Online advertising: analysis of privacy threats and protection approaches

Online advertising, the pillar of the “free” content on the Web, has revolutionized the marketing business in recent years by creating a myriad of new opportunities for advertisers to reach potential customers. The current advertising model builds upon an intricate infrastructure composed of a variety of intermediary entities and technologies whose main aim is to deliver personalized ads. For this purpose, a wealth of user data is collected, aggregated, processed and traded behind the scenes at an unprecedented rate. Despite the enormous value of online advertising, however, the intrusiveness and ubiquity of these practices prompt serious privacy concerns. This article surveys the online advertising infrastructure and its supporting technologies, and presents a thorough overview of the underlying privacy risks and the solutions that may mitigate them. We first analyze the threats and potential privacy attackers in this scenario of online advertising. In particular, we examine the main components of the advertising infrastructure in terms of tracking capabilities, data collection, aggregation level and privacy risk, and overview the tracking and data-sharing technologies employed by these components. Then, we conduct a comprehensive survey of the most relevant privacy mechanisms, and classify and compare them on the basis of their privacy guarantees and impact on the Web.Peer ReviewedPostprint (author's final draft

Regulating Mobile Mental Health Apps

Mobile medical apps (MMAs) are a fast‐growing category of software typically installed on personal smartphones and wearable devices. A subset of MMAs are aimed at helping consumers identify mental states and/or mental illnesses. Although this is a fledgling domain, there are already enough extant mental health MMAs both to suggest a typology and to detail some of the regulatory issues they pose. As to the former, the current generation of apps includes those that facilitate self‐assessment or self‐help, connect patients with online support groups, connect patients with therapists, or predict mental health issues. Regulatory concerns with these apps include their quality, safety, and data protection. Unfortunately, the regulatory frameworks that apply have failed to provide coherent risk‐assessment models. As a result, prudent providers will need to progress with caution when it comes to recommending apps to patients or relying on app‐generated data to guide treatment

Understanding Ecommerce Consumer Privacy From the Behavioral Marketers\u27 Viewpoint

Ecommerce sales were expected to increase to $4.8 trillion dollars in 2021 for online retailers in the United States. Behavioral marketers increase sales and revenue by targeting potential customers based on the use of ecommerce consumers\u27 personal information. This correlational research study was framed with the theory of planned behavior. The participants were behavioral marketers based in the United States who completed an online survey. The data were analyzed using multiple regressions and analysis of variance analyses to answer the research question. The results of the analysis answered the research question regarding the correlation between behavioral marketer\u27s attitudes, social norms, and perceived behavioral control (PBC), especially concerning the collection of ecommerce consumers\u27 personal information. The results of the analyses indicated attitude is a strong predictor for behavior intention, as indicated by a positive correlation. The ρ value was greater than .05; therefore, the null hypothesis was rejected. The social norms and PBC variables were not significant. Social norms resulted in F (14,18) = 2.298, ρ = .026. The p value is less than .05; therefore, the null hypothesis was accepted. PBC results were F (78,5) = 4.263, ρ = .048. The p value was less than .05; therefore, the null hypothesis was accepted. The findings showed that behavioral marketers have a strong correlation between their attitude and intention to protect ecommerce privacy. Behavioral managers might benefit from this study and contribute to social change by taking the lead in their organizations to change data collection methods to reduce the number of security breaches

Users\u27 Knowkedge and Social Media Sharing Behaviors

The success of social media marketing tactics is highly dependent on the understanding of social media users\u27 information sharing behaviors. Social media user’s likelihood to share is related to various factors, such as knowledge, belief and personality traits. Survey data from 504 American social media users reveals that users\u27 perceived knowledge about social media marketing tactics positively related to their perceived benefits, which further associated with their likelihood of sharing information on social media. Findings also indicate that users\u27 desire for control partially mediates relationship between users’ knowledge of social media tactics and their likelihood to share information. However, the data does not provide evidence for the expected relationship between knowledge, perceived privacy risk and social media sharing behaviors. The findings reinforce the expectancy-value model, indicating the relationship between social media users’ perception of positive self-performance in evaluating social media marketing tactics and the activeness of social media use. The author also discusses the privacy paradox in social media use

Empirical Studies on Online Information Privacy Concerns: Literature Review and an Integrative Framework

In the e-commerce environment, individuals’ concerns for online information privacy play critical roles in determining their intention to use the Internet to provide personal information for services and transactions. Understanding this relationship has important implications for e-commerce. Despite much research in this area, an overarching picture of the relationship between information privacy concerns and the antecedent and consequence factors is yet to be drawn. Based on a review on empirical studies in this area, this research summarizes the conceptualizations of privacy concerns and the antecedents and consequences. An integrative framework is developed to illustrate the relationships between the factors. In this framework, a person’s concern for information privacy regarding a specific e-commerce website is distinguished from his/her concern for information privacy regarding the general e-commerce environment. These two forms of privacy concerns have distinct impacts on a person’s online behavior. Their relationships with multiple antecedent and consequence factors are analyzed