Internet Privacy

Internet Privacy

Nathan John Rodriguez (Weber State University, USA)
Copyright: © 2020 |Pages: 17
DOI: 10.4018/978-1-5225-9715-5.ch049

Abstract

In recent years, consumers have become more knowledgeable about the risks of submitting personal information online. Yet despite being familiar with these risks, many users do not act to secure their privacy online. Variations of the axiom, “If the service is free, you are the product” point to what is often viewed as a tacit agreement entered by users to exchange their personal data for a more personalized online experience. This entry begins with a broad theoretical discussion of internet privacy before examining the concept through the perspective of user activity, corporate data collection, and malevolent actors. Various solutions to increase awareness of privacy risk and proactively protect personal information are discussed, as well as directions for future research and legislation.
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Background

Privacy Theories

One of the earliest definitions of privacy is “the right to be let alone” (Warren & Brandeis, 1890). The notion of privacy encompasses territorial privacy, personal privacy and informational privacy (Rosenberg, 1992). There are a variety of potential dimensions to informational privacy, but a broader definition of these concerns has been characterized as the unauthorized use of personal information. (Smith, Milberg, & Burke, 1996).

Online privacy studies have focused on the motivation for privacy protection as well as the behavior related to privacy protection. Internet privacy research frequently relies upon protection motivation theory (PMT), which posits that individuals engage in a rational thought process, and protect themselves based on the perceived severity of a negative outcome, the probability of that event occurring, and the efficacy of a potential solution (Rogers, 1975). PMT has undergone several iterations in recent years, and an extended parallel process model (EPPM) emerged to address these deficiencies by explaining why—even in the face of a high-perceived threat—a user may not change their behavior. Recent studies have shown that internet users “tend to ignore privacy risks until they encounter monetary loss online in person” (Chen, Beaudoin, & Hong, 2017, p. 300).

The Privacy Paradox describes the incongruent way in which users frequently express a theoretical interest in protecting their privacy, yet do not engage in behaviors that would protect their privacy (Norberg, Horne, & Horne, 2007; Brown, 2001). A thorough review of Privacy Paradox literature concluded that decision-making regarding privacy may be a rational calculation of risk and reward, a biased and irrational risk assessment, or a situation that involves virtually no calculation (Barth & de Jong, 2017). The authors concluded that decision-making tends to occur more frequently on an irrational rather than a rational level, as individuals tend to follow their intuition with little regard to privacy risks.

Key Terms in this Chapter

Cloud Computing: The use of remote servers via the internet—rather than a local server or personal computer—to store and process data.

Big Data: A data set this is too large for “standard” software programs, and is generally used to identify large trends, and predict behaviors and outcomes.

Privacy Paradox: Individuals often claim to be concerned about threats to their privacy, yet do not act to protect their personal information.

Private Browsing Mode: A privacy feature in web browsers that disables a user’s browser and search history.

Cookies: Small text files that are placed on a user’s web browser as they visit a website.

Protection Motivation Theory: This concept attempts to explain the way in which individuals react to perceived threats, and holds that individuals consider the perceived severity and probability of a threat, as well as the efficacy of their potential response.

Data Breach: An incident where information is accessed without authorization.

Internet of Things: A network of physical objects embedded with sensors that enable them to collect and share data.

Phishing: An attempt to obtain a user’s sensitive data through the use of a fraudulent identity via electronic communication.

Virtual Private Network: A technology that uses an encrypted connection to add security and privacy to private and public networks.

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