Smartphones and Internet have become prevalent in our society with various applications in businesses, education, healthcare, gaming, and research. One of the major issues with the Internet today is its lack of security since an eavesdropper can potentially intercept the communication. This has contributed towards an increased number of cyber-crime incidents, resulting in an increase in users’ consciousness about the security and privacy of their communication. One example is the shift towards using private browsers such as Tor. Tor is a well-recognized and widely used privacy browser based on The Onion Router network that provisions anonymity over the insecure Internet. This functionality of Tor has been a major hurdle in cybercrime investigations due to the complex nature of its anonymity. This paper investigates artifacts from the Tor privacy browser on the latest Windows 10 and Android 10 devices to determine potential areas where evidence can be found. We examine the registry, storage, and memory of Windows 10 devices and the memory, storage, logs, and Zram of Android 10 devices for three possible scenarios i.e. before, during, and after use of the Tor browser. Our results do not support the claims made by the Tor Project regarding user privacy and anonymity. We find that it is possible to retrieve significant details about a user’s browsing activities while the Tor browser is in use as well as after it is closed (on both operating systems). This paper also provides an investigative methodology for the acquisition and analysis of Tor browser artifacts from different areas of the targeted operating systems. Therefore, it can serve as a base to expand research in the forensic analysis of other privacy browsers and improve the efficiency of cybercrime investigations efficiency.

An organization’s privacy policy states how it collects, stores, processes, and shares its users’ personal information. The growing number of data protection laws and regulations, as well as the numerous sectors where the organizations are collecting user information, has led to the investigation of privacy policies with regards to their accessibility, readability, completeness, comparison with organization’s actual data practices, use of machine learning/natural language processing for automated analysis, and comprehension/perception/concerns of end-users via summarization/visualization tools and user studies. However, there is limited work on systematically reviewing the existing research on this topic. We address this gap by conducting a systematic review of the existing privacy policy literature. To this end, we compiled and analyzed 202 papers (published till 31st December, 2023) that investigated privacy policies. Our work advances the field of privacy policies by summarizing the analysis techniques that have been used to study them, the data protection laws/regulations explored, and the sectors to which these policies pertain. We provide actionable insights for organizations to achieve better end-user privacy.

Privacy laws in South Asian countries are still at a nascent stage. Therefore, South Asian websites are susceptible to user privacy violation. This paper presents an assessment of website privacy policies from 10 sectors in the three largest South Asian economies, namely, India, Pakistan, and Bangladesh. Using a manual qualitative analysis on a dataset of 284 popular websites, we assessed the policies based on accessibility, readability, and compliance with 11 privacy principles. Our findings show that overall, the privacy statement accessibility, and privacy compliance of websites from the three countries is low especially in the education, healthcare, and government sectors. Readability is quite low for websites in all 10 sectors of the three countries. Privacy compliance in each country is the highest for the principles of data processing and third-party transfer, whereas it is the lowest for protection of children’s data, data retention and portability. Indian websites performed comparatively better amongst the three countries on all three metrics, followed by Pakistan, and Bangladesh. Based on our results, we provide recommendations involving all stakeholders (i.e., website owners, privacy regulators, and users) to help improve privacy protection of user data in South Asia.

Purpose: During the past few years, social media has faced the challenge of maintaining its user base. Reports show that the social media giants such as Facebook and Twitter experienced a decline in their users. Taking WhatsApp's recent change of its terms of use as the case of this study and using the push-pull-mooring model and a configurational perspective, this study aims to identify pathways for switching intentions.Design/methodology/approach: Data were collected from 624 WhatsApp users recruited from Amazon Mechanical Turk and analyzed using fuzzy set qualitative comparative analysis (fsQCA).Findings: The findings identify seven configurations for high switching intentions and four configurations for low intentions to switch. Firm reputation and critical mass increase intention to switch, while low firm reputation and absence of attractive alternatives hinder switching.Research limitations/implications: This study extends extant literature on social media migration by identifying configurations that result in high and low switching intention among messaging applications.Practical implications: The study identifies factors the technology service providers should consider to attract new users and retain existing users.Originality/value: This study complements the extant literature on switching intention that explains the phenomenon based on a net-effect approach by offering an alternative view that focuses on the existence of multiple pathways to social media switching. It further advances the authors’ understanding of the relevant importance of switching factors.