Mgrre_Thinsections_05_A_75,
2022
Western Michigan University
Quantum Key-Length Extension,
2022
Georgia Institute of Technology
Quantum Key-Length Extension, Joseph Jaeger, Fang Song, Stefano Tessaro
Computer Science Faculty Publications and Presentations
Should quantum computers become available, they will reduce the effective key length of basic secret-key primitives, such as blockciphers. To address this we will either need to use blockciphers with inherently longer keys or develop key-length extension techniques to amplify the security of a blockcipher to use longer keys.
We consider the latter approach and revisit the FX and double encryption constructions. Classically, FX was proven to be a secure key-length extension technique, while double encryption fails to be more secure than single encryption due to a meet-in-the-middle attack. In this work we provide positive results, with concrete and tight ...
Mgrre_Thinsections_05_A_71,
2022
Western Michigan University
Mgrre_Thinsections_05_A_70,
2022
Western Michigan University
Approved Final Butte Priority Soils Operable Unit (Bpsou) Unreclaimed Sites Field Sampling Plan (Fsp) Package #7: Ur-01, Ur-12, Ur-03, Ur-04, Ur-15, And Ur-17,
2022
Atlantic Richfield Company
Approved Final Butte Priority Soils Operable Unit (Bpsou) Unreclaimed Sites Field Sampling Plan (Fsp) Package #7: Ur-01, Ur-12, Ur-03, Ur-04, Ur-15, And Ur-17, Mike Mcanulty
Silver Bow Creek/Butte Area Superfund Site
No abstract provided.
Mgrre_Thinsections_05_A_69,
2022
Western Michigan University
Mgrre_Thinsections_05_A_68,
2022
Western Michigan University
Validation Of A Method For Pantoprazole And Its Sulfone Metabolite In Goat Plasma Using High Performance Liquid Chromatography, Sherry Cox, Lainey Harvill, Sarah Bullock, Joseph Smith, Joan Bergman
Faculty Publications and Other Works -- Large Animal Clinical Sciences
No abstract provided.
Which Neural Network Makes More Explainable Decisions? An Approach Towards Measuring Explainability,
2022
Singapore Management University
Which Neural Network Makes More Explainable Decisions? An Approach Towards Measuring Explainability, Mengdi Zhang, Jun Sun, Jingyi Wang
Research Collection School Of Computing and Information Systems
Neural networks are getting increasingly popular thanks to their exceptional performance in solving many real-world problems. At the same time, they are shown to be vulnerable to attacks, difficult to debug and subject to fairness issues. To improve people’s trust in the technology, it is often necessary to provide some human-understandable explanation of neural networks’ decisions, e.g., why is that my loan application is rejected whereas hers is approved? That is, the stakeholder would be interested to minimize the chances of not being able to explain the decision consistently and would like to know how often and how ...
Mgrre_Thinsections_05_A_67,
2022
Western Michigan University
Mgrre_Thinsections_05_A_66,
2022
Western Michigan University
Mgrre_Thinsections_05_A_65,
2022
Western Michigan University
Mgrre_Thinsections_05_A_64,
2022
Western Michigan University
Mgrre_Thinsections_05_A_63,
2022
Western Michigan University
Mgrre_Thinsections_05_A_62,
2022
Western Michigan University
Mgrre_Thinsections_05_A_61,
2022
Western Michigan University
Mgrre_Thinsections_05_A_60,
2022
Western Michigan University
Mgrre_Thinsections_05_A_59,
2022
Western Michigan University
Mgrre_Thinsections_05_A_58,
2022
Western Michigan University
Mgrre_Thinsections_05_A_57,
2022
Western Michigan University