Alpernas et al., 2018 - Google Patents
Secure serverless computing using dynamic information flow controlAlpernas et al., 2018
View PDF- Document ID
- 13685675606507007244
- Author
- Alpernas K
- Flanagan C
- Fouladi S
- Ryzhyk L
- Sagiv M
- Schmitz T
- Winstein K
- Publication year
- Publication venue
- Proceedings of the ACM on Programming Languages
External Links
Snippet
The rise of serverless computing provides an opportunity to rethink cloud security. We present an approach for securing serverless systems using a novel form of dynamic information flow control (IFC). We show that in serverless applications, the termination …
- 238000000034 method 0 abstract description 37
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Alpernas et al. | Secure serverless computing using dynamic information flow control | |
| Hunt et al. | Ryoan: A distributed sandbox for untrusted computation on secret data | |
| Subramanyan et al. | A formal foundation for secure remote execution of enclaves | |
| Quoc et al. | Securetf: A secure tensorflow framework | |
| Sinha et al. | Moat: Verifying confidentiality of enclave programs | |
| Bacon et al. | Information flow control for secure cloud computing | |
| Backes et al. | Appguard–fine-grained policy enforcement for untrusted android applications | |
| Pappas et al. | CloudFence: Data flow tracking as a cloud service | |
| Sankaran et al. | Workflow integration alleviates identity and access management in serverless computing | |
| Jiang et al. | Uranus: Simple, efficient sgx programming and its applications | |
| Austin et al. | Multiple facets for dynamic information flow with exceptions | |
| Heule et al. | IFC inside: Retrofitting languages with dynamic information flow control | |
| DeHon et al. | Preliminary design of the SAFE platform | |
| Strackx et al. | Salus: Kernel support for secure process compartments | |
| Khan et al. | A protocol for preventing insider attacks in untrusted infrastructure-as-a-service clouds | |
| Mofrad et al. | Securing big data scientific workflows via trusted heterogeneous environments | |
| Zobaed et al. | Confidential computing across edge-to-cloud for machine learning: A survey study | |
| Pappas et al. | CloudFence: Enabling users to audit the use of their cloud-resident data | |
| Fong | Viewer's discretion: Host security in mobile code systems | |
| Feng et al. | Survey of research on confidential computing | |
| Crowell et al. | The confinement problem: 40 years later | |
| Shepherd et al. | Trusted Execution Environments | |
| Szekeres et al. | Making Distributed Mobile Applications SAFE: Enforcing User Privacy Policies on Untrusted Applications with Secure Application Flow Enforcement | |
| Fitzek | Development of an ARM TrustZone aware operating system ANDIX OS | |
| Mofrad | Securing Big Data Scientific Workflows & GPGPU Computation in the Commodity Cloud with Hardware-Assisted Trusted Execution Environments |