A Combined Dependability and Security Approach for Third Party Software in Space Systems
August 22, 2016 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
David Escorial Rico, Mark Hann
arXiv ID
1608.06133
Category
cs.SE: Software Engineering
Citations
2
Venue
arXiv.org
Last Checked
4 months ago
Abstract
Software components for on-board architectures in the space domain are increasingly reliant on Commercial Off-The-Shelf (COTS), Open Source (OSS) or other third party software products. However, these software components often have not been built with mission critical requirements in mind. Development project teams incorporating these products have limited knowledge of or control over the processes applied during the design, implementation, testing and maintenance of selected COTS/OSS software products. These constraints generate uncertainty of potential software induced failures. Moreover, the lack of information regarding security vulnerabilities increases the risks of their usage, since their exploitation might lead to undesired behaviour of the software and therefore to a system failure. The purpose of this paper is to present a combined approach that takes into account reliability and security enhancements for third party software, based on Time-Space Partitioning and Multiple Levels of Security.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Software Engineering
R.I.P.
π»
Ghosted
R.I.P.
π»
Ghosted
Microservices: yesterday, today, and tomorrow
π
π
The Cartographer
A Survey of Machine Learning for Big Code and Naturalness
R.I.P.
π»
Ghosted
An Overview on Smart Contracts: Challenges, Advances and Platforms
R.I.P.
π»
Ghosted
Slither: A Static Analysis Framework For Smart Contracts
R.I.P.
π»
Ghosted
ContractFuzzer: Fuzzing Smart Contracts for Vulnerability Detection
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted