| Title | Data Exfiltration: Methods and Detection Countermeasures |
| Publication Type | Conference Paper |
| Year of Publication | 2021 |
| Authors | King, James, Bendiab, Gueltoum, Savage, Nick, Shiaeles, Stavros |
| Conference Name | 2021 IEEE International Conference on Cyber Security and Resilience (CSR) |
| Keywords | composability, countermeasures, cyberattack, Data Exfiltration, Instruments, intrusion detection system, IP networks, Measurement, Metrics, network intrusion detection, Planning, privacy, pubcrawl, security, steganography, steganography detection, telecommunication traffic, Timing |
| Abstract | Data exfiltration is of increasing concern throughout the world. The number of incidents and capabilities of data exfiltration attacks are growing at an unprecedented rate. However, such attack vectors have not been deeply explored in the literature. This paper aims to address this gap by implementing a data exfiltration methodology, detailing some data exfiltration methods. Groups of exfiltration methods are incorporated into a program that can act as a testbed for owners of any network that stores sensitive data. The implemented methods are tested against the well-known network intrusion detection system Snort, where all of them have been successfully evaded detection by its community rule sets. Thus, in this paper, we have developed new countermeasures to prevent and detect data exfiltration attempts using these methods. |
| DOI | 10.1109/CSR51186.2021.9527962 |
| Citation Key | king_data_2021 |
Data Exfiltration: Methods and Detection Countermeasures