
With the growing complexity of networks and communications protocols that become increasingly enormous and extensive, we are confronted with the problem of covert channel that affects the confidentiality and integrity of data sent in the network. Covert channels also known as hidden channels can elude basic security systems such as Intrusion Detection Systems (IDS) and firewalls. We propose in this work a method to monitor and detect the presence of hidden channels that are based on an essential monitoring protocol "Internet Control Message Protocol" (ICMP). We undergo the network traffic with a set of verifications ranging from simple fields verification to more complex pattern matching operations. To validate our idea, we have installed Ptunnel, a tool that allows to tunnel TCP connections to a remote host using ICMP echo request and reply packets. Our experimental results show the possibility to discover such malicious traffic with high performance.
Network Security, [INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI], ICMP Tunneling, Covert Channel, [SPI] Engineering Sciences [physics], Traffic analysis, Tunneling Detection, Storage Chan- nel, ICMP protocol, [INFO.INFO-BI] Computer Science [cs]/Bioinformatics [q-bio.QM], [INFO.INFO-CR] Computer Science [cs]/Cryptography and Security [cs.CR]
Network Security, [INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI], ICMP Tunneling, Covert Channel, [SPI] Engineering Sciences [physics], Traffic analysis, Tunneling Detection, Storage Chan- nel, ICMP protocol, [INFO.INFO-BI] Computer Science [cs]/Bioinformatics [q-bio.QM], [INFO.INFO-CR] Computer Science [cs]/Cryptography and Security [cs.CR]
| 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). | 4 | |
| 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). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
