AI-SPRINT
Artificial Intelligence in Secure PRIvacy-preserving computing coNTinuum
Full project details (EU Research results portal): https://cordis.europa.eu/project/id/101016577
Project description:
Artificial Intelligence (AI), to become fully pervasive, needs resources at the edge of the network. The cloud can provide the processing power needed for big data, but edge computing is close to where data are produced and therefore crucial to their timely, flexible, and secure management. AI-SPRINT will define a framework for developing AI applications in computing continua, enabling a finely-tuned tradeoff between performance (e.g. in terms of end-to-end latency and throughput) and AI model accuracy, while providing security and privacy guarantees. AI-SPRINT outcomes are: i) simplified programming models to reduce the steep learning curves in the development of AI software in computing continua; ii) highly specialized building blocks for distributed training, privacy preservation and advanced machine learning models, to shorten time-to-market for AI applications; iii) automated deployment and dynamic reconfiguration to decrease the cost of operating AI software. Beneficiaries include end-users of AI systems, software developers, system integrators, and cloud providers. AI-SPRINT tools will make it possible to consider security and privacy early in the design stage and to seamlessly manage the time-varying conditions typical of real environments. Real-world scenarios are an integral part of AI-SPRINT as key to guiding requirements and development and validating results. Three heterogeneous use cases (farming 4.0, maintenance & inspection, and personalized healthcare) are built by industrial partners. Cutting-edge innovation is brought to the Consortium by four research partners with complementary expertise. Two system integrators provide vision on relevant verticals and technology insights, one cloud provider brings real-world implementation expertise, and two specialists in dissemination ensure impacts and uptake. AI-SPRINT will also pursue a sustainability path through the creation of an Alliance and Adopter Acceleration club as a marketplace for AI businesses
EuroVoc IDs: /natural sciences/computer and information sciences/software
EU Programme: Horizon 2020
EU Project
Project publications:
| EU Project | Has Title | Has Category | Has Type | Has Year | Has DOI |
|---|---|---|---|---|---|
| AI-SPRINT | Secure execution of ML workflows on the Computing Continuum | Artificial Intelligence and Machine Learning Systems | Conference proceedings | 2023 | https://doi.org/10.1145/3578245.3584727 |
| AI-SPRINT | SinClave: Hardware-assisted Singletons for TEEs | Artificial Intelligence and Machine Learning Systems | Conference proceedings | 2023 | https://doi.org/10.1145/3590140.3629107 |
| AI-SPRINT | A Sorted Datalog Hammer for Supervisor Verification Conditions Modulo Simple Linear Arithmetic | Artificial Intelligence and Machine Learning Systems | Conference proceedings | 2022 | https://doi.org/10.1007/978-3-030-99524-9 27 |
| AI-SPRINT | OSCAR-P and aMLLibrary: Performance Profiling and Prediction of Computing Continua Applications | Artificial Intelligence and Machine Learning Systems | Conference proceedings | 2023 | https://doi.org/10.1145/3578245.3584941 |
| AI-SPRINT | Securing the Execution of ML Workflows across the Compute Continua | Artificial Intelligence and Machine Learning Systems | Conference proceedings | 2023 | https://doi.org/10.1145/3578245 |
| AI-SPRINT | A Last-Level Defense for Application Integrity and Confidentiality | Artificial Intelligence and Machine Learning Systems | Conference proceedings | 2023 | https://doi.org/10.48550/arxiv.2311.06154 |
| AI-SPRINT | A Datalog Hammer for Supervisor Verification Conditions Modulo Simple Linear Arithmetic | Artificial Intelligence and Machine Learning Systems | Conference proceedings | 2021 | https://doi.org/10.1007/978-3-030-86205-3 |
| AI-SPRINT | Perun: Confidential Multi-stakeholder Machine Learning Framework with Hardware Acceleration Support | Artificial Intelligence and Machine Learning Systems | Conference proceedings | 2021 | https://doi.org/10.1007/978-3-030-81242-3 11 |
| AI-SPRINT | TaScaaS: A Multi-Tenant Serverless Task Scheduler and Load Balancer as a Service | Artificial Intelligence and Machine Learning Systems | Peer reviewed articles | 2021 | https://doi.org/10.1109/access.2021.3109972 |
| AI-SPRINT | On the Acceleration of FaaS Using Remote GPU Virtualization | Artificial Intelligence and Machine Learning Systems | Conference proceedings | 2023 | https://doi.org/10.1145/3578245.3584933 |
| AI-SPRINT | Capacity Planning for Dependable Services | Artificial Intelligence and Machine Learning Systems | Peer reviewed articles | 2023 | https://doi.org/10.1016/j.tcs.2023.114126 |
| AI-SPRINT | Discriminative Adversarial Privacy: Balancing Accuracy and Membership Privacy in Neural Networks | Artificial Intelligence and Machine Learning Systems | Conference proceedings | 2023 | https://doi.org/10.48550/arxiv.2306.03054 |
| AI-SPRINT | Enhancing Once-For-All: A Study on Parallel Blocks, Skip Connections and Early Exits | Artificial Intelligence and Machine Learning Systems | Conference proceedings | 2023 | https://doi.org/10.48550/arxiv.2302.01888 |
| AI-SPRINT | Trustworthy confidential virtual machines for the masses | Artificial Intelligence and Machine Learning Systems | Conference proceedings | 2023 | https://doi.org/10.1145/3590140.3629124 |
| AI-SPRINT | Heterogeneous Datasets for Federated Survival Analysis Simulation | Artificial Intelligence and Machine Learning Systems | Conference proceedings | 2023 | https://doi.org/10.1145/3578245.3584935 |
| AI-SPRINT | Challenges Towards Modeling and Generating Infrastructure-as-Code | Artificial Intelligence and Machine Learning Systems | Conference proceedings | 2023 | https://doi.org/10.1145/3578245.3584937 |
| AI-SPRINT | SGDE: Secure Generative Data Exchange for Cross-Silo Federated Learning | Artificial Intelligence and Machine Learning Systems | Conference proceedings | 2022 | https://doi.org/10.1145/3573942.3573974 |
| AI-SPRINT | Formal Foundations for Intel SGX Data Center Attestation Primitives | Artificial Intelligence and Machine Learning Systems | Conference proceedings | 2021 | https://doi.org/10.13140/rg.2.2.36760.21768 |
| AI-SPRINT | ADAM-CS - Advanced Asynchronous Monotonic Counter Service | Artificial Intelligence and Machine Learning Systems | Conference proceedings | 2021 | https://doi.org/10.1109/dsn48987.2021.00053 |
| AI-SPRINT | Anticipate, Ensemble and Prune: Improving Convolutional Neural Networks via Aggregated Early Exits | Artificial Intelligence and Machine Learning Systems | Conference proceedings | 2023 | https://doi.org/10.1016/j.procs.2023.08.190 |
| AI-SPRINT | Serverless Workflows for Containerised Applications in the Cloud Continuum | Artificial Intelligence and Machine Learning Systems | Peer reviewed articles | 2021 | https://doi.org/10.1007/s10723-021-09570-2 |