Munich Workshop on Coding and Cryptography 2024
Contributed Posters
- Houman Asgari (TUM): Age of Information for Frame Asynchrounous Slotted ALOHA
- Anna Baumeister (TUM): Erasure Decoding of LRPC codes via Row Support
- Sebastian Bitzer (TUM): The Restricted Syndrome Decoding Problem
- Marvin Geiselhart (University of Stuttgart): Row-Merged Polar Codes: Analysis and Design
- Christoph Hofmeister (TUM): Achieving DNA Labeling Capacity with Minimum Labels through Extremal de Bruijn Subgraphs
- Alex Jäger (TUM): Successive Interference Cancellation for Optical Fiber Using Discrete Constellations
- Tayyebeh Jahani-Nezhad (TU Berlin): ByzSecAgg: A Byzantine-Resistant Secure Aggregation Scheme for Federated Learning Based on Coded Computing and Vector Commitment
- Diego Lentner (TUM): Low Latency Coding for Datacenter Interconnects
- Hedongliang Liu (TUM): Support-Constrained Codes for Multi-Source Network Coding
- Georg Maringer (TUM): Ciphertext size bounds for sharing a key using Kyber
- Luis Maßny (TUM): Attacks and Defenses for Over-the-Air SGD
- Vivian Papadopoulou (TUM): Sequence Reconstruction over Exact-t Adversarial Channel Repetitions: An Average Case Analysis
- Daniel Plabst (TUM): Neural network equalization for bandlimited nonlinear channels
- Anmoal Porwal (TUM): Code-Based Cryptography based on Supercode Decoding
- Stefan Ritterhoff (TUM): FuLeeca and FuLeakage
- Constantin Runge (TUM): Improved list-decoding for polar coded shaping
- Vladimir Sidorenko (TUM) joint work with Victor Zyablov and Vladimir Potapov: A network with data protection from both channel errors and unauthorized access using one code
- Andreas Straßhofer (TUM): Dispersion of the Rayleigh Fading Channel with CSIR and CSIT
- Thomas Wiegart (TUM): Probabilistic Shaping for Asymmetric Channels and LDPC Codes
- Saar Tarnopolsky (Technion): Coding-Based Hybrid Post-Quantum Cryptosystem for Non-Uniform Information
- Marvin Xhemrishi (TUM): FedGT: Identification of Malicious Clients in Federated Learning with Secure Aggregation
- Yue Xia (TUM): Byzantine-resilient and Information-Theoretically Private Federated Learning
- Lorenzo Zaniboni (TUM): Beam Alignment with an Intelligent Reflecting Surface for Integrated Sensing and Communciation