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Anirudh Ekambaranathan

dblp:264/7965 · DBLP profile ↗
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3ranked-venue papers
3as first author
3since 2021 · last 2023
0000-0003-1795-0400ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Human-computer interaction and ubiquitous computing · 2 · 2 first-author · 2 since 2021Security and privacy · 1 · 1 first-author · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Network and information security
2 papers
Privacy and data protection · 76% Web and mobile security · 24%
Human-computer interaction and pervasive computing
1 paper
Usability and user experience research · 100%

Topics — the 3 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Privacy and data protection › privacy of vulnerable populations
children's privacy
1.122022
Poster: An Analysis of Privacy Features in 'Expert-Approved' Kids' Apps · CCS 2022
"Money makes the world go around": Identifying Barriers to Better Privacy in Children's Apps From Developers' Perspectives · CHI 2021
Web and mobile security › mobile application security
mobile app analysis
0.612022
Poster: An Analysis of Privacy Features in 'Expert-Approved' Kids' Apps · CCS 2022
Privacy and data protection
mobile app privacy
0.612022
Poster: An Analysis of Privacy Features in 'Expert-Approved' Kids' Apps · CCS 2022

Methods — techniques the papers use, named apart from their topics

survey · 1.0semi-structured interviews · 1.0mixed-methods analysis · 0.6
YearPublicationVenuePosition
2023 How Can We Design Privacy-Friendly Apps for Children? Using a Research through Design Process to Understand Developers' Needs and Challenges
abstract
Mobile apps used by children often make use of harmful techniques, such as data tracking and targeted advertising. Previous research has suggested that developers face several systemic challenges in designing apps that prioritise children's best interests. To understand how developers can be better supported, we used a Research through Design (RtD) method to explore what the future of privacy-friendly app development could look like. We performed an elicitation study with 20 children's app developers to understand their needs and requirements. We found a number of specific technical requirements from the participants about how they would like to be supported, such as having actionable transnational design guidelines and easy-to-use development libraries. However, participants were reluctant to adopt these design ideas in their development practices due to perceived financial risks associated with increased privacy in apps. To overcome this critical gap, participants formulated socio-technical requirements that extend to other stakeholders in the mobile industry, including parents and marketplaces. Our findings provide important immediate and long-term design opportunities for the HCI community, and indicate that support for changing app developers' practices must be designed in the context of their relationship with other stakeholders.
Anirudh Ekambaranathan, Jun Zhao 0003, Max Van Kleek
Proc. ACM Hum. Comput. Interact.1
2022 Poster: An Analysis of Privacy Features in 'Expert-Approved' Kids' Apps
abstract
During the course of the past decade, children have become avid consumers of digital media through mobile devices. The industry for children's mobile applications is booming and marketplaces offer categories of apps aimed specifically at children. In this study, we perform a mixed-methods privacy analysis of 137 'expert-approved' children's apps from the Google Play Store. Our findings show that these apps do not sufficiently support children to exercise their privacy rights, whilst simultaneously making use of libraries and data trackers which may collect and share sensitive user data.
Anirudh Ekambaranathan, Jun Zhao 0003, Max Van Kleek
CCS1
2021 "Money makes the world go around": Identifying Barriers to Better Privacy in Children's Apps From Developers' Perspectives
abstract
The industry for children’s apps is thriving at the cost of children’s privacy: these apps routinely disclose children’s data to multiple data trackers and ad networks. As children spend increasing time online, such exposure accumulates to long-term privacy risks. In this paper, we used a mixed-methods approach to investigate why this is happening and how developers might change their practices. We base our analysis against 5 leading data protection frameworks that set out requirements and recommendations for data collection in children’s apps. To understand developers’ perspectives and constraints, we conducted 134 surveys and 20 semi-structured interviews with popular Android children’s app developers. Our analysis revealed that developers largely respect children’s best interests; however, they have to make compromises due to limited monetisation options, perceived harmlessness of certain third-party libraries, and lack of availability of design guidelines. We identified concrete approaches and directions for future research to help overcome these barriers.
Anirudh Ekambaranathan, Jun Zhao 0003, Max Van Kleek
CHI1