A team from the Cryptography Research Center (CRC) secured 6th place out of 210 teams in the 'Donjon CTF 2021: Capture the Fortress' cybersecurity competition. The competition featured jeopardy-style challenges covering cryptography, reverse engineering, and hardware security. The CRC team participated to improve visibility and assess team capabilities, particularly in hardware security. Why it matters: The CRC team's strong performance highlights the growing cybersecurity expertise in the UAE and its attractiveness for talent in this field.
A cryptanalysis team at the UAE's Cryptography Research Center (CRC) has set new records in computation by decrypting a McEliece ciphertext without the secret key at INRIA’s McEliece decoding challenge, taking first and second place. The record computation took about 31.4 days on a cluster using 256 CPU-cores. The team also achieved top ranks in decoding quasi-cyclic codes and ternary codes, used in post-quantum cryptography. Why it matters: This achievement demonstrates the UAE's growing capabilities in advanced cryptography research and its contributions to the global effort to develop quantum-resistant algorithms.
Professor Mike Scott will present a seminar at the Technology Innovation Institute's Cryptography Research Centre in the UAE. The seminar will focus on the challenges of keeping secrets safe from attackers in the context of cryptography. It will review proposed solutions, discuss use cases, and present a promising new approach. Why it matters: This seminar indicates TII's ongoing research and development efforts in advanced cryptography, a crucial area for secure digital infrastructure in the UAE and beyond.
The National Institute of Standards and Technology (NIST) has been evaluating Post-Quantum Cryptography proposals since 2017. Lattice-based schemes have emerged as efficient candidates for Key Encapsulation Mechanisms (KEM) and Digital Signatures. This talk will cover the core operations within lattice-based schemes and efficient implementation strategies. Why it matters: As quantum computing advances, exploring and standardizing post-quantum cryptography is crucial for maintaining secure communication and data protection in the future.
Conor McMenamin from Universitat Pompeu Fabra presented a seminar on State Machine Replication (SMR) without honest participants. The talk covered the limitations of current SMR protocols and introduced the ByRa model, a framework for player characterization free of honest participants. He then described FAIRSICAL, a sandbox SMR protocol, and discussed how the ideas could be extended to real-world protocols, with a focus on blockchains and cryptocurrencies. Why it matters: This research on SMR protocols and their incentive compatibility could lead to more robust and secure blockchain technologies in the region.
Associate Professor Anamaria Costache from the Norwegian University of Science and Technology (NTNU) will present a seminar on Fully Homomorphic Encryption (FHE). The talk will cover recent advancements in FHE, its mathematical foundations, and implementation results. It will also address remaining challenges in the field. Why it matters: FHE's growing importance is driven by Machine Learning as a Service and the increasing value of secure computation, though the seminar itself has no direct connection to the Middle East.
This paper details an autonomous cooperative wall-building system using UAVs developed for Challenge 2 of the MBZIRC 2020 competition. The system employs scanning, RGB-D detection, precise grasping, and multi-UAV coordination to place bricks on a wall. The CTU-UPenn-NYU approach achieved the highest score in the competition by correctly placing the most bricks. Why it matters: This demonstrates advanced capabilities in robotics and autonomous systems relevant for construction and infrastructure development in challenging environments.
Team NimbRo's robot Mario won the MBZIRC 2017 Challenge 2 by autonomously manipulating a valve stem using a wrench. The robot uses an omnidirectional base for locomotion and a 3D laser scan detector to find the manipulation panel. A deep neural network detects and selects the correct tool from grayscale images, and motion primitives are adapted to turn the valve stem. Why it matters: This work demonstrates advanced robotic manipulation capabilities relevant for industrial automation and hazardous environment operations in the region.