S2Logger: End-to-End Data Tracking Mechanism for Cloud Data Provenance

Suen, Chun Hui; Ko, Ryan K. L.; Tan, Alan Yu Shyang; Jagadpramana, Peter; Lee, Bu-Sung

doi:10.1109/trustcom.2013.73

Cited by 60 publications

(32 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Inability to track data in the cloud has raised a number of challenges, for example, data provenance has turned out to be a very big concern because there exist no data tracking tools focused in the cloud at the time of writing this paper. Nevertheless the logging mechanisms that exist are mainly focused on operating in a system-centric perspective [7]. Research on methods of collecting digital evidence in the cloud and potential digital evidence have been proposed by Kebande & venter, where potential evidence can be digitally preserved for purposes of conducting digital investigation [17], [18], [19], [20], [21], [22].…”

Section: Cloud Computingmentioning

confidence: 99%

See 1 more Smart Citation

An Approach for Estimating Forensic Data Provenance of an Object in the Cloud Environment using One Dimensional Successive Bisection Method

Kebande¹,

Karie²

2016

IJCA

View full text Add to dashboard Cite

The decline in traditional forensics and the emergence of cloud forensics has made it hard for digital forensic investigators to conduct digital investigations due to inadaptability of the cloud to digital forensic processes. Additionally, data that resides in the cloud is normally scattered across constantly changing data centers, hosts and virtual instances are easily destroyed as they are created. On the same note it is not easy to seize physical devices where a particular crime has occurred and locating the origin of an object in the cloud can be a challenge when we do not know where the actual data resides. Data provenance provides a solution whereby one can trace data based on the tag as it keeps changing directions in the cloud. However, if the distance between two particular tagged data is taken into account then the source and destination of an object can be located easily which can then enable digital forensic investigators to locate the physical devices. The problem that this paper is addressing is that, there is no easy way of locating data provenance in the cloud environment without estimating the distance between tagged data that moves in the cloud. Based on this, the authors have proposed a mechanism for locating the provenance of an object using successive bisection method. Similar test have been carried using different intervals in an experiment and the results are very promising.

show abstract

Section: Cloud Computingmentioning

confidence: 99%

“…In this research the authors highlights that if the metadata tags cannot be appended to the headers of all or any other file, then the metadata should be stored separately from the data objects [12].…”

Section: Related Workmentioning

confidence: 99%

An Approach for Estimating Forensic Data Provenance of an Object in the Cloud Environment using One Dimensional Successive Bisection Method

Kebande¹,

Karie²

2016

IJCA

View full text Add to dashboard Cite

show abstract

“…Improvements to the provenance concepts Flogger introduced were made. For example, DataPROVE [20] was proposed to cater to the causality issue identified and S2Logger [21] was proposed to solve the scalability and visualisation challenges in end-to-end data activity tracking in the cloud. However, all of them still were unable to maintain the authenticity and integrity of provenance logs (e.g.…”

Section: B Critical Gaps Identified In Related Provenance Techniquesmentioning

confidence: 99%

Progger: An Efficient, Tamper-Evident Kernel-Space Logger for Cloud Data Provenance Tracking

Will

2014

2014 IEEE 7th International Conference on Cloud Computing

Self Cite

View full text Add to dashboard Cite

Cloud data provenance, or "what has happened to my data in the cloud", is a critical data security component which addresses pressing data accountability and data governance issues in cloud computing systems. In this paper, we present Progger (Provenance Logger), a kernel-space logger which potentially empowers all cloud stakeholders to trace their data. Logging from the kernel space empowers security analysts to collect provenance from the lowest possible atomic data actions, and enables several higher-level tools to be built for effective end-to-end tracking of data provenance. Within the last few years, there has been an increasing number of proposed kernel space provenance tools but they faced several critical data security and integrity problems. Some of these prior tools' limitations include (1) the inability to provide log tamper-evidence and prevention of fake/ manual entries, (2) accurate and granular timestamp synchronisation across several machines, (3) log space requirements and growth, and (4) the efficient logging of root usage of the system. Progger has resolved all these critical issues, and as such, provides high assurance of data security and data activity audit. With this in mind, the paper will discuss these elements of high-assurance cloud data provenance, describe the design of Progger and its efficiency, and present compelling results which paves the way for Progger being a foundation tool used for data activity tracking across all cloud systems.

show abstract

“…Other approaches advocate the collection of data provenance to increase the awareness of data in third-party cloud services [38,41,42]. However, the importance of trusted computing for cloud services is accepted.…”

Section: B Cloud Computingmentioning

confidence: 99%

Digital Trust - Trusted Computing and Beyond: A Position Paper

Akram

2014

2014 IEEE 13th International Conference on Trust, Security and Privacy in Computing and Communications

Self Cite

View full text Add to dashboard Cite

Abstract-Along with the invention of computers and interconnected networks, physical societal notions like security, trust, and privacy entered the digital environment. The concept of digital environments begins with the trust (established in the real world) in the organisation/individual that manages the digital resources. This concept evolved to deal with the rapid growth of the Internet, where it became impractical for entities to have prior offline (real world) trust. The evolution of digital trust took diverse approaches and now trust is defined and understood differently across heterogeneous domains. This paper looks at digital trust from the point of view of security and examines how valid trust approaches from other domains are now making their way into secure computing. The paper also revisits and analyses the Trusted Platform Module (TPM) along with associated technologies and their relevance in the changing landscape. We especially focus on the domains of cloud computing, mobile computing and cyber-physical systems. In addition, the paper also explores our proposals that are competing with and extending the traditional functionality of TPM specifications.

show abstract

S2Logger: End-to-End Data Tracking Mechanism for Cloud Data Provenance

Cited by 60 publications

References 12 publications

An Approach for Estimating Forensic Data Provenance of an Object in the Cloud Environment using One Dimensional Successive Bisection Method

An Approach for Estimating Forensic Data Provenance of an Object in the Cloud Environment using One Dimensional Successive Bisection Method

Progger: An Efficient, Tamper-Evident Kernel-Space Logger for Cloud Data Provenance Tracking

Digital Trust - Trusted Computing and Beyond: A Position Paper

Contact Info

Product

Resources

About