The DOI matches its Crossref record; 15 of the 15 references it cites were found in a registry or an index.
Information Leakage in Wearable Applications
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“For instance, the largest set of apps, 2133 wearable apps, was evaluated by Olabenjo and Makaroff [67].”
From Security and Privacy of mHealth Applications: A Scoping Review (2020) · cites this paper as [67]
In the citing paper
“15.9% (7/44) of studies were undertaken to evaluate the data practices of mHealth applications, for instance, classi cation and analysis of information leakage in wearable smartwatch apps [67] or assessment of prominent transport security issues [57].”
From Security and Privacy of mHealth Applications: A Scoping Review (2020) · cites this paper as [67]
Citations
Cites
Security and privacy in smart city applications: Challenges and solutions
Zhang, K., Ni, J., Yang, K., Liang, X., Ren, J., & Shen, X. S. (2017) · IEEE Communications Magazine · doi:10.1109/mcom.2017.1600267cm · Cited by 638
Security and Privacy in the Medical Internet of Things: A Review
Sun, W., Cai, Z., Li, Y., Liu, F., Fang, S., & Wang, G. (2018) · Security and Communication Networks · doi:10.1155/2018/5978636 · Cited by 289
Hou, S., Ye, Y., Song, Y., & Abdulhayoglu, M. (2017) · Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining · doi:10.1145/3097983.3098026 · Cited by 244
Privacy Implications of Wearable Health Devices
Paul, G., & Irvine, J. M. (2014) · International Conference on Security of Information and Networks (SIN) · doi:10.1145/2659651.2659683 · Cited by 74
Understanding the Characteristics of Android Wear OS
Liu, R., & Lin, F. X. (2016) · International Conference on Mobile Systems, Applications, and Services · doi:10.1145/2906388.2906398 · Cited by 41
Security threat on wearable services: Empirical study using a commercial smartband
Lee, M., Lee, K., Shim, J., Cho, S.-J., & Choi, J. (2016) · IEEE International Conference on Consumer Electronics-Asia (ICCE-Asia) · doi:10.1109/icce-asia.2016.7804766 · Cited by 31
Characterization of early smartwatch apps
Chauhan, J., Seneviratne, S., Kâafar, M. A., Mahanti, A., & Seneviratne, A. P. (2016) · IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops) · doi:10.1109/percomw.2016.7457170 · Cited by 28
Privacy Leakage of Physical Activity Levels in Wireless Embedded Wearable Systems
Fafoutis, X., Marchegiani, L., Papadopoulos, G. Z., Piechocki, R. J., Tryfonas, T., & Oikonomou, G. (2016) · IEEE Signal Processing Letters · doi:10.1109/lsp.2016.2642300 · Cited by 27
Analysis and Testing of Notifications in Android Wear Applications
Zhang, H., & Rountev, A. (2017) · IEEE/ACM International Conference on Software Engineering (ICSE) · doi:10.1109/icse.2017.39 · Cited by 24
Revisiting Mobile Advertising Threats with MAdLife
Gong, C., Meng, W., & Copeland, J. A. (2019) · International World Wide Web Conference (WWW) · doi:10.1145/3308558.3313549 · Cited by 24
Cited by
Security and Privacy of mHealth Applications: A Scoping Review
Nurgalieva, L., O'Callaghan, D., & Doherty, G. (2020) · IEEE Access · doi:10.1109/access.2020.2999934 · Cited by 132
“For instance, the largest set of apps, 2133 wearable apps, was evaluated by Olabenjo and Makaroff [67].”
BackgroundInfluential
Metadata
- Authors
- Olabenjo, B., & Makaroff, D.
- Affiliations
- University of Saskatchewan (CA)
- Corresponding author
- Olabenjo, Babatunde
- ORCID
- Makaroff, Dwight
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer International Publishing
- Published
- 2019
- Pages
- 211-224
- ISSN
- 0302-9743 (ISSN-L)
- 1611-3349
- OpenAlex
- W2958472176
- Cited by
- 3
- References
- 15
- Citations by year
- 2025: 1 · 2023: 1 · 2020: 1
- FWCI
- 0.71
- Type
- conference paper
- Language
- en
- Open access
- closed
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Lecture notes in computer science (publishedVersion)
- Topics
- Social Sciences › Sociology and Political Science › Privacy, Security, and Data Protection
- Physical Sciences › Computer Science › Software › Advanced Malware Detection Techniques
- Physical Sciences › Computer Science › Artificial Intelligence › Privacy-Preserving Technologies in Data
- Keywords
- information leakage, mobile app privacy, personal data exposure, companion app, static and dynamic analysis
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Information Leakage in Wearable Applications. https://app.cochat.ai/papers/10.1007/978-3-030-24907-6_17
- The paper
- Olabenjo, B., & Makaroff, D. (2019). Information Leakage in Wearable Applications. Lecture Notes in Computer Science. https://doi.org/10.1007/978-3-030-24907-6_17
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
