Nils Gruschka

• Bisztray, Tamas; Gruschka, Nils; Mavroeidis, Vasileios & Fritsch, Lothar (2020). Data Protection Impact Assessment in Identity Control Management with a Focus on Biometrics, In Heiko Roßnagel; Christian H. Schunck; Sebastian Mödersheim & Detlef Hühnlein (ed.),  Open Identity Summit 2020.  Gesellschaft für Informatik e.V..  ISBN 978-3-88579-699-2.  Paper.  s 185 - 192
• Bisztray, Tamas & Gruschka, Nils (2019). Privacy impact assessment: Comparing methodologies with a focus on practicality. Lecture Notes in Computer Science (LNCS).  ISSN 0302-9743.  11875 LNCS, s 3- 19 . doi: 10.1007/978-3-030-35055-0_1
• Gruschka, Nils & Bisztray, Tamas (2019). Privacy Impact Assessment: Comparing Methodologies with a Focus on Practicality, In Aslan Askarov; René Rydhof Hansen & Willard Rafnsson (ed.),  Secure IT Systems - 24th Nordic Conference, NordSec 2019.  Springer Nature.  ISBN 978-3-030-35054-3.  1.  s 3 - 19
• Wiefling, Stephan; Gruschka, Nils & Lo Iacono, Luigi (2019). Even Turing Should Sometimes Not Be Able to Tell: Mimicking Humanoid Usage Behavior for Exploratory Studies of Online Service, In Aslan Askarov; René Rydhof Hansen & Willard Rafnsson (ed.),  Secure IT Systems - 24th Nordic Conference, NordSec 2019.  Springer Nature.  ISBN 978-3-030-35054-3.  12.  s 188 - 203
• Gruschka, Nils; Iacono, Luigi Lo & Tolsdorf, Jan (2018). Classification of android app permissions: Tell me what app you are and i tell you what you are allowed to do. Proceedings of the ... European conference on information warfare and security.  ISSN 2048-8602.  2018-June, s 181- 189
• Gruschka, Nils; Mavroeidis, Vasileios; Vishi, Kamer & Jensen, Meiko (2018). Privacy Issues and Data Protection in Big Data: A Case Study Analysis under GDPR, In Naoki Abe; Huan Liu; Xiaohua Hu; Nesreen Ahmed; Mu Qiao; Yang Song; Donald Kossmann; Bing Liu; Kisung Lee; Jiliang Tang; Jingrui He & Jeffrey Saltz (ed.),  2018 IEEE International Conference on Big Data (Big Data), Seattle, 10-13 Dec. 2018.  IEEE.  ISBN 978-1-5386-5035-6.  1.  s 5027 - 5033 Vis sammendrag

  Big data has become a great asset for many organizations, promising improved operations and new business opportunities. However, big data has increased access to sensitive information that when processed can directly jeopardize the privacy of individuals and violate data protection laws. As a consequence, data controllers and data processors may be imposed tough penalties for non-compliance that can result even to bankruptcy. In this paper, we discuss the current state of the legal regulations and analyse different data protection and privacy-preserving techniques in the context of big data analysis. In addition, we present and analyse two real-life research projects as case studies dealing with sensitive data and actions for complying with the data regulation laws. We show which types of information might become a privacy risk, the employed privacy-preserving techniques in accordance with the legal requirements, and the influence of these techniques on the data processing phase and the research results.

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• Gruschka, Nils (ed.) (2018). Secure IT Systems - 23rd Nordic Conference, NordSec 2018, Oslo, Norway, November 28-30, 2018, Proceedings. Springer Nature.  ISBN 978-3-030-03637-9.  486 s.

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