Recent attacks on the software supply chain have shed light on the fragility and importance of ensuring the security and integrity of this vital ecosystem. Addressing the technical and social challenges to building trustworthy software for deployment in ...

The workshop on "Attacks and Solutions in HardwarE Security (ASHES)" welcomes any theoretical and practical works on hardware security, including attacks, solutions, countermeasures, proofs, classification, formalization, and implementations. Besides ...

Clouds and massive-scale computing infrastructures are starting to dominate computing and will likely continue to do so for the foreseeable future. Major cloud operators are now comprising millions of cores hosting substantial fractions of corporate and ...

The 11th Workshop on Encrypted Computing and Applied Homomorphic Cryptography is held in Copenhagen, Denmark on Novem- ber 26, 2023, co-located with the ACM Conference on Computer and Communications Security (CCS). The workshop aims to bring together ...

Fully Homomorphic Encryption (FHE) is a technique that allows computation on encrypted data. It has the potential to drastically change privacy considerations in the cloud, but high computational and memory overheads are preventing its broad adoption. ...

C/C++ memory safety issues, such as out-of-bounds errors, are still prevalent in today's applications. The presence of a single exploitable software bug allows an adversary to gain unauthorized memory access and ultimately compromise the entire system. ...

Due to an increase in the availability of cheap off-the-shelf radio hardware, signal spoofing and replay attacks on satellite ground systems have become more accessible than ever. This is particularly a problem for legacy systems, many of which do not ...

To reduce latency and communication overhead of asynchronous Byzantine Fault Tolerance (BFT) consensus, an optimistic path is often added, with Ditto and BDT as state-of-the-art representatives. These protocols first attempt to run an optimistic path ...

Distributed Multi-exit Neural Networks (MeNNs) use partitioning and early exits to reduce the cost of neural network inference on low-power sensing systems. Existing MeNNs exhibit high inference accuracy using policies that select when to exit based on ...

In autonomous driving, millimeter wave (mmWave) radar has been widely adopted for object detection because of its robustness and reliability under various weather and lighting conditions. For radar object detection, deep neural networks (DNNs) are ...

Asynchronous common subset (ACS) is a powerful paradigm enabling applications such as Byzantine fault-tolerance (BFT) and multi-party computation (MPC). The most efficient ACS framework in the information-theoretic setting is due to Ben-Or, Kelmer, and ...