Morello-HAT: Morello High-Level API and Tooling

Morello-HAT：Morello 高级 API 和工具

基本信息

批准号：
EP/X015955/1
负责人：
Wim Vanderbauwhede
金额：
$ 143.81万
依托单位：
University of Glasgow
依托单位国家：
英国
项目类别：
Research Grant
财政年份：
2022
资助国家：
英国
起止时间：
2022 至无数据
项目状态：
未结题

来源：
https://gtr.ukri.org/projects?ref=EP%2FX015955%2F1
关键词：
Morello HAT Level API Tooling

项目摘要

The CHERI project has created the infrastructure for hardware capabilities. The Morello project implements these concepts and tools for the Arm architecture. In terms of programming languages, the focus of CHERI and Morello has been primarily on C but considerable work has also been done on C++ and some more preliminary work on Rust. The Morello-HAT project (Morello High-Level API and Tooling) intends to create a common API that can be used by compiler developers as well as programmers of higher-level languages, to allow them to leverage Morello's HW capabilities to improve memory security and type safety, spatial as well as temporal, of their language and programs.The project consists of three work packages:1. Develop the API using C++, Rust, Go and Dart as target languages2. Demonstrate the usability and effectiveness of the API on a series of example applications by ML-based detection of vulnerabilities and assessment of the effectiveness of our API in mitigation of vulnerabilities.3. Use hardware capabilities to enhance the debug infrastructure.WP 1 High-Level Capability APIThe technical focus of the work will be on higher-level APIs which will use capabilities to harden run-time type checking, dynamic memory management and concurrency.WP1.1 will start from existing work on C++ to design the API foundations for object type safety and investigate the use of capabilities in managed memory. 1. Develop a C++ API for object type safety 2. Develop a capability-based garbage collector for C/C++WP1.2 will focus on Rust, Go and Dart, fast-growing programming languages that are representative for many modern programming languages. 1. Building on existing work on use of capabilities in Rust, extend the type safety API from WP1 to languages with a Rust-like type system, and design a concurrency API. 2. Provide capability support for garbage collection and concurrency, using Go as an example of a language with managed memory, first-class concurrency support and structural typing. 3. Dart, set to become the preferred language for Android app development, allows dynamic typing which run-time checks. This task focuses on supporting these checks with capabilities.WP 2 Machine learning based validation of the high-level APIWe will use the High-level API from WP1 and the debug interface built in our EPSRC AppControl project to create an efficient data collection mechanism for collecting unique data features from the Morello architecture, which will be used to train our ML models for detection of anomalies in non-capability as well as capability versions of applications written in C++, Rust, Go and Dart.WP 2.1 will focus on building data collection mechanism and ML detection models for validation of the high-level API 1. Setup debug interface to create an efficient low-level data collection mechanism. 2. Create benchmark vulnerable testing suites 3. Design data pre-processing and normalisation algorithms for data collection and analysis of data features. 4. Train and validate the abnormality detection ML modelsWP 2.2 will focus on validating the API from WP1 using ML based approaches. 1. Develop ML runtime compute API 2. Develop ML inference models 3. Test and validate the high-level API using the ML modelsWP 3 Securing the debug infrastructureWP3 will enhance the traditionally exposed debug infrastructure by creating a ICMetrics secured software API on top of the CHERI software stack for debug and authentication. WP 3.1 Create high-level API for accessing the debug subsystem and registers 1. Analyse debug mechanism and authentication signals to create high-level API to access debug infrastructure 2. Create ICMetrics secured software API 3. Integrate, test and validate the debug stackWP 3.2 Carry out trial and evaluation on the enhanced debug management mechanism. 1. Create penetration testing and evaluation program suites 2. Evaluate and analyse the enhanced debug mechanism

Cheri项目已为硬件功能创建了基础架构。 Morello项目为ARM架构实施了这些概念和工具。在编程语言方面，Cheri和Morello的重点主要放在C上，但是在C ++上也做了相当大的工作，并且在Rust上进行了一些更初步的工作。 Morello-Hat项目（Morello高级API和工具）打算创建一个通用的API，可以由编译器开发人员以及高级语言的程序员使用，以使他们能够利用Morello的HW功能来提高记忆安全性和类型的安全性，空间和类型的安全性，空间和类型的语言和程序和程序。使用C ++，Rust，Go和Dart作为目标语言开发API2。通过基于ML的漏洞检测以及对API在缓解漏洞的有效性的评估，证明了API对一系列示例应用的可用性和有效性。3。 Use hardware capabilities to enhance the debug infrastructure.WP 1 High-Level Capability APIThe technical focus of the work will be on higher-level APIs which will use capabilities to harden run-time type checking, dynamic memory management and concurrency.WP1.1 will start from existing work on C++ to design the API foundations for object type safety and investigate the use of capabilities in managed memory. 1。为对象类型安全2开发C ++ API。开发一个基于功能的垃圾收集器，用于C/C ++ WP1.2将重点放在Rust，Go and Dart，Dart，快速增长的编程语言上，这些语言代表着许多现代编程语言。 1。基于在RUST中使用功能的现有工作，将类型的安全性API从WP1扩展到具有类似Rust类型系统的语言，并设计并发API。 2。使用GO作为具有托管内存，一流并发支持和结构性键入的语言的示例，为垃圾收集和并发提供了能力支持。 3. DART将成为Android应用程序开发的首选语言，允许动态键入哪个运行时检查。 This task focuses on supporting these checks with capabilities.WP 2 Machine learning based validation of the high-level APIWe will use the High-level API from WP1 and the debug interface built in our EPSRC AppControl project to create an efficient data collection mechanism for collecting unique data features from the Morello architecture, which will be used to train our ML models for detection of anomalies in non-capability as well as capability versions of用C ++，Rust，Go和Dart.wp 2.1编写的应用程序将集中在构建数据收集机制和ML检测模型上，以验证高级API 1.设置调试接口，以创建有效的低级数据收集机制。 2。创建基准测试套件3。设计数据预处理和标准化算法，用于数据收集和分析数据功能。 4。训练和验证异常检测ML ModelSWP 2.2将专注于使用基于ML的方法从WP1验证API。 1。开发ML运行时计算API 2。开发ML推理模型3。使用ML Modelswp 3测试和验证高级API，确保Debug InfrastructureWp3将增强传统上揭示的调试基础架构，通过创建ICMetrics Software API在Cheri Software actack for Debug和Debag for Debug and perhentication。 WP 3.1创建用于访问调试子系统和注册的高级API 1。分析调试机制和身份验证信号，以创建高级API以访问Debug Infrastructure 2。创建ICMetrics Software Software API 3。集成，测试并验证Debug StackWP 3.2进行了debug StackWP 3.2进行EANCAND DEBANCED MANCENANCENS。 1。创建渗透测试和评估计划套件2。评估和分析增强的调试机制