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ORCIDFlorian Kerschbaum
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- affiliation: University of Waterloo, ON, Canada
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2020 – today
- 2024
[j36]Shubhankar Mohapatra
, Jianqiao Zong, Florian Kerschbaum, Xi He:
Differentially Private Data Generation with Missing Data. Proc. VLDB Endow. 17(8): 2022-2035 (2024)- [c147]Nils Lukas, Abdulrahman Diaa, Lucas Fenaux, Florian Kerschbaum:
Leveraging Optimization for Adaptive Attacks on Image Watermarks. ICLR 2024 - [c146]Benjamin Schneider, Nils Lukas, Florian Kerschbaum:
Universal Backdoor Attacks. ICLR 2024 - [c145]Abdulrahman Diaa, Lucas Fenaux, Thomas Humphries, Marian Dietz, Faezeh Ebrahimianghazani, Bailey Kacsmar, Xinda Li, Nils Lukas, Rasoul Akhavan Mahdavi, Simon Oya, Ehsan Amjadian, Florian Kerschbaum:
Fast and Private Inference of Deep Neural Networks by Co-designing Activation Functions. USENIX Security Symposium 2024 - [c144]Rasoul Akhavan Mahdavi, Nils Lukas, Faezeh Ebrahimianghazani, Thomas Humphries, Bailey Kacsmar, John A. Premkumar, Xinda Li, Simon Oya, Ehsan Amjadian, Florian Kerschbaum:
PEPSI: Practically Efficient Private Set Intersection in the Unbalanced Setting. USENIX Security Symposium 2024 - [i61]Lucas Fenaux, Florian Kerschbaum:
SoK: Analyzing Adversarial Examples: A Framework to Study Adversary Knowledge. CoRR abs/2402.14937 (2024) - [i60]Abdulrahman Diaa, Thomas Humphries, Florian Kerschbaum:
FastLloyd: Federated, Accurate, Secure, and Tunable k-Means Clustering with Differential Privacy. CoRR abs/2405.02437 (2024) - [i59]Ronny Ko, Rasoul Akhavan Mahdavi, Byoungwoo Yoon, Makoto Onizuka, Florian Kerschbaum:
SilentWood: Private Inference Over Gradient-Boosting Decision Forests. CoRR abs/2411.15494 (2024) - 2023
- [j35]Clark W. Barrett, Brad Boyd, Elie Bursztein, Nicholas Carlini, Brad Chen, Jihye Choi, Amrita Roy Chowdhury, Mihai Christodorescu, Anupam Datta, Soheil Feizi, Kathleen Fisher, Tatsunori Hashimoto, Dan Hendrycks, Somesh Jha, Daniel Kang, Florian Kerschbaum, Eric Mitchell, John C. Mitchell, Zulfikar Ramzan, Khawaja Shams, Dawn Song, Ankur Taly, Diyi Yang:
Identifying and Mitigating the Security Risks of Generative AI. Found. Trends Priv. Secur. 6(1): 1-52 (2023) - [j34]Florian Kerschbaum, Nils Lukas:
Privacy-Preserving Machine Learning [Cryptography]. IEEE Secur. Priv. 21(6): 90-94 (2023) - [j33]Sujaya Maiyya, Sharath Chandra Vemula, Divyakant Agrawal, Amr El Abbadi, Florian Kerschbaum:
Waffle: An Online Oblivious Datastore for Protecting Data Access Patterns. Proc. ACM Manag. Data 1(4): 266:1-266:25 (2023) - [j32]Sina Faraji, Florian Kerschbaum:
Trifecta: Faster High-Throughput Three-Party Computation over WAN Using Multi-Fan-In Logic Gates. Proc. Priv. Enhancing Technol. 2023(4): 224-237 (2023) - [j31]Thomas Humphries, Florian Kerschbaum:
Differentially Private Simple Genetic Algorithms. Proc. Priv. Enhancing Technol. 2023(4): 540-558 (2023) - [j30]Ruidi Wei, Florian Kerschbaum:
Cryptographically Secure Private Record Linkage Using Locality-Sensitive Hashing. Proc. VLDB Endow. 17(2): 79-91 (2023) - [c143]Bailey Kacsmar, Vasisht Duddu, Kyle Tilbury, Blase Ur, Florian Kerschbaum:
Comprehension from Chaos: Towards Informed Consent for Private Computation. CCS 2023: 210-224 - [c142]Rasoul Akhavan Mahdavi, Haoyan Ni, Dimitry Linkov, Florian Kerschbaum:
Level Up: Private Non-Interactive Decision Tree Evaluation using Levelled Homomorphic Encryption. CCS 2023: 2945-2958 - [c141]Thomas Humphries, Simon Oya, Lindsey Tulloch, Matthew Rafuse, Ian Goldberg, Urs Hengartner, Florian Kerschbaum:
Investigating Membership Inference Attacks under Data Dependencies. CSF 2023: 473-488 - [c140]Lucas Fenaux, Thomas Humphries, Florian Kerschbaum:
Gaggle: Genetic Algorithms on the GPU using PyTorch. GECCO Companion 2023: 2358-2361 - [c139]Florian Kerschbaum, Erik-Oliver Blass, Rasoul Akhavan Mahdavi:
Faster Secure Comparisons with Offline Phase for Efficient Private Set Intersection. NDSS 2023 - [c138]Erik-Oliver Blass, Florian Kerschbaum:
Private Collaborative Data Cleaning via Non-Equi PSI. SP 2023: 1419-1434 - [c137]Erik-Oliver Blass, Florian Kerschbaum:
Private Collaborative Data Cleaning via Non-Equi PSI. SP 2023: 1419-1434 - [c136]Nils Lukas, Florian Kerschbaum:
PTW: Pivotal Tuning Watermarking for Pre-Trained Image Generators. USENIX Security Symposium 2023: 2241-2258 - [i58]Rasoul Akhavan Mahdavi, Abdulrahman Diaa, Florian Kerschbaum:
HE is all you need: Compressing FHE Ciphertexts using Additive HE. CoRR abs/2303.09043 (2023) - [i57]Nils Lukas, Florian Kerschbaum:
PTW: Pivotal Tuning Watermarking for Pre-Trained Image Generators. CoRR abs/2304.07361 (2023) - [i56]Nils Lukas, Florian Kerschbaum:
Pick your Poison: Undetectability versus Robustness in Data Poisoning Attacks against Deep Image Classification. CoRR abs/2305.09671 (2023) - [i55]Abdulrahman Diaa, Lucas Fenaux, Thomas Humphries, Marian Dietz, Faezeh Ebrahimianghazani, Bailey Kacsmar, Xinda Li, Nils Lukas, Rasoul Akhavan Mahdavi, Simon Oya, Ehsan Amjadian, Florian Kerschbaum:
Fast and Private Inference of Deep Neural Networks by Co-designing Activation Functions. CoRR abs/2306.08538 (2023) - [i54]Yutong Wu, Jie Zhang, Florian Kerschbaum, Tianwei Zhang:
Backdooring Textual Inversion for Concept Censorship. CoRR abs/2308.10718 (2023) - [i53]Clark W. Barrett, Brad Boyd, Ellie Burzstein, Nicholas Carlini, Brad Chen, Jihye Choi, Amrita Roy Chowdhury, Mihai Christodorescu, Anupam Datta, Soheil Feizi, Kathleen Fisher, Tatsunori Hashimoto, Dan Hendrycks, Somesh Jha, Daniel Kang, Florian Kerschbaum, Eric Mitchell, John C. Mitchell, Zulfikar Ramzan, Khawaja Shams, Dawn Song, Ankur Taly, Diyi Yang:
Identifying and Mitigating the Security Risks of Generative AI. CoRR abs/2308.14840 (2023) - [i52]Rasoul Akhavan Mahdavi, Haoyan Ni, Dimitry Linkov, Florian Kerschbaum:
Level Up: Private Non-Interactive Decision Tree Evaluation using Levelled Homomorphic Encryption. CoRR abs/2309.06496 (2023) - [i51]Nils Lukas, Abdulrahman Diaa, Lucas Fenaux, Florian Kerschbaum:
Leveraging Optimization for Adaptive Attacks on Image Watermarks. CoRR abs/2309.16952 (2023) - [i50]Shubhankar Mohapatra, Jianqiao Zong, Florian Kerschbaum, Xi He:
Differentially Private Data Generation with Missing Data. CoRR abs/2310.11548 (2023) - [i49]Rasoul Akhavan Mahdavi, Nils Lukas, Faezeh Ebrahimianghazani, Thomas Humphries, Bailey Kacsmar, John A. Premkumar, Xinda Li, Simon Oya, Ehsan Amjadian, Florian Kerschbaum:
PEPSI: Practically Efficient Private Set Intersection in the Unbalanced Setting. CoRR abs/2310.14565 (2023) - [i48]Benjamin Schneider, Nils Lukas, Florian Kerschbaum:
Universal Backdoor Attacks. CoRR abs/2312.00157 (2023) - [i47]Sujaya Maiyya, Sharath Chandra Vemula, Divyakant Agrawal, Amr El Abbadi, Florian Kerschbaum:
Waffle: An Online Oblivious Datastore for Protecting Data Access Patterns. IACR Cryptol. ePrint Arch. 2023: 1285 (2023) - 2022
- [j29]Florian Kerschbaum, Michelle L. Mazurek:
Editors' Introduction. Proc. Priv. Enhancing Technol. 2022(1): 1-5 (2022) - [j28]Florian Kerschbaum, Michelle L. Mazurek:
Editors' Introduction. Proc. Priv. Enhancing Technol. 2022(2): 1-5 (2022) - [j27]Florian Kerschbaum, Michelle L. Mazurek:
Editors' Introduction. Proc. Priv. Enhancing Technol. 2022(3): 1-5 (2022) - [j26]Florian Kerschbaum, Michelle L. Mazurek:
Editors' Introduction. Proc. Priv. Enhancing Technol. 2022(4): 1-5 (2022) - [j25]Andreas Fischer, Benny Fuhry, Jörn Kußmaul, Jonas Janneck, Florian Kerschbaum, Eric Bodden:
Computation on Encrypted Data Using Dataflow Authentication. ACM Trans. Priv. Secur. 25(3): 21:1-21:36 (2022) - [c135]Erik-Oliver Blass, Florian Kerschbaum, Travis Mayberry:
Iterative Oblivious Pseudo-Random Functions and Applications. AsiaCCS 2022: 28-41 - [c134]Thomas Humphries, Rasoul Akhavan Mahdavi, Shannon Veitch, Florian Kerschbaum:
Selective MPC: Distributed Computation of Differentially Private Key-Value Statistics. CCS 2022: 1459-1472 - [c133]Daniel Bernau, Jonas Robl, Florian Kerschbaum:
Assessing Differentially Private Variational Autoencoders Under Membership Inference. DBSec 2022: 3-14 - [c132]Erik-Oliver Blass, Florian Kerschbaum:
Mixed-Technique Multi-Party Computations Composed of Two-Party Computations. ESORICS (3) 2022: 295-319 - [c131]Masoumeh Shafieinejad, Suraj Gupta, Jin Yang Liu, Koray Karabina, Florian Kerschbaum:
Equi-Joins over Encrypted Data for Series of Queries. ICDE 2022: 1635-1648 - [c130]Justus Mattern, Benjamin Weggenmann, Florian Kerschbaum:
The Limits of Word Level Differential Privacy. NAACL-HLT (Findings) 2022: 867-881 - [c129]Nils Lukas, Edward Jiang, Xinda Li, Florian Kerschbaum:
SoK: How Robust is Image Classification Deep Neural Network Watermarking? SP 2022: 787-804 - [c128]Bailey Kacsmar, Kyle Tilbury, Miti Mazmudar, Florian Kerschbaum:
Caring about Sharing: User Perceptions of Multiparty Data Sharing. USENIX Security Symposium 2022: 899-916 - [c127]Rasoul Akhavan Mahdavi, Florian Kerschbaum:
Constant-weight PIR: Single-round Keyword PIR via Constant-weight Equality Operators. USENIX Security Symposium 2022: 1723-1740 - [c126]Simon Oya, Florian Kerschbaum:
IHOP: Improved Statistical Query Recovery against Searchable Symmetric Encryption through Quadratic Optimization. USENIX Security Symposium 2022: 2407-2424 - [c125]Benjamin Weggenmann, Valentin Rublack, Michael Andrejczuk, Justus Mattern, Florian Kerschbaum:
DP-VAE: Human-Readable Text Anonymization for Online Reviews with Differentially Private Variational Autoencoders. WWW 2022: 721-731 - [i46]Rasoul Akhavan Mahdavi, Florian Kerschbaum:
Constant-weight PIR: Single-round Keyword PIR via Constant-weight Equality Operators. CoRR abs/2202.07569 (2022) - [i45]Daniel Bernau, Jonas Robl, Florian Kerschbaum:
Assessing Differentially Private Variational Autoencoders under Membership Inference. CoRR abs/2204.07877 (2022) - [i44]Justus Mattern, Benjamin Weggenmann, Florian Kerschbaum:
The Limits of Word Level Differential Privacy. CoRR abs/2205.02130 (2022) - [i43]Florian Kerschbaum, Erik-Oliver Blass, Rasoul Akhavan Mahdavi:
Faster Secure Comparisons with Offline Phase for Efficient Private Set Intersection. CoRR abs/2209.13913 (2022) - [i42]Bailey Kacsmar, Vasisht Duddu, Kyle Tilbury, Blase Ur, Florian Kerschbaum:
Comprehension from Chaos: What Users Understand and Expect from Private Computation. CoRR abs/2211.07026 (2022) - [i41]Yihan Wu, Xinda Li, Florian Kerschbaum, Heng Huang, Hongyang Zhang:
Towards Robust Dataset Learning. CoRR abs/2211.10752 (2022) - [i40]Erik-Oliver Blass, Florian Kerschbaum:
Private Collaborative Data Cleaning via Non-Equi PSI. IACR Cryptol. ePrint Arch. 2022: 1465 (2022) - 2021
- [j24]Aaron Johnson, Florian Kerschbaum:
Editors' Introduction. Proc. Priv. Enhancing Technol. 2021(1): 1-4 (2021) - [j23]Aaron Johnson, Florian Kerschbaum:
Editors' Introduction. Proc. Priv. Enhancing Technol. 2021(2): 1-4 (2021) - [j22]Aaron Johnson, Florian Kerschbaum:
Editors' Introduction. Proc. Priv. Enhancing Technol. 2021(3): 1-4 (2021) - [j21]Aaron Johnson, Florian Kerschbaum:
Editors' Introduction. Proc. Priv. Enhancing Technol. 2021(4): 1-5 (2021) - [j20]Daniel Bernau, Günther Eibl, Philip-William Grassal, Hannah Keller, Florian Kerschbaum:
Quantifying identifiability to choose and audit epsilon in differentially private deep learning. Proc. VLDB Endow. 14(13): 3335-3347 (2021) - [c124]Maryam Sepehri, Florian Kerschbaum:
Low-Cost Hiding of the Query Pattern. AsiaCCS 2021: 593-603 - [c123]Benjamin Weggenmann, Florian Kerschbaum:
Differential Privacy for Directional Data. CCS 2021: 1205-1222 - [c122]Jonas Böhler, Florian Kerschbaum:
Secure Multi-party Computation of Differentially Private Heavy Hitters. CCS 2021: 2361-2377 - [c121]Daniel Bernau, Jonas Robl, Philip-William Grassal, Steffen Schneider, Florian Kerschbaum:
Comparing Local and Central Differential Privacy Using Membership Inference Attacks. DBSec 2021: 22-42 - [c120]Benny Fuhry, Jayanth Jain H. A, Florian Kerschbaum:
EncDBDB: Searchable Encrypted, Fast, Compressed, In-Memory Database Using Enclaves. DSN 2021: 438-450 - [c119]Chan Nam Ngo, Fabio Massacci, Florian Kerschbaum, Julian Williams:
Practical Witness-Key-Agreement for Blockchain-Based Dark Pools Financial Trading. Financial Cryptography (2) 2021: 579-598 - [c118]Nils Lukas, Yuxuan Zhang, Florian Kerschbaum:
Deep Neural Network Fingerprinting by Conferrable Adversarial Examples. ICLR 2021 - [c117]Masoumeh Shafieinejad, Nils Lukas, Jiaqi Wang, Xinda Li, Florian Kerschbaum:
On the Robustness of Backdoor-based Watermarking in Deep Neural Networks. IH&MMSec 2021: 177-188 - [c116]Zhiwei Shang, Simon Oya, Andreas Peter, Florian Kerschbaum:
Obfuscated Access and Search Patterns in Searchable Encryption. NDSS 2021 - [c115]Masoumeh Shafieinejad, Florian Kerschbaum, Ihab F. Ilyas:
PCOR: Private Contextual Outlier Release via Differentially Private Search. SIGMOD Conference 2021: 1571-1583 - [c114]Florian Kerschbaum:
Towards Privacy in Deep Learning. TPS-ISA 2021: 279-280 - [c113]Simon Oya, Florian Kerschbaum:
Hiding the Access Pattern is Not Enough: Exploiting Search Pattern Leakage in Searchable Encryption. USENIX Security Symposium 2021: 127-142 - [c112]Tianhao Wang, Florian Kerschbaum:
RIGA: Covert and Robust White-Box Watermarking of Deep Neural Networks. WWW 2021: 993-1004 - [i39]Zhiwei Shang, Simon Oya, Andreas Peter, Florian Kerschbaum:
Obfuscated Access and Search Patterns in Searchable Encryption. CoRR abs/2102.09651 (2021) - [i38]Daniel Bernau, Günther Eibl, Philip-William Grassal, Hannah Keller, Florian Kerschbaum:
Quantifying identifiability to choose and audit ε in differentially private deep learning. CoRR abs/2103.02913 (2021) - [i37]Masoumeh Shafieinejad, Florian Kerschbaum, Ihab F. Ilyas:
PCOR: Private Contextual Outlier Release via Differentially Private Search. CoRR abs/2103.05173 (2021) - [i36]Masoumeh Shafieinejad, Suraj Gupta, Jin Yang Liu, Koray Karabina, Florian Kerschbaum:
Equi-Joins Over Encrypted Data for Series of Queries. CoRR abs/2103.05792 (2021) - [i35]Thomas Humphries, Rasoul Akhavan Mahdavi, Shannon Veitch, Florian Kerschbaum:
Selective MPC: Distributed Computation of Differentially Private Key Value Statistics. CoRR abs/2107.12407 (2021) - [i34]Nils Lukas, Edward Jiang, Xinda Li, Florian Kerschbaum:
SoK: How Robust is Image Classification Deep Neural Network Watermarking? (Extended Version). CoRR abs/2108.04974 (2021) - [i33]Simon Oya, Florian Kerschbaum:
IHOP: Improved Statistical Query Recovery against Searchable Symmetric Encryption through Quadratic Optimization. CoRR abs/2110.04180 (2021) - [i32]Jiaxiang Liu, Simon Oya, Florian Kerschbaum:
Generalization Techniques Empirically Outperform Differential Privacy against Membership Inference. CoRR abs/2110.05524 (2021) - [i31]Erik-Oliver Blass, Florian Kerschbaum, Travis Mayberry:
Iterative Oblivious Pseudo-Random Functions and Applications. IACR Cryptol. ePrint Arch. 2021: 1013 (2021) - 2020
- [j19]Andreas Fischer, Benny Fuhry, Florian Kerschbaum, Eric Bodden:
Computation on Encrypted Data using Dataflow Authentication. Proc. Priv. Enhancing Technol. 2020(1): 5-25 (2020) - [j18]Bailey Kacsmar, Chelsea Komlo, Florian Kerschbaum, Ian Goldberg:
Mind the Gap: Ceremonies for Applied Secret Sharing. Proc. Priv. Enhancing Technol. 2020(2): 397-415 (2020) - [j17]Simeon Krastnikov, Florian Kerschbaum, Douglas Stebila:
Efficient Oblivious Database Joins. Proc. VLDB Endow. 13(11): 2132-2145 (2020) - [c111]Rasoul Akhavan Mahdavi, Thomas Humphries, Bailey Kacsmar, Simeon Krastnikov, Nils Lukas, John A. Premkumar, Masoumeh Shafieinejad, Simon Oya, Florian Kerschbaum, Erik-Oliver Blass:
Practical Over-Threshold Multi-Party Private Set Intersection. ACSAC 2020: 772-783 - [c110]Anselme Tueno, Florian Kerschbaum:
Efficient Secure Computation of Order-Preserving Encryption. AsiaCCS 2020: 193-207 - [c109]Erik-Oliver Blass, Florian Kerschbaum:
BOREALIS: Building Block for Sealed Bid Auctions on Blockchains. AsiaCCS 2020: 558-571 - [c108]Andreas Fischer, Jonas Janneck, Jörn Kussmaul, Nikolas Krätzschmar, Florian Kerschbaum, Eric Bodden:
PASAPTO: Policy-aware Security and Performance Trade-off Analysis-Computation on Encrypted Data with Restricted Leakage. CSF 2020: 230-245 - [c107]Anselme Tueno, Yordan Boev, Florian Kerschbaum:
Non-interactive Private Decision Tree Evaluation. DBSec 2020: 174-194 - [c106]Benny Fuhry, Lina Hirschoff, Samuel Koesnadi, Florian Kerschbaum:
SeGShare: Secure Group File Sharing in the Cloud using Enclaves. DSN 2020: 476-488 - [c105]Bailey Kacsmar, Basit Khurram, Nils Lukas, Alexander Norton, Masoumeh Shafieinejad, Zhiwei Shang, Yaser Baseri, Maryam Sepehri, Simon Oya, Florian Kerschbaum:
Differentially Private Two-Party Set Operations. EuroS&P 2020: 390-404 - [c104]Anselme Tueno, Florian Kerschbaum, Stefan Katzenbeisser, Yordan Boev, Mubashir Qureshi:
Secure Computation of the kth-Ranked Element in a Star Network. Financial Cryptography 2020: 386-403 - [c103]Basit Khurram, Florian Kerschbaum:
SFour: A Protocol for Cryptographically Secure Record Linkage at Scale. ICDE 2020: 277-288 - [c102]Jonas Böhler, Florian Kerschbaum:
Secure Sublinear Time Differentially Private Median Computation. NDSS 2020 - [c101]Timon Hackenjos, Florian Hahn, Florian Kerschbaum:
SAGMA: Secure Aggregation Grouped by Multiple Attributes. SIGMOD Conference 2020: 587-601 - [c100]Jonas Böhler, Florian Kerschbaum:
Secure Multi-party Computation of Differentially Private Median. USENIX Security Symposium 2020: 2147-2164 - [i30]Benny Fuhry, Jayanth Jain H. A, Florian Kerschbaum:
EncDBDB: Searchable Encrypted, Fast, Compressed, In-Memory Database using Enclaves. CoRR abs/2002.05097 (2020) - [i29]Simeon Krastnikov, Florian Kerschbaum, Douglas Stebila:
Efficient Oblivious Database Joins. CoRR abs/2003.09481 (2020) - [i28]Simon Oya, Florian Kerschbaum:
Hiding the Access Pattern is Not Enough: Exploiting Search Pattern Leakage in Searchable Encryption. CoRR abs/2010.03465 (2020) - [i27]Thomas Humphries, Matthew Rafuse, Lindsey Tulloch, Simon Oya, Ian Goldberg, Florian Kerschbaum:
Differentially Private Learning Does Not Bound Membership Inference. CoRR abs/2010.12112 (2020) - [i26]Erik-Oliver Blass, Florian Kerschbaum:
Mixed-Technique, Maliciously-Secure, and Composed Multi-Party Computations. IACR Cryptol. ePrint Arch. 2020: 636 (2020)
2010 – 2019
- 2019
- [j16]Anselme Tueno, Florian Kerschbaum, Stefan Katzenbeisser:
Private Evaluation of Decision Trees using Sublinear Cost. Proc. Priv. Enhancing Technol. 2019(1): 266-286 (2019) - [j15]Chang Ge, Ihab F. Ilyas, Florian Kerschbaum:
Secure Multi-Party Functional Dependency Discovery. Proc. VLDB Endow. 13(2): 184-196 (2019) - [c99]Florian Kerschbaum, Anselme Tueno:
An Efficiently Searchable Encrypted Data Structure for Range Queries. ESORICS (2) 2019: 344-364 - [c98]Tianhao Wang, Florian Kerschbaum:
Attacks on Digital Watermarks for Deep Neural Networks. ICASSP 2019: 2622-2626 - [c97]Florian Hahn, Nicolas Loza, Florian Kerschbaum:
Joins Over Encrypted Data with Fine Granular Security. ICDE 2019: 674-685 - [e6]Florian Kerschbaum, Atefeh Mashatan, Jianwei Niu, Adam J. Lee:
Proceedings of the 24th ACM Symposium on Access Control Models and Technologies, SACMAT 2019, Toronto, ON, Canada, June 03-06, 2019. ACM 2019, ISBN 978-1-4503-6753-0 [contents] - [i25]Masoumeh Shafieinejad, Jiaqi Wang, Nils Lukas, Florian Kerschbaum:
On the Robustness of the Backdoor-based Watermarking in Deep Neural Networks. CoRR abs/1906.07745 (2019) - [i24]Anselme Tueno, Florian Kerschbaum, Stefan Katzenbeisser, Yordan Boev, Mubashir Qureshi:
Secure Computation of the kth-Ranked Element in a Star Network. CoRR abs/1909.08347 (2019) - [i23]Anselme Tueno, Yordan Boev, Florian Kerschbaum:
Non-Interactive Private Decision Tree Evaluation. CoRR abs/1909.08362 (2019) - [i22]Tianhao Wang, Florian Kerschbaum:
Robust and Undetectable White-Box Watermarks for Deep Neural Networks. CoRR abs/1910.14268 (2019) - [i21]Nils Lukas, Yuxuan Zhang, Florian Kerschbaum:
Deep Neural Network Fingerprinting by Conferrable Adversarial Examples. CoRR abs/1912.00888 (2019) - [i20]Daniel Bernau, Philip-William Grassal, Jonas Robl, Florian Kerschbaum:
Assessing differentially private deep learning with Membership Inference. CoRR abs/1912.11328 (2019) - [i19]Erik-Oliver Blass, Florian Kerschbaum:
Secure Computation of the kth-ranked Integer on Blockchains. IACR Cryptol. ePrint Arch. 2019: 276 (2019) - 2018
- [j14]Benny Fuhry, Raad Bahmani, Ferdinand Brasser, Florian Hahn, Florian Kerschbaum, Ahmad-Reza Sadeghi:
HardIDX: Practical and secure index with SGX in a malicious environment. J. Comput. Secur. 26(5): 677-706 (2018) - [j13]