A Discretionary Access Control Method for Preventing Data Exfiltration (DE) via Removable Devices

Wilson, Duane; Lavine, Michael K.

doi:10.1007/978-3-642-11534-9_15

Cited by 2 publications

References 0 publications

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“…In our review, we observed that quite a large number of countermeasures are either not evaluated at all ( [23], [40], [45] , [48] , [49] , [62] , [75] , [88] , [91] , [67] , [92] , [105] , [110], [111], [114], [137], [141], [154], , [160], [174], , [175]) or evaluated weakly ( [60], [70], [100], [109], [132], [138], [147], [158], [161], [165], [171]). We consider an evaluation as weak evaluation when the system is evaluated with a small dataset (e.g.…”

Section: Discussionmentioning

confidence: 99%

“…[132], [138], [147], [171]), or just one type of data (e.g. [70], [100], [165]), or restricted to a specific case (e.g. [109], [160]).…”

Section: Discussionmentioning

confidence: 99%

“…Wilson and Lavine [70] present a discretionary access control method for preventing data exfiltration via removable devices. The authors tie the dissemination of files via USB storage to the classification of a file.…”

Section: Discrete Access Controlmentioning

confidence: 99%

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Data exfiltration: A review of external attack vectors and countermeasures

Ullah¹,

Edwards

Ramdhany

et al. 2018

Journal of Network and Computer Applications

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Context: One of the main targets of cyber-attacks is data exfiltration, which is the leakage of sensitive or private data to an unauthorized entity. Data exfiltration can be perpetrated by an outsider or an insider of an organization. Given the increasing number of data exfiltration incidents, a large number of data exfiltration countermeasures have been developed. These countermeasures aim to detect, prevent, or investigate exfiltration of sensitive or private data. With the growing interest in data exfiltration, it is important to review data exfiltration attack vectors and countermeasures to support future research in this field. Objective: This paper is aimed at identifying and critically analysing data exfiltration attack vectors and countermeasures for reporting the status of the art and determining gaps for future research. Method: We have followed a structured process for selecting 108 papers from seven publication databases. Thematic analysis method has been applied to analyse the extracted data from the reviewed papers. Results: We have developed a classification of (1) data exfiltration attack vectors used by external attackers and (2) the countermeasures in the face of external attacks. We have mapped the countermeasures to attack vectors. Furthermore, we have explored the applicability of various countermeasures for different states of data (i.e., in use, in transit, or at rest). Conclusion: This review has revealed that (a) most of the state of the art is focussed on preventive and detective countermeasures and significant research is required on developing investigative countermeasures that are equally important; (b) Several data exfiltration countermeasures are not able to respond in real-time, which specifies that research efforts need to be invested to enable them to respond in real-time (c) A number of data exfiltration countermeasures do not take privacy and ethical concerns into consideration, which may become an obstacle in their full adoption (d) Existing research is primarily focussed on protecting data in 'in use' state, therefore, future research needs to be directed towards securing data in 'in rest' and 'in transit' states (e) There is no standard or framework for evaluation of data exfiltration countermeasures. We assert the need for developing such an evaluation framework.

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