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Modern malware increasingly exploits information hiding to re- main undetected while attacking. To this aim, network covert chan- nels, i.e., hidden communication paths established within legitimate flows, can be used to exfiltrate data or exchange commands with- out getting noticed by firewalls, antivirus, and intrusion detection systems. Since the secret data can be directly injected in various portions of the stream or encoded via suitable alterations of the traffic, spotting hidden communications is a challenging and poorly generalizable task. Moreover, the majority of works addressed IPv4, thus leaving the detection of covert channels targeting IPv6 almost unexplored. This paper presents bccstego, i.e., an inspection framework for computing statistical indicators to reveal covert channels targeting the IPv6 header. The proposed approach has been designed to be easily extended, for instance to search for channels not known a priori. Numerical results demonstrate the effectiveness of our first tool in the bccstego framework as well as its ability to handle high-throughput IPv6 flows without adding additional delays.
packet inspection, stegomalware, network covert channel, packet inspection, eBPF, BPF compiler collection, covert channels, information hiding, eBPF, stegomalware
packet inspection, stegomalware, network covert channel, packet inspection, eBPF, BPF compiler collection, covert channels, information hiding, eBPF, stegomalware
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 14 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
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| downloads | 23 |

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