Data exfiltration: A review of external attack vectors and countermeasures

Abstract

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.

Cybersecurity Metrics for Enhanced Protection of Healthcare IT Systems

“…• Volume of outbound traffic. unusual increase in outgoing traffic could be a sign of data exfiltration [66]. Organisations have a responsibility to protect their sensitive data and any breach is likely to attract attention from the government bodies with responsibilities for enforcing the data protection laws such as GDPR.…”

A Review of Insider Threat Detection: Classification, Machine Learning Techniques, Datasets, Open Challenges, and Recommendations

“…This section discusses the surveys and review articles on insider threats. Only a few papers were found, i.e., [6][7][8][9][10][11][12][13][14][15][16]. Walker-Roberts et al [6] conducted a systematic review on insider threat detection; however, the scope of the review focused only on insider threats in healthcare critical infrastructures.…”

Architectural Tactics for Big Data Cybersecurity Analytics Systems: A Review

“…In the context of security analytics, privacy assurance is quite critical because a number of security analytic systems capture, store, and process packet payload, which contains personal data of users. For example, one of the reviewed papers i.e., [S17] employs a technique called content inspection [43], which in addition to the header information, also capture, store, and process payload of network packets. According to the European data laws and regulations [44], it is not allowed to store and process the packet payload without the relevant users' consent.…”