Detecting Malicious Middleboxes In Service Function Chaining
draft-park-sfc-malicious-middlebox-00

Document Type Active Internet-Draft (individual)
Authors Canh Nguyen  , Minho Park 
Last updated 2020-12-01
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Network Working Group                                         CT. NGUYEN
Internet-Draft                                                   M. Park
Intended status: Informational                       Soongsil University
Expires: June 5, 2021                                   December 2, 2020

      Detecting Malicious Middleboxes In Service Function Chaining
                 draft-park-sfc-malicious-middlebox-00

Abstract

   This document addresses problems caused by malicious middleboxes and
   proposes a scheme that can detect them in Service Function Chaining
   (SFC) by combining two mechanisms: direct and indirect.  The direct
   mechanism injects a tool into the middleboxes to observe and report
   the state of each middlebox.  In contrast, the indirect mechanism
   creates a probe service chain, which includes trustful middleboxes,
   to investigate the operation of other middleboxes in the network.

Status of This Memo

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   This Internet-Draft will expire on June 5, 2021.

Copyright Notice

   Copyright (c) 2020 IETF Trust and the persons identified as the
   document authors.  All rights reserved.

   This document is subject to BCP 78 and the IETF Trust's Legal
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   include Simplified BSD License text as described in Section 4.e of

NGUYEN  & Park            Expires June 5, 2021                  [Page 1]
Internet-Draft             malicious_middlebox             December 2020

   the Trust Legal Provisions and are provided without warranty as
   described in the Simplified BSD License.

Table of Contents

   1.  Introduction  . . . . . . . . . . . . . . . . . . . . . . . .   2
   2.  Terminology . . . . . . . . . . . . . . . . . . . . . . . . .   3
   3.  Attack Models . . . . . . . . . . . . . . . . . . . . . . . .   3
   4.  Methodology . . . . . . . . . . . . . . . . . . . . . . . . .   4
   5.  Detection Methods . . . . . . . . . . . . . . . . . . . . . .   4
     5.1.  Direct Method: Injection of Malicious Detecting Tool  . .   4
     5.2.  Indirect Method: Probe Chain Generation . . . . . . . . .   5
   6.  Informative References  . . . . . . . . . . . . . . . . . . .   5
   Appendix A.  Acknowledgements . . . . . . . . . . . . . . . . . .   6
   Authors' Addresses  . . . . . . . . . . . . . . . . . . . . . . .   6

1.  Introduction

   Service Function Chaining (SFC) creates on-demand ordered chains of
   network services (e.g., the load balancer, firewalls, and network
   address translation), and uses the chains to steer the network
   traffic to ensure that the network is agile and effective.  Service
   functions run as middleboxes, which are connected to switches in the
   network, and SFC connects these switches to create the required
   virtual chains.

   Because of the virtual attributes obtained from SDN and NFV, SFC is
   prone to encounter various security vulnerabilities, especially
   malicious middleboxes.  In particular, attackers can modify the
   service functions that run on the middlebox or inject malicious code
   into the middlebox to perform harmful actions.  Malicious middleboxes
   can create various attack types that exploit the weaknesses of both
   SDN and NFV to disrupt the operation and policy of SFC.  With respect
   to the SDN, malicious middleboxes can attack the control and data
   plane by launching distributed denial-of-service (DDoS) attacks,
   abusing computing resources, or incorrectly managing the network
   traffic.  With respect to the NFV, malicious middleboxes can attack
   the infrastructure of other middleboxes, or even user equipment or
   the network by injecting malware, spoofing or sniffing data, carrying
   out denial-of-service (DoS) attacks, misusing shared resources,
   violating the privacy and confidentiality, etc.

   Many countermeasures have been proposed to protect the network from
   these attacks, by either analyzing the network traffic or by
   installing programs in virtual machines (VMs) to collect data
   generated by the hardware to discover the attacks.  However, in the
   SFC environment, these solutions still have limitations and
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