Landmark-based data location verification in the cloud: review of approaches and challenges

Abstract

Data storage on the cloud is growing every day and many companies, administrations, and individuals are now outsourcing storage of their data to large-scale Cloud Service Providers (CSP). However, because of today's cloud infrastructure virtualization, data owners cannot easily know the location where their data are stored. Even in case of the establishment of a strong Service-Level Agreement, which includes an initial guarantee regarding data location, the CSP may then move data to another location, like another country, in order to cut storage costs or for any other reasons, including backup mistakes and fraudulent use of data. Data location verification is required due to legal, privacy, and performance constraints. Recently "Where are my data located in the cloud?" has become a challenge and solutions have been proposed to verify data location, under given assumptions regarding CSP behavior. The objective of this paper is twofold: propose a comprehensive classification of the location verification approaches and discuss their vulnerabilities regarding malicious CSP attacks. Location verification solutions may be Framework-based, Hardware-based or Landmark-based. This paper addresses only landmark-based approaches for their deployment flexibility and low cost.

Data sovereignty: A review

“…Occasionally, these agents are also portrayed as the contributors, facilitators, or difference-makers to the sovereignty of some agent or other, e.g. when commentators observe: “ China’s Cybersecurity Law took effect in 2017 embodying the state’s commitment to ‘data sovereignty’” (Kuner et al., 2019: 1); when they demand: “Data sovereignty: governments must provide and enforce laws to guarantee data independence to their citizens and companies in order to avoid particularly data access by foreign authorities” (Irain et al., 2017: 2); or when they note that “ patients always have data sovereignty and further parties like care providers or researchers are only involved if desired by patients ” (Dehling and Sunyaev, 2014: 89).…”

Network Services Anomalies in NFV: Survey, Taxonomy, and Verification Methods

“…Pratical approaches for GLV encompass: distance-bounding protocols [59], landmark-based geolocation [63], [70], and IP address mapping based geolocation [64]- [67], topology-aware geolocation [68]- [69], and hardware-based geolocation [56], [60]- [62].…”

“…Landmark-based geolocation techniques [63], [70] assume a correlation or mapping between network metrics (e.g., Round Time Trip, hop counts, bandwidth, etc.) and geographic distance.…”

Assessment of Regression-based Techniques for Data Location Verification at Country-Level (Invited Paper)

“…A distance is associated to RTT value. Among the proposed DLV approaches, we select three, which are representative in the field of data location verification [12].…”

“…Users can either trust the CSP and there is no data location verification problem, or assume that the CSP can be malicious and store data in an inappropriate location and they have to deploy mechanisms enabling data location verification at any time. Huge approaches addressing this problem were proposed in literature [12]. Three DLV (data location verification) approaches classes are commonly distinguished:…”