Detecting encrypted stepping-stone connections

Ting He, Lang Tong

Research output: Contribution to journalArticle

49 Scopus citations

Abstract

Stepping-stone attacks are often used by network intruders to hide their identities. In a stepping-stone attack, attacking commands are sent indirectly to the victim through a chain of compromised hosts acting as "stepping stones."In defending against such attacks, it is necessary to detect stepping-stone connections at the compromised hosts. The use of encrypted connections by the attacker complicates the detection problem and the attacker's active timing perturbation and insertion of chaff make it even more challenging. This paper considers strategies to identify stepping-stone connections when the attacker is able to encrypt the attacking packets and perturb their timing. Furthermore, the attacker can also add chaff packets in the attacking stream. The paper first considers stepping-stone connections subject to packet-conserving transformations by the attacker. Two activity-based algorithms are proposed to detect stepping-stone connections with bounded memory or bounded delay perturbation, respectively. These algorithms are proven to have exponentially decaying false alarm probabilities if normal traffic can be modelled as Poisson processes. It is shown that the proposed algorithms improve the performance of an existing stepping-stone detection algorithm. This paper then addresses the detection of stepping-stone connections with both timing perturbation and chaff. Robust algorithms are developed to deal with chaff evasion. It is proven that the proposed robust algorithms can tolerate a number of chaff packets proportional to the size of the attacking traffic, and have vanishing false alarm probabilities for Poisson traffic. Simulations using synthetic data are used to validate the theoretical analysis. Further results using actual Internet traces are shown to demonstrate the performance of the proposed algorithms.

Original languageEnglish (US)
Pages (from-to)1612-1623
Number of pages12
JournalIEEE Transactions on Signal Processing
Volume55
Issue number5 I
DOIs
StatePublished - May 1 2007

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Electrical and Electronic Engineering

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