Internet DRAFT - draft-fink-coin-sec-priv


COINRG                                                           I. Fink
Internet-Draft                                                 K. Wehrle
Intended status: Informational                    RWTH Aachen University
Expires: September 10, 2020                                March 9, 2020

        Enhancing Security and Privacy with In-Network Computing


   With the growing interconnection of devices, cyber-security and data
   protection are of increasing importance.  This is especially the case
   regarding cyber-physical systems due to their close entanglement with
   the physical world.  Misbehavior and information leakage can lead to
   financial and physical damage and endanger human lives and well-
   being.  Thus, hard security and privacy requirements are necessary to
   be met.  Furthermore, thorough investigation of incidents is
   essential for ultimate protection.  In-network computing allows the
   processing of traffic and data directly in the network and at line-
   rate.  Thus, the in-network computing paradigm presents a promising
   solution for efficiently providing security and privacy mechanisms as
   well as event analysis.  This document discusses select mechanisms to
   demonstrate how in-network computing concepts can be applied to
   encounter current shortcomings of cyber-security and data privacy.

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   document authors.  All rights reserved.

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Table of Contents

   1.  Introduction  . . . . . . . . . . . . . . . . . . . . . . . .   2
   2.  Protection Mechanisms . . . . . . . . . . . . . . . . . . . .   3
     2.1.  Encryption and Integrity Checking . . . . . . . . . . . .   4
     2.2.  Authorization and Authentication  . . . . . . . . . . . .   4
     2.3.  Behavioral and Enterprise Policies  . . . . . . . . . . .   5
     2.4.  Anonymization . . . . . . . . . . . . . . . . . . . . . .   6
   3.  Intrusion and Anomaly Detection . . . . . . . . . . . . . . .   7
     3.1.  Intrusion Detection . . . . . . . . . . . . . . . . . . .   7
     3.2.  Dead man's switch . . . . . . . . . . . . . . . . . . . .   7
   4.  Incident Reappraisal  . . . . . . . . . . . . . . . . . . . .   8
   5.  Security Considerations . . . . . . . . . . . . . . . . . . .   8
   6.  IANA Considerations . . . . . . . . . . . . . . . . . . . . .   8
   7.  Conclusion  . . . . . . . . . . . . . . . . . . . . . . . . .   8
   8.  Informative References  . . . . . . . . . . . . . . . . . . .   9
   Authors' Addresses  . . . . . . . . . . . . . . . . . . . . . . .  10

1.  Introduction

   Several deficiencies emerge from cyber-physical systems (CPS) such as
   the (Industrial) Internet of Things (IoT).  Everyday things are
   equipped with sensors and CPUs to allow for automatization and make
   life more comfortable.  The deployment of additional sensors supports
   the processing efficiency in Industrial Control Systems (ICS).  The
   entanglement of the sensors with the physical world leads to a high
   sensitivity of the transmitted and collected data.  At the same time,
   devices are increasingly connected to the Internet to enable, e.g.,
   processing of data on cloud servers or exchange with other systems.

   Devices in CPS are often resource-constrained and do not offer the
   possibility to implement elaborate security mechanisms.  Furthermore,
   legacy devices and communication protocols are often still in use in
   industrial networks but were not designed to face the security and
   privacy challenges the new interconnection brings.  Thus,
   communication and access are often unprotected, providing new attack
   surfaces with severe consequences: leakage of private data endangers
   the users' privacy.  The leakage of business secrets bears the risk

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   of severe financial damage.  Manipulation of ICSs can lead to
   downtimes in the best case or, financially worse, faulty production
   results.  Last, the failure of CPS can lead to personal injury or
   even death.  As a consequence of the described risks, we need
   security and privacy measures tailored to the new situation.
   Upgrading legacy devices with protection mechanisms is an effortful
   and expensive procedure.  A promising approach for retrofitting
   security nevertheless is the deployment of suitable mechanisms within
   the network.  To date, this is mainly realized using middle-boxes,
   leading to overhead and need for additional hardware.

   While proper prevention and detection of attacks in the (Industrial)
   IoT is an unresolved issue, the after-treatment of incidents in
   networks offers room for improvement in general.  We can use network
   forensics to retrace and comprehend the origin and course of
   malicious events.  However, realization requires high effort and
   costs in traditional networks.

   The common problem of all shortcomings is that traditional networking
   devices only allow for fixed-function deployment.  Software-defined
   networking (SDN) enables more flexible traffic handling in the
   network by separating control and data plane.  However, the use of
   fixed-function switches still restricts primary approaches like
   OpenFlow.  Those switches match traffic against a fixed set of
   protocol headers to decide if and where it should be forwarded.
   Furthermore, consultation of the remote control plane leads to
   communication overhead and delays, which is especially unfavorable in
   the context of time-sensitive applications, e.g., in industry.

   INC, in contrast, covers the shortfalls of traditional networks and
   SDN by allowing actual programming of the switches.  This
   programmability leads to dynamic and custom processing of network
   packets at line-rate.  Thus, security-related functions and packet
   inspection can be implemented and applied right at the switch.

   This draft explores the opportunities of INC for improving security
   and privacy as follows: we first describe feasible mechanisms for
   preventing attacks and intrusion in the first place.  Then, we
   present which mechanisms we can implement with INC for detecting
   intrusion and undesired behavior when it has already taken place.
   Last, we explore how INC can improve network forensics for analyzing
   and following up incidents, which helps to prevent future attacks.

2.  Protection Mechanisms

   The common ground for providing security and data privacy is to
   protect against unauthorized access.  That protection is primarily
   provided by deploying the basic security mechanisms encryption,

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   integrity checking, authentication, and authorization.  Those are
   especially often missing in resource-constrained environments.
   [RFC7744] thoroughly discusses the need for authentication and
   authorization in resource-restrained environments.  [RFC8576]
   presents security and privacy risks and challenges specific to the
   IoT.  In the following, we describe how INC can help to retrofit
   suitable mechanisms.

2.1.  Encryption and Integrity Checking

   Encryption is critical to preserve confidentiality when transmitting
   data.  Integrity checks prevent undetected manipulation, which can
   remain unnoticed even despite encryption, e.g., in case of flipped
   bits.  Due to resource-constraints, many devices in CPS do not
   provide encryption or calculation of check-sums.

   Complex cryptography is not supported by current programmable
   switches either.  However, this might change in the future, which
   would allow retrofitting encryption and integrity checks at
   networking devices.  Concretely, using INC with suitable hardware,
   data could be encrypted and supplemented with a check-sum directly at
   the first networking device passed by the respective data packet.
   The packet is then forwarded through the network or Internet to its
   designated destination.  Decryption and integrity checks can be
   executed at the last networking device before the destination.
   Alternatively, this can be implemented at the destination if
   supported by the respective device.  This approach does not require
   deployment or forwarding to additional middleboxes.  Thus, no
   additional attack surface or processing overhead is introduced, which
   is essential for time-sensitive processes as often at hand in

   Overall, INC has the potential to help maintain confidentiality and
   integrity efficiently, and thus the availability of resource-
   constrained or legacy devices.  Questions to clarify are if and at
   which costs hardware for enabling cryptographic calculations could
   and should be embedded in future generations of programmable
   networking devices.

2.2.  Authorization and Authentication

   Authorization and authentication mechanisms are needed to avoid
   unauthorized access to devices and their manipulation in the first
   place.  With INC, networking devices can flexibly decide whether to
   forward packets, thus enforce authorization and authentication

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   One possibility for authorization is to conduct a handshake between
   the sender and networking device before starting the communication
   with the industrial device.  If not feasible in switch hardware, the
   respective calculations can be conducted in the control plane.  In
   the case of success, the sender is added to a list of authorized
   communication partners.  The decision is then enforced by the switch.
   Since authorization is only needed when starting or refreshing a
   connection, the necessity and overhead for consulting the control
   plane are limited.

   The sender can append a secret token for authentication to packets
   directed to an industrial device.  Then, the last networking device
   can authenticate the sender and forward the actual data only in case
   of success and drop it otherwise.  One possibility to avoid
   eavesdropping of the token is the use of hash chains.  Secure
   reinitialization can again be done using the control plane, which
   usually has the resources for conducting encrypted communication.

   In the case of unsuccessful authorization or authentication,
   networking devices can inform the network administrator about
   possible intrusion of the system.

   Undesired traffic can emerge even from authorized and authenticated
   devices.  A solution is to add policy-based access control, on which
   we elaborate in the next subsection.

2.3.  Behavioral and Enterprise Policies

   Control processes can include communication between various parties.
   Even despite authorization and authentication mechanisms, undesired
   behavior can occur.  For instance, malicious third-party software
   might be installed at the approved device.  Regarding communication
   between two legacy devices, authentication might not be possible at
   all.  An effective way to exclude malicious behavior nevertheless is
   policy-based access control.

   [RFC8520] proposes the Manufacturer Usage Description (MUD), a
   standard for defining the communication behavior of IoT devices,
   which use specific communication patterns.  The definition is
   primarily based on domain names, ports, and use of protocols (e.g.,
   TCP and UDP).  Further characteristics as the TLS usage
   [I-D.draft-reddy-opsawg-mud-tls-03] or the required bandwidth of a
   device [I-D.draft-lear-opsawg-mud-bw-profile-01] can help to define
   connections more narrowly.

   By defining the typical behavior, we can exclude deviating
   communication, including undesired behavior.  Likewise to IoT
   devices, industrial devices usually serve a specific purpose.  Thus,

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   the application of MUD or similar policies is possible in industrial
   scenarios as well.

   The problem that remains to date is the efficient enforcement of such
   policies in the form of fine-granular and flexible traffic filtering.
   While middle-boxes increase costs and processing overhead, primary
   SDN approaches as OpenFlow allow only filtering based on match-action
   rules regarding fixed protocol header fields.  Evaluation of traffic
   statistics for, e.g., limiting the bandwidth, requires consultation
   of the remote controller.  This leads to latency overheads, which are
   not acceptable in time-sensitive scenarios.

   In contrast, the INC paradigm allows flexible filtering even
   concerning the content of packets and connection metadata.
   Furthermore, traffic filtering can be executed at line-rate in the

   Going one step further, not only network communication behavior of
   devices can be defined in policies.  As [KANG] shows, INC can be used
   to consider additional (contextual) parameters, e.g., the time of day
   or activity of other devices in the network.  Furthermore, companies
   can define advanced policies to, e.g., authorize specific users or

   Additional protection of data is needed to preserve business secrets
   and the privacy of individuals.  We show in the following subsection
   how INC can contribute to data anonymization.

2.4.  Anonymization

   Due to its interconnection with the physical world, the generation of
   sensitive data is inherent to CPS.  Smart infrastructure leads to the
   collection of sensitive user data.  In industrial networks,
   information about confidential processes is gathered.  Such data is
   increasingly shared with other entities to increase production
   efficiency or enable automatic processing.

   Despite the benefits of data exchange, manufacturers, as well as
   individuals, might not want to share sensitive information.  Again,
   deployment of privacy mechanisms is usually not possible at resource-
   constrained or legacy devices.  INC has the potential to flexibly
   apply privacy mechanisms at line-rate.

   Data can be pseudonymized at networking devices by, e.g., extracting
   and replacing specific values.  Furthermore, elaborate anonymization
   techniques can be implemented in the network by sensibly decreasing
   the data accuracy.  For example, concepts like k-Anonymity can be
   applied by aggregating the values of multiple packets before

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   forwarding the result.  Noise addition can be implemented by adding a
   random number to values.  Similarly, the state-of-the-art technique
   differential privacy can be implemented by adding noise to responses
   to statistical requests.

   Even though the INC paradigm shows the potential to deploy described
   privacy mechanisms within the network, research is needed to clarify
   the feasibility of the proposed concepts.

3.  Intrusion and Anomaly Detection

   Ideally, attacks are prevented from the outset.  However, in the case
   of incidents, fast detection is critical for limiting damage.
   Deployment of sensors, e.g., in industrial control systems, can help
   to monitor the system state and detect anomalies.  This can be used
   in combination with INC to detect intrusion as well as to provide
   advanced safety measures, as described in the following.

3.1.  Intrusion Detection

   Data of sensors or communication behavior can be compared against
   expected patterns to detect intrusion.  Even if intrusion prevention
   is deployed and connections are allowed when taken individually,
   subtle attacks might still be possible.  In this case, e.g., a series
   of values might be again out of line if considered at large.  Anomaly
   detection can be used to detect such abnormalities and notify the
   network administrator for further assessment.

   While anomaly detection is usually outsourced to middleboxes or
   external servers, INC provides the possibility to detect anomalies
   at-line rate, e.g., by maintaining statistics about traffic flows.
   This decreases costs and latency, which is valuable for a prompt

   Besides intrusion, anomalies can also imply safety risks.  In the
   following, we pick up the potential of INC to support safety.

3.2.  Dead man's switch

   [I-D.draft-kunze-coin-industrial-use-cases-01] addresses the
   potential of INC for improving industrial safety.  Detection of an
   anomaly in the sensor data or operational flow can be used to
   automatically trigger an emergency shutdown of a system or single
   components if the data indicates an actual hazard.  Apart from that,
   other safety measures like warning systems or isolation of areas can
   be implemented.  While we do not aim at replacing traditional dead
   man's switches, we see the potential of INC to accelerate the

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   detection of failures.  Thus, INC can valuably complement existing
   safety measures.

4.  Incident Reappraisal

   After the detection and treatment of an incident, it is important to
   conduct Network Forensics to investigate the origin and spreading of
   the related activity.  The results of this analysis can be used to
   adapt protection mechanisms and prevent similar events in the future.
   For enabling potential investigation, traffic records are constantly
   collected for each flow in a network.  This requires additional
   hardware in traditional networks.  Furthermore, it might be
   preferable to exclude, e.g., specific subnets from the analysis.
   This is not possible with traditional networking devices, leading to
   storage and processing overhead.

   With INC, flow records can be created directly at the switch when
   forwarding a packet.  Furthermore, record generation can be done more
   flexibly, e.g., by applying fine-granular traffic filtering.  Also,
   header fields of particular interest can be efficiently extracted.
   Therefore, INC can considerably decrease the load and increase the
   efficiency of network forensics.  This leads in turn to a better
   understanding of attacks and security.

5.  Security Considerations

   When implementing security and privacy measures in networking
   devices, security and failure resistance of the networking devices
   themselves is critical.  Related research questions to clarify in the
   future are stated in [I-D.draft-kutscher-coinrg-dir-01].

6.  IANA Considerations


7.  Conclusion

   In-network computing has the potential to improve and retrofit
   security and privacy, especially in concern of resource-restrained
   and legacy devices.

   First, INC can provide intrusion prevention mechanisms like
   authentication and efficient enforcement of (context-based) policies.
   Encryption and integrity checks are limited by the current hardware
   but might be realizable in the future.

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   Second, INC allows examining packet contents at networking devices,
   which can be used to implement fast anomaly and intrusion detection
   in the network.

   Last, INC can contribute to an efficient and targeted incident

   Investigation of the feasibility of the presented mechanisms is
   subject to future research.

8.  Informative References

              Kunze, I. and K. Wehrle, "Industrial Use Cases for In-
              Network Computing", draft-kunze-coin-industrial-use-
              cases-01 (work in progress), November 2019.

              Kutscher, D., Karkkainen, T., and J. Ott, "Directions for
              Computing in the Network", draft-kutscher-coinrg-dir-01
              (work in progress), November 2019.

              Lear, E. and O. Friel, "Bandwidth Profiling Extensions for
              MUD", draft-lear-opsawg-mud-bw-profile-01 (work in
              progress), July 2019.

              Reddy, T., Wing, D., and B. Anderson, "MUD (D)TLS profiles
              for IoT devices", draft-reddy-opsawg-mud-tls-03 (work in
              progress), January 2019.

   [KANG]     Kang, Q., Morrison, A., Tang, Y., Chen, A., and X. Luo,
              "Programmable In-Network Security for Context-aware BYOD
              Policies", In Proceedings of the 29th USENIX Security
              Symposium (USENIX Security 20), August 2020,

   [RFC7744]  Seitz, L., Ed., Gerdes, S., Ed., Selander, G., Mani, M.,
              and S. Kumar, "Use Cases for Authentication and
              Authorization in Constrained Environments", RFC 7744,
              DOI 10.17487/RFC7744, January 2016,

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   [RFC8520]  Lear, E., Droms, R., and D. Romascanu, "Manufacturer Usage
              Description Specification", RFC 8520,
              DOI 10.17487/RFC8520, March 2019,

   [RFC8576]  Garcia-Morchon, O., Kumar, S., and M. Sethi, "Internet of
              Things (IoT) Security: State of the Art and Challenges",
              RFC 8576, DOI 10.17487/RFC8576, April 2019,

Authors' Addresses

   Ina Berenice Fink
   RWTH Aachen University
   Ahornstr. 55
   Aachen  D-52062

   Phone: +49-241-80-21419

   Klaus Wehrle
   RWTH Aachen University
   Ahornstr. 55
   Aachen  D-52062

   Phone: +49-241-80-21401

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