Artificial Intelligence Is Safer for My Privacy: Interplay Between Types of Personal Information and Agents on Perceived Privacy Risk and Concerns

2021 ◽  
Author(s):  
Jungwon Kim ◽  
Yongjun Sung
Keyword(s):  
Artificial Intelligence ◽  
Personal Information ◽  
Privacy Risk

Smishing Detection: Using Artificial Intelligence

2021 ◽  
Vol 9 (8) ◽  
pp. 2218-2224
Author(s):  
Samyak Sadanand Shravasti
Keyword(s):  
Artificial Intelligence ◽  
Short Message Service ◽  
Personal Information ◽  
Critical Issue ◽  
Cyber Attacks ◽  
Sensitive Information ◽  
Short Message ◽  
Proposed Model ◽  
Message Service ◽  
A Company

Abstract: Phishing occurs when people's personal information is stolen via email, phone, or text communications. In Smishing Short Message Service (SMS) is used for cyber-attacks, Smishing is a type of theft of sensitive information. People are more likely to give personal information such as account details and passwords when they receive SMS messages. This data could be used to steal money or personal information from a person or a company. As a result, Smishing is a critical issue to consider. The proposed model uses an Artificial Intelligence to detect smishing. Analysing a SMS and successfully detecting Smishing is possible. Finally, we evaluate and analyse our proposed model to show its efficacy. Keywords: Phishing, Smishing, Artificial Intelligence, LSTM, RNN

A Decision Support System for Privacy Compliance

2012 ◽  
pp. 158-180 ◽  
Author(s):  
Siani Pearson ◽  
Tomas Sander
Keyword(s):  
Risk Assessment ◽  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Personal Information ◽  
Regulatory Compliance ◽  
Privacy Management ◽  
Privacy Risk ◽  
Global Company

Regulatory compliance in areas such as privacy has become a major challenge for organizations. In large organizations there can be hundreds or thousands of projects that involve personal information. Ensuring that all those projects properly take privacy considerations into account is a complex challenge for accountable privacy management. Accountable privacy management requires that an organization makes sure that all relevant projects are in compliance and that there is evidence and assurance that this actually is the case. To date, there has been no suitable automated, scalable support for accountable privacy management; it is such a tool that the authors describe in this chapter. Specifically, they describe a privacy risk assessment and compliance tool which they are developing and rolling out within a large, global company – called HP Privacy Advisor (HP PA) – and its generalisation and extension. The authors also bring out those security, privacy, risk, and trust-related aspects they have been researching related to this work in particular.

A Decision Support System for Privacy Compliance

Data Mining ◽  
2013 ◽  
pp. 1496-1518 ◽  
Author(s):  
Siani Pearson ◽  
Tomas Sander
Keyword(s):  
Risk Assessment ◽  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Personal Information ◽  
Regulatory Compliance ◽  
Privacy Management ◽  
Privacy Risk ◽  
Global Company

Regulatory compliance in areas such as privacy has become a major challenge for organizations. In large organizations there can be hundreds or thousands of projects that involve personal information. Ensuring that all those projects properly take privacy considerations into account is a complex challenge for accountable privacy management. Accountable privacy management requires that an organization makes sure that all relevant projects are in compliance and that there is evidence and assurance that this actually is the case. To date, there has been no suitable automated, scalable support for accountable privacy management; it is such a tool that the authors describe in this chapter. Specifically, they describe a privacy risk assessment and compliance tool which they are developing and rolling out within a large, global company – called HP Privacy Advisor (HP PA) – and its generalisation and extension. The authors also bring out those security, privacy, risk, and trust-related aspects they have been researching related to this work in particular.

scholarly journals Effects of Privacy Policy and Government Regulation on Trust of Consumers in Saudi Arabia: An Empirical Study

2019 ◽  
Vol 5 (4) ◽  
pp. 7-24
Author(s):  
Alharbi Nesreen Nasser A. ◽  
Yanhui Li
Keyword(s):  
Government Regulation ◽  
Online Survey ◽  
Negative Impact ◽  
Positive Impact ◽  
Personal Information ◽  
Privacy Policy ◽  
Privacy Rights ◽  
Privacy Risk ◽  
Online Questionnaire ◽  
Government Regulations

The research aimed to analyze the influence of privacy policy and government regulation on privacy risk concerns and trust. In other words, this paper attempted to highlight the importance of privacy policy and government regulations, which are two important aspects related to user’s privacy rights. Data were collected through an online questionnaire to test the relationships between each FTC category in online privacy statements of websites/Government regulation and its effect on trust/privacy concerns and relationships. Two hundred sixty-eight respondents participated in the online survey. Results of the study indicate that the privacy policy has a positive impact on trust, whereas privacy risk concerns have a negative impact on trust. A clear and transparent privacy policy helps organizations to establish good relationships with consumers. Additionally, the privacy policy has a negative impact on privacy risk concerns. A strong and powerful privacy policy will significantly improve users’ conservative attitudes about information sharing and privacy disclosure risks. Finally, government regulation has a positive impact on trust and a negative impact on privacy risk concerns. Government regulations such as disclosure, sharing, and use of personal information must be enforced to increase the willingness to use users’ information, thereby enhancing users’ trust in the relevant privacy policy protection laws. Clear and effective laws and regulations reduce users’ fear of privacy policy; that is, the quality of the law will effectively motivate users to provide personal information. The findings of the research imply that there is a high level of concern among the citizens linked to their privacy risk, indicating people do not trust e-government sufficiently. Taking into consideration weak spots related to e-government policies a cybersecurity plan should be implemented. Besides that, consumers’ trust related to privacy policy should be increased. This can be done by improving the standards for a privacy policy.

Ambiguities in the Privacy Policies of Common Health and Fitness Apps

2021 ◽  
pp. 1839-1849
Author(s):  
Devjani Sen ◽  
Rukhsana Ahmed
Keyword(s):  
Personal Information ◽  
Personal Data ◽  
Online Privacy ◽  
Risk Category ◽  
Health And Wellness ◽  
Privacy Risk ◽  
Privacy Policies ◽  
Health And Fitness ◽  
Privacy Risks ◽  
Risk Categories

With a growing number of health and wellness applications (apps), there is a need to explore exactly what third parties can legally do with personal data. Following a review of the online privacy policies of a select set of mobile health and fitness apps, this chapter assessed the privacy policies of four popular health and fitness apps, using a checklist that comprised five privacy risk categories. Privacy risks, were based on two questions: a) is important information missing to make informed decisions about the use of personal data? and b) is information being shared that might compromise the end-user's right to privacy of that information? The online privacy policies of each selected app was further examined to identify important privacy risks. From this, a separate checklist was completed and compared to reach an agreement of the presence or absence of each privacy risk category. This chapter concludes with a set of recommendations when designing privacy policies for the sharing of personal information collected from health and fitness apps.

Ambiguities in the Privacy Policies of Common Health and Fitness Apps

2021 ◽  
pp. 1575-1586
Author(s):  
Devjani Sen ◽  
Rukhsana Ahmed
Keyword(s):  
Personal Information ◽  
Personal Data ◽  
Online Privacy ◽  
Risk Category ◽  
Health And Wellness ◽  
Privacy Risk ◽  
Privacy Policies ◽  
Health And Fitness ◽  
Privacy Risks ◽  
Risk Categories

With a growing number of health and wellness applications (apps), there is a need to explore exactly what third parties can legally do with personal data. Following a review of the online privacy policies of a select set of mobile health and fitness apps, this chapter assessed the privacy policies of four popular health and fitness apps, using a checklist that comprised five privacy risk categories. Privacy risks, were based on two questions: a) is important information missing to make informed decisions about the use of personal data? and b) is information being shared that might compromise the end-user's right to privacy of that information? The online privacy policies of each selected app was further examined to identify important privacy risks. From this, a separate checklist was completed and compared to reach an agreement of the presence or absence of each privacy risk category. This chapter concludes with a set of recommendations when designing privacy policies for the sharing of personal information collected from health and fitness apps.

scholarly journals Purchasing Behaviour on Social Commerce Platforms: An Examination of Canadian Consumers

2021 ◽  
Author(s):  
Zainab Khan
Keyword(s):  
Social Presence ◽  
Purchase Intention ◽  
Personal Information ◽  
Social Commerce ◽  
Privacy Risk ◽  
Internet Privacy ◽  
Media Technologies ◽  
Consumer Purchase Intention ◽  
Purchasing Behaviour

As social media technologies become more embedded within the online shopping interface, the phenomenon of social commerce arises. This research examines the role of social commerce in influencing consumer purchase intention. Specifically, factors investigated are social presence, consumer’s security perceptions, perceived internet privacy risk, trust and willingness to provide personal information to transact. The study found that security perception, trust and willingness to provide personal information to transact have a significant influence on consumer purchase intention.

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