Related papers: Execution Integrity with In-Place Encryption

Inverse reinforcement learning (IRL) aims to recover the reward function and the associated optimal policy that best fits observed sequences of states and actions implemented by an expert. Many algorithms for IRL have an inherently nested…

Index coding is concerned with efficient broadcast of a set of messages to receivers in the presence of receiver side information. In this paper, we study the secure index coding problem with security constraints on the receivers…

While data from Supervisory Control And Data Acquisition (SCADA) systems is sent upstream, it is both the length of pulses as well as their frequency present an excellent opportunity to incor-porate statistical fingerprinting. This is so,…

Intel has introduced a trusted computing technology, Intel Software Guard Extension (SGX), which provides an isolated and secure execution environment called enclave for a user program without trusting any privilege software (e.g., an…

Internet of Things is an ecosystem of interconnected devices that are accessible through the internet. The recent research focuses on adding more smartness and intelligence to these edge devices. This makes them susceptible to various kinds…

Control flow integrity (CFI) has received significant attention in the community to combat control hijacking attacks in the presence of memory corruption vulnerabilities. The challenges in creating a practical CFI has resulted in the…

An information-theoretic approach to irregular repetition slotted ALOHA (IRSA) is proposed. In contrast with previous works, in which IRSA analysis is conducted only based on quantities that are typical of collision models such as the…

Security Enhanced Linux (SELinux) is a security architecture for Linux implementing mandatory access control. It has been used in numerous security-critical contexts ranging from servers to mobile devices. But this is challenging as SELinux…

The adoption of high-performance multi-core platforms in avionics and automotive systems introduces significant challenges in ensuring predictable execution, primarily due to shared resource interferences. Many existing approaches study…

Implicit in-context learning (ICL) has newly emerged as a promising paradigm that simulates ICL behaviors in the representation space of Large Language Models (LLMs), aiming to attain few-shot performance at zero-shot cost. However,…

The simultaneous rise of machine learning as a service and concerns over user privacy have increasingly motivated the need for private inference (PI). While recent work demonstrates PI is possible using cryptographic primitives, the…

In this paper, secure wireless information and power transfer with intelligent reflecting surface (IRS) is proposed for a multiple-input single-output (MISO) system. Under the secrecy rate (SR) and the reflecting phase shifts of IRS…

Information Flow Control (IFC) is a collection of techniques for ensuring a no-write-down no-read-up style security policy known as noninterference. Traditional methods for both static and dynamic IFC suffer from untenable numbers of false…

Intel(R) Software Guard eXtensions (SGX) is a hardware-based technology for ensuring security of sensitive data from disclosure or modification that enables user-level applications to allocate protected areas of memory called enclaves. Such…

A central assumption in quantum key distribution (QKD) is that Eve has no knowledge about which rounds will be used for parameter estimation or key distillation. Here we show that this assumption is violated for iterative sifting, a sifting…

In this paper, we review the key figures of merit to assess the performance of advanced random access (RA) schemes exploiting physical layer coding, repetitions and collision resolution techniques. We then investigate RA modeling aspects…

The language models, especially the basic text classification models, have been shown to be susceptible to textual adversarial attacks such as synonym substitution and word insertion attacks. To defend against such attacks, a growing body…

Trusted Execution Environments (TEEs) allow user processes to create enclaves that protect security-sensitive computation against access from the OS kernel and the hypervisor. Recent work has shown that TEEs are vulnerable to side-channel…

Randomized smoothing is a leading approach for constructing classifiers that are certifiably robust against adversarial examples. Existing work on randomized smoothing has focused on classifiers with continuous inputs, such as images, where…

Memory disclosure attacks play an important role in the exploitation of memory corruption vulnerabilities. By analyzing recent research, we observe that bypasses of defensive solutions that enforce control-flow integrity or attempt to…