emissions. Since this task is an NP-hard problem, a heuristic-based nondominated sorting genetic algorithm (NSGA-II) is also presented to find Pareto optimal solutions in a reasonable amount of time. Finally, a real-world example is provided to illustrate the proposed methodology. The results demonstrate that the model not only selects an optimal depot for each AFV but also determines its route and timetable plan. A sensitivity analysis is also given to assess the effect of early/late arrival penalty weights and the number of AFVs on the model performance, and the difference in quality between the proposed and traditional models is compared.

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