Security and privacy for big data: A systematic literature review. - Boel Nelson; Tomas Olovsson (IEEE BigData, 2016)

Joint Subjective and Objective Data Capture and Analytics for Automotive Applications. - Mathias Johanson; Jonas Jalminger; Emmanuel Frécon; Boel Nelson; Tomas Olovsson; Mats Gjertz (VTC Fall, 2017)

Introducing Differential Privacy to the Automotive Domain: Opportunities and Challenges. - Boel Nelson; Tomas Olovsson (VTC Fall, 2017)

Chasing Accuracy and Privacy, and Catching Both: A Literature Survey on Differentially Private Histogram Publication. - Boel Nelson; Jenni Reuben (CoRR, 2019)

SoK: Chasing Accuracy and Privacy, and Catching Both in Differentially Private Histogram Publication. - Boel Nelson; Jenni Reuben (Trans. Data Priv., 2020)

Efficient Error Prediction for Differentially Private Algorithms. - Boel Nelson (ARES, 2021)

Randori: Local Differential Privacy for All. - Boel Nelson (CoRR, 2021)

Efficient Accuracy Prediction for Differentially Private Algorithms. - Boel Nelson (CoRR, 2021)

With a Little Help from My Friends: Transport Deniability for Instant Messaging. - Boel Nelson; Aslan Askarov (CoRR, 2022)

To Signal or Not to Signal? Layering Traffic Analysis Resistance on Secure Instant Messaging. - Boel Nelson; Elena Pagnin; Aslan Askarov (CoRR, 2022)

Differentially Private Selection from Secure Distributed Computing. - Ivan Damgård; Hannah Keller; Boel Nelson; Claudio Orlandi; Rasmus Pagh (IACR Cryptol. ePrint Arch., 2023)

Metadata Privacy Beyond Tunneling for Instant Messaging. - Boel Nelson; Elena Pagnin; Aslan Askarov (EuroS&P, 2024)

PLAN: Variance-Aware Private Mean Estimation. - Martin Aumüller 001; Christian Janos Lebeda; Boel Nelson; Rasmus Pagh (Proc. Priv. Enhancing Technol., 2024)

Private Lossless Multiple Release. - Joel Daniel Andersson; Lukas Retschmeier; Boel Nelson; Rasmus Pagh (CoRR, 2025)

User Perceptions and Attitudes Toward Untraceability in Messaging Platforms. - Carla F. Griggio; Boel Nelson; Zefan Sramek; Aslan Askarov (CoRR, 2025)