Publicaties
SpectrEM: Exploiting Electromagnetic Emanations During Transient Execution KU Leuven
Modern processors implement sophisticated performance optimizations, such as out-of-order execution and speculation, that expose programs to so-called transient execution attacks. So far, such attacks rely on specific on-chip covert channels (e.g., cache timing), instilling the hope that they can be thwarted by closing or weakening these channels. In this paper, we consider the inevitable physical side effects of transient execution. We focus on ...
A 334 - μW 0.158 - mm2 ASIC for Post-Quantum Key-Encapsulation Mechanism Saber With Low-Latency Striding Toom–Cook Multiplication KU Leuven
Lattice-based cryptography is a novel approach to public key cryptography (PKC), of which the mathematical investigation (so far) resists attacks from quantum computers. By choosing a module learning with errors (MLWE) algorithm as the next standard, the National Institute of Standards and Technology (NIST) follows this approach. The multiplication of polynomials is the central bottleneck in the computation of lattice-based cryptography. Because ...
PROVE: Provable remote attestation for public verifiability KU Leuven Vrije Universiteit Brussel
Evolving Non-cryptographic Hash Functions Using Genetic Programming for High-speed Lookups in Network Security Applications KU Leuven
Non-cryptographic (NC) hash functions are the core part of many networking and security applications such as traffic flow monitoring and deep packet inspection. For these applications, speed is more important than strong cryptographic properties. In Terabit Ethernet networks, the speed of the hash functions can have a significant impact on the overall performance of the system when it is required to process the packets at a line rate. Hence, ...
Optimized algorithms and architectures for fast non-cryptographic hash functions in hardware KU Leuven
Feature dimensionality in CNN acceleration for high-throughput network intrusion detection KU Leuven
With the ever increasing need for better cybersecurity, and due to the continuous growth of network traffic bandwidths, there is a continuous pursuit of faster and smarter network intrusion detection systems. Neural network-based solutions on FPGAs are very effective in detecting different types of attacks, but have problems with analyzing network traffic online at line speed. One important bottleneck that limits the throughput in raw ...