Secure provenance: the essential of bread and butter of data forensics in cloud computing
By Rongxing Lu, Xiaodong Lin, Xiaohui Liang, Xuemin Shen. ACM Asia Conference on Computer and Communications Security, 2010
443 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Information Systems
View Paper: https://www.semanticscholar.org/paper/fc33c3dbf05391ce08ea093da0fe677cc8da0096
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Samee Ullah Khan
- Assad Abbas
- Siani Pearson
- Ryan Kok Leong Ko
- Sherman S. M. Chow
- Cheng-Kang Chu
- Miranda Mowbray
- Wen-Guey Tzeng
In Information Systems
- Samee Ullah Khan
- Siani Pearson
- Ryan Kok Leong Ko
- Sherman S. M. Chow
- Wen-Guey Tzeng
- Robert Huijie Deng
- Bu-Sung Lee
- Jingbo Yan
Citations in the corpus
- Key-Aggregate Cryptosystem for Scalable Data Sharing in Cloud Storage (2014, methodology): “(2) We then instantiate the KASE framework by designing a concrete KASE scheme.”
- A Review on the State-of-the-Art Privacy-Preserving Approaches in the e-Health Clouds (2014, background): “Generally, the provenance may include tracking and monitoring of 1) actions taken, 2) the entities taking the actions, 3) the location of the actions, and 4) the reason for action [93].”
- Mona: Secure Multi-Owner Data Sharing for Dynamic Groups in the Cloud (2013, background): “Lu et al. [7] proposed a secure provenance scheme, which is built upon group signatures and ciphertext-policy attribute-based encryption techniques.”
- TrustCloud: A Framework for Accountability and Trust in Cloud Computing (2011, background): “Secure provenance [28] and privacy-aware provenance [29] have also been proposed for cloud computing systems, as provenance information may contain or expose sensitive, confidential or proprietary information directly or indirectly.”