The increasing diffusion of malware endowed with steganographic and cloaking capabilities requires tools and techniques for conducting research activities, testing real deployments and elaborating mitigation mechanisms. To investigate attacks targeting network and appliances, a core requirement concerns the availability of suitable traffic traces, which can be used to derive mathematical models for simulation or to develop machine-learning-based countermeasures. Unfortunately, the young nature of threats injecting secrets or cloaking their presence within network traffic, the high protocol- dependent nature of the various embedding processes, and privacy issues, prevent the vast diffusion of datasets to perform research. Therefore, in this paper we present pcapStego, a tool for creating network covert channels within .pcap files. This approach has two major advantages: it allows to prepare large datasets starting from real network traces, and it generates "replayable" conversations useful for both emulating attacks or conduct pentesting campaigns. To prove the effectiveness of the tool, we showcase the generation of network covert channels targeting IPv6 traffic, which is gaining momentum and it is expected to be a major target for future attacks.

pcapStego: A Tool for Generating Traffic Traces for Experimenting with Network Covert Channels

M Zuppelli;L Caviglione
2021

Abstract

The increasing diffusion of malware endowed with steganographic and cloaking capabilities requires tools and techniques for conducting research activities, testing real deployments and elaborating mitigation mechanisms. To investigate attacks targeting network and appliances, a core requirement concerns the availability of suitable traffic traces, which can be used to derive mathematical models for simulation or to develop machine-learning-based countermeasures. Unfortunately, the young nature of threats injecting secrets or cloaking their presence within network traffic, the high protocol- dependent nature of the various embedding processes, and privacy issues, prevent the vast diffusion of datasets to perform research. Therefore, in this paper we present pcapStego, a tool for creating network covert channels within .pcap files. This approach has two major advantages: it allows to prepare large datasets starting from real network traces, and it generates "replayable" conversations useful for both emulating attacks or conduct pentesting campaigns. To prove the effectiveness of the tool, we showcase the generation of network covert channels targeting IPv6 traffic, which is gaining momentum and it is expected to be a major target for future attacks.
2021
Istituto di Matematica Applicata e Tecnologie Informatiche - IMATI -
Inglese
3rd International Workshop on Information Security Methodology and Replication Studies congiuntamente con la 16th International Conference on Availability, Reliability and Security (ARES 2021)
https://dl.acm.org/doi/abs/10.1145/3465481.3470067
Sì, ma tipo non specificato
17-20/08/2021
All-digital (per pandemia covid-19)
covert channels
information hiding
cybersecurity
traffic generation
2
restricted
Zuppelli, M; Caviglione, L
273
info:eu-repo/semantics/conferenceObject
04 Contributo in convegno::04.01 Contributo in Atti di convegno
   Secure Intelligent Methods for Advanced RecoGnition of malware and stegomalware
   SIMARGL
   H2020
   833042
File in questo prodotto:
File Dimensione Formato  
prod_454732-doc_175406.pdf

solo utenti autorizzati

Descrizione: pcapStego: A Tool for Generating Traffic Traces for Experimenting with Network Covert Channels
Tipologia: Versione Editoriale (PDF)
Dimensione 772.92 kB
Formato Adobe PDF
772.92 kB Adobe PDF   Visualizza/Apri   Richiedi una copia
prod_454732-doc_176565.pdf

solo utenti autorizzati

Descrizione: pcapStego: A Tool for Generating Traffic Traces for Experimenting with Network Covert Channels - Published Version
Tipologia: Versione Editoriale (PDF)
Dimensione 778.36 kB
Formato Adobe PDF
778.36 kB Adobe PDF   Visualizza/Apri   Richiedi una copia

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/396902
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
  • ???jsp.display-item.citation.isi??? ND
social impact