Internet Engineering Task Force (IETF)                   N. Rozen-Schiff
Request for Comments: 9523                                      D. Dolev
Category: Informational                   Hebrew University of Jerusalem
ISSN: 2070-1721                                               T. Mizrahi
                                       Huawei Network.IO Innovation Lab
                                                            M. Schapira
                                         Hebrew University of Jerusalem
                                                          February 2024


A Secure Selection and Filtering Mechanism for the Network Time Protocol
                             with Khronos

Abstract

  The Network Time Protocol version 4 (NTPv4), as defined in RFC 5905,
  is the mechanism used by NTP clients to synchronize with NTP servers
  across the Internet.  This document describes a companion application
  to the NTPv4 client, named "Khronos", that is used as a "watchdog"
  alongside NTPv4 and that provides improved security against time-
  shifting attacks.  Khronos involves changes to the NTP client's
  system process only.  Since it does not affect the wire protocol, the
  Khronos mechanism is applicable to current and future time protocols.

Status of This Memo

  This document is not an Internet Standards Track specification; it is
  published for informational purposes.

  This document is a product of the Internet Engineering Task Force
  (IETF).  It represents the consensus of the IETF community.  It has
  received public review and has been approved for publication by the
  Internet Engineering Steering Group (IESG).  Not all documents
  approved by the IESG are candidates for any level of Internet
  Standard; see Section 2 of RFC 7841.

  Information about the current status of this document, any errata,
  and how to provide feedback on it may be obtained at
  https://www.rfc-editor.org/info/rfc9523.

Copyright Notice

  Copyright (c) 2024 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
  Provisions Relating to IETF Documents
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  publication of this document.  Please review these documents
  carefully, as they describe your rights and restrictions with respect
  to this document.  Code Components extracted from this document must
  include Revised BSD License text as described in Section 4.e of the
  Trust Legal Provisions and are provided without warranty as described
  in the Revised BSD License.

Table of Contents

  1.  Introduction
  2.  Conventions Used in This Document
    2.1.  Terms and Abbreviations
    2.2.  Notations
  3.  Khronos Design
    3.1.  Khronos Calibration - Gathering the Khronos Pool
    3.2.  Khronos's Poll and System Processes
    3.3.  Khronos's Recommended Parameters
  4.  Operational Considerations
    4.1.  Load Considerations
  5.  Security Considerations
    5.1.  Threat Model
    5.2.  Attack Detection
    5.3.  Security Analysis Overview
  6.  Khronos Pseudocode
  7.  Precision vs. Security
  8.  IANA Considerations
  9.  References
    9.1.  Normative References
    9.2.  Informative References
  Acknowledgements
  Authors' Addresses

1.  Introduction

  NTPv4, as defined in [RFC5905], is vulnerable to time-shifting
  attacks in which the attacker changes (shifts) the clock of a network
  device.  Time-shifting attacks on NTP clients can be based on
  interfering with the communication between the NTP clients and
  servers or compromising the servers themselves.  Time-shifting
  attacks on NTP are possible even if NTP communication is encrypted
  and authenticated.  A weaker machine-in-the-middle (MITM) attacker
  can shift time simply by dropping or delaying packets, whereas a
  powerful attacker that has full control over an NTP server can do so
  by explicitly determining the NTP response content.  This document
  introduces a time-shifting mitigation mechanism called "Khronos".
  Khronos can be integrated as a background-monitoring application
  (watchdog) that guards against time-shifting attacks in any NTP
  client.  An NTP client that runs Khronos is interoperable with NTPv4
  servers that are compatible with [RFC5905].  The Khronos mechanism
  does not affect the wire mechanism; therefore, it is applicable to
  any current or future time protocol.

  Khronos is a mechanism that runs in the background, continuously
  monitoring the client clock (which is updated by NTPv4) and
  calculating an estimated offset (referred to as the "Khronos time
  offset").  When the offset exceeds a predefined threshold (specified
  in Section 5.2), this is interpreted as the client experiencing a
  time-shifting attack.  In this case, Khronos updates the client's
  clock.

  When the client is not under attack, Khronos is passive.  This allows
  NTPv4 to control the client's clock and provides the ordinary high
  precision and accuracy of NTPv4.  When under attack, Khronos takes
  control of the client's clock, mitigating the time shift while
  guaranteeing relatively high accuracy with respect to UTC and
  precision, as discussed in Section 7.

  By leveraging techniques from distributed computing theory for time
  synchronization, Khronos achieves accurate time even in the presence
  of powerful attackers who are in direct control of a large number of
  NTP servers.  Khronos will prevent shifting the clock when the ratio
  of compromised time samples is below 2/3.  In each polling interval,
  a Khronos client randomly selects and samples a few NTP servers out
  of a local pool of hundreds of servers.  Khronos is carefully
  engineered to minimize the load on NTP servers and the communication
  overhead.  In contrast, NTPv4 employs an algorithm that typically
  relies on a small subset of the NTP server pool (e.g., four servers)
  for time synchronization and is much more vulnerable to time-shifting
  attacks.  Configuring NTPv4 to use several hundreds of servers will
  increase its security, but will incur very high network and
  computational overhead compared to Khronos and will be bounded by a
  compromised ratio of half of the time samples.

  A Khronos client iteratively "crowdsources" time queries across NTP
  servers and applies a provably secure algorithm for eliminating
  "suspicious" responses and for averaging over the remaining
  responses.  In each Khronos poll interval, the Khronos client
  selects, uniformly at random, a small subset (e.g., 10-15 servers) of
  a large server pool (containing hundreds of servers).  While Khronos
  queries around three times more servers per polling interval than
  NTP, Khronos's polling interval can be longer (e.g., 10 times longer)
  than NTPv4, thereby minimizing the load on NTP servers and the
  communication overhead.  Moreover, Khronos's random server selection
  may even help to distribute queries across the whole pool.

  Khronos's security was evaluated both theoretically and
  experimentally with a prototype implementation.  According to this
  security analysis, if a local Khronos pool consists of, for example,
  500 servers, one-seventh of whom are controlled by an attacker and
  Khronos queries 15 servers in each Khronos poll interval (around 10
  times the NTPv4 poll interval), then over 20 years of effort are
  required (in expectation) to successfully shift time at a Khronos
  client by over 100 ms from UTC.  The full exposition of the formal
  analysis of this guarantee is available at [Khronos].

  Khronos maintains a time offset value (the Khronos time offset) and
  uses it as a reference for detecting attacks.  This time offset value
  computation differs from the current NTPv4 in two key aspects:

  *  First, in each Khronos poll interval, Khronos periodically
     communicates with only a few (tens) randomly selected servers out
     of a pool consisting of a large number (e.g., hundreds) of NTP
     servers.

  *  Second, Khronos computes the Khronos time offset based on an
     approximate agreement technique to remove outliers, thus limiting
     the attacker's ability to contaminate the time samples (offsets)
     derived from the queried NTP servers.

  These two aspects allow Khronos to minimize the load on the NTP
  servers and to provide provable security guarantees against both MITM
  attackers and attackers capable of compromising a large number of NTP
  servers.

  We note that, to some extent, Network Time Security (NTS) [RFC8915]
  could make it more challenging for attackers to perform MITM attacks,
  but is of little impact if the servers themselves are compromised.

2.  Conventions Used in This Document

2.1.  Terms and Abbreviations

  NTPv4:  Network Time Protocol version 4.  See [RFC5905].

  System process:  See the "Selection Algorithm" and the "Cluster
     Algorithm" sections of [RFC5905].

  Security Requirements:  See "Security Requirements of Time Protocols
     in Packet Switched Networks" [RFC7384].

  NTS:  Network Time Security.  See "Network Time Security for the
     Network Time Protocol" [RFC8915].

2.2.  Notations

  When describing the Khronos algorithm, the following notation is
  used:

    +==========+====================================================+
    | Notation | Meaning                                            |
    +==========+====================================================+
    |    n     | The number of candidate servers in a Khronos pool  |
    |          | (potentially hundreds).                            |
    +----------+----------------------------------------------------+
    |    m     | The number of servers that Khronos queries in each |
    |          | poll interval (up to tens).                        |
    +----------+----------------------------------------------------+
    |    w     | An upper bound on the distance between any         |
    |          | "truechimer" NTP server (as in [RFC5905]) and UTC. |
    +----------+----------------------------------------------------+
    |    B     | An upper bound on the client's clock error rate    |
    |          | (ms/sec).                                          |
    +----------+----------------------------------------------------+
    |   ERR    | An upper bound on the client's clock error between |
    |          | Khronos polls (ms).                                |
    +----------+----------------------------------------------------+
    |    K     | The number of Khronos pool resamplings until       |
    |          | reaching "panic mode".                             |
    +----------+----------------------------------------------------+
    |    H     | Predefined threshold for a Khronos time offset     |
    |          | triggering clock update by Khronos.                |
    +----------+----------------------------------------------------+

                        Table 1: Khronos Notation


  The recommended values are discussed in Section 3.3.

3.  Khronos Design

  Khronos periodically queries a set of m (tens) servers from a large
  (hundreds) server pool in each Khronos poll interval, where the m
  servers are selected from the server pool at random.  Based on
  empirical analyses, to minimize the load on NTP servers while
  providing high security, the Khronos poll interval should be around
  10 times the NTPv4 poll interval (i.e., a Khronos clock update occurs
  once every 10 NTPv4 clock updates).  In each Khronos poll interval,
  if the Khronos time offset exceeds a predetermined threshold (denoted
  as H), an attack is indicated.

  Unless an attack is indicated, Khronos uses only one sample from each
  server (avoiding the "Clock Filter Algorithm" as defined in
  Section 10 of [RFC5905]).  When under attack, Khronos uses several
  samples from each server and executes the "Clock Filter Algorithm"
  for choosing the best sample from each server with low jitter.  Then,
  given a sample from each server, Khronos discards outliers by
  executing the procedure described in Section 3.2.

  Between consecutive Khronos polls, Khronos keeps track of clock
  offsets, e.g., by catching clock discipline (as in [RFC5905]) calls.
  The sum of offsets is referred to as the "Khronos inter-poll offset"
  (denoted as tk), which is set to zero after each Khronos poll.

3.1.  Khronos Calibration - Gathering the Khronos Pool

  Calibration is performed the first time Khronos is executed and
  periodically thereafter (once every two weeks).  The calibration
  process generates a local Khronos pool of n (up to hundreds) NTP
  servers that the client can synchronize with.  To this end, Khronos
  makes multiple DNS queries to the NTP pools.  Each query returns a
  few NTP server IPs that Khronos combines into one set of IPs
  considered as the Khronos pool.  The servers in the Khronos pool
  should be scattered across different regions to make it harder for an
  attacker to compromise or gain MITM capabilities with respect to a
  large fraction of the Khronos pool.  Therefore, Khronos calibration
  queries general NTP server pools (e.g., pool.ntp.org) and not just
  the pool in the client's state or region.  In addition, servers can
  be selected to be part of the Khronos pool manually or by using other
  NTP pools (such as NIST Internet time servers).

  The first Khronos update requires m servers, which can be found in
  several minutes.  Moreover, it is possible to query several DNS pool
  names to vastly accelerate the calibration and the first update.

  The calibration is the only Khronos part where DNS traffic is
  generated.  Around 125 DNS queries are required by Khronos to obtain
  addresses of 500 NTP servers, which is higher than Khronos pool size
  (n).  Assuming the calibration period is two weeks, the expected DNS
  traffic generated by the Khronos client is less than 10 DNS queries
  per day, which is usually several orders of magnitude lower than the
  total daily number of DNS queries per machine.

3.2.  Khronos's Poll and System Processes

  In each Khronos poll interval, the Khronos system process randomly
  chooses a set of m (tens) servers out of the Khronos pool of n
  (hundreds) servers and samples them.  Note that the randomness of the
  server selection is crucial for the security of the scheme;
  therefore, any Khronos implementation must use a secure randomness
  implementation such as what is used for encryption key generation.

  Khronos's polling times of different servers may spread uniformly
  within its poll interval, which is similar to NTPv4.  Servers that do
  not respond during the Khronos poll interval are filtered out.  If
  less than one-third of the m servers are left, a new subset of
  servers is immediately sampled in the exact same manner (which is
  called the "resampling" process).

  Next, out of the time samples received from this chosen subset of
  servers, the lowest third of the samples' offset values and the
  highest third of the samples' offset values are discarded.

  Khronos checks that the following two conditions hold for the
  remaining sampled offsets (considering w and ERR defined in Table 1):

  *  The maximal distance between every two offsets does not exceed 2w
     (can be verified by considering just the minimum and the maximum
     offsets).

  *  The distance between the offset's average and the Khronos inter-
     poll offset is ERR+2w at most.

  In the event that both of these conditions are satisfied, the average
  of the offsets is set to be the Khronos time offset.  Otherwise,
  resampling is performed.  This process spreads the Khronos client's
  queries across servers, thereby improving security against powerful
  attackers (as discussed in Section 5.3) and mitigating the effect of
  a DoS attack on NTP servers that renders them non-responsive.  This
  resampling process continues in subsequent Khronos poll intervals
  until the two conditions are both satisfied or the number of times
  the servers are resampled exceeds a "panic trigger" (K in Table 1).
  In this case, Khronos enters panic mode.

  In panic mode, Khronos queries all the servers in its local Khronos
  pool, orders the collected time samples from lowest to highest, and
  eliminates the lowest third and the highest third of the samples.
  The client then calculates the average of the remaining samples and
  sets this average to be the new Khronos time offset.

  If the Khronos time offset exceeds a predetermined threshold (H), it
  is passed on to the clock discipline algorithm in order to steer the
  system time (as in [RFC5905]).  In this case, the user and/or admin
  of the client machine should be notified about the detected time-
  shifting attack, e.g., by a message written to a relevant event log
  or displayed on screen.

  Note that resampling immediately follows the previous sampling since
  waiting until the next polling interval may increase the time shift
  in face of an attack.  This shouldn't generate high overhead since
  the number of resamples is bounded by K (after K resamplings, panic
  mode is in place) and the chances of ending up with repeated
  resampling are low (see Section 5 for more details).  Moreover, in an
  interval following a panic mode, Khronos executes the same system
  process that starts by querying only m servers (regardless of
  previous panic).

3.3.  Khronos's Recommended Parameters

  According to empirical observations (presented in [Khronos]),
  querying 15 servers at each poll interval (i.e., m=15) out of 500
  servers (i.e., n=500) and setting w to be around 25 ms provides both
  high time accuracy and good security.  Specifically, when selecting
  w=25 ms, approximately 83% of the servers' clocks are, at most, w
  away from UTC and within 2w from each other, satisfying the first
  condition of Khronos's system process.  For a similar reason, the
  threshold for a Khronos time offset triggering a clock update by
  Khronos (H) should be between w and 2w; the default is 30 ms.  Note
  that in order to support scenarios with congested links, using a
  higher w value, such as 1 second, is recommended.

  Furthermore, according to Khronos security analysis, setting K to be
  3 (i.e., if the two conditions are not satisfied after three
  resamplings, then Khronos enters panic mode) is safe when facing
  time-shifting attacks.  In addition, the probability of an attacker
  forcing a panic mode on a client when K=3 is negligible (less than
  0.000002 for each polling interval).

  Khronos's effect on precision and accuracy are discussed in Sections
  5 and 7.

4.  Operational Considerations

  Khronos is designed to defend NTP clients from time-shifting attacks
  while using public NTP servers.  As such, Khronos is not applicable
  for data centers and enterprises that synchronize with local atomic
  clocks, GPS devices, or a dedicated NTP server (e.g., due to
  regulations).

  Khronos can be used for devices that require and depend upon
  timekeeping within a configurable constant distance from UTC.

4.1.  Load Considerations

  One requirement from Khronos is not to induce excessive load on NTP
  servers beyond that of NTPv4, even if it is widely integrated into
  NTP clients.  We discuss below the possible causes for a Khronos-
  induced load on servers and how this can be mitigated.

  Servers in pool.ntp.org are weighted differently by the NTP server
  pool when assigned to NTP clients.  Specifically, server owners
  define a "server weight" (the "netspeed" parameter) and servers are
  assigned to clients probabilistically according to their proportional
  weight.  Khronos's queries are equally distributed across a pool of
  servers.  To avoid overloading servers, Khronos queries servers less
  frequently than NTPv4, with the Khronos query interval set to 10
  times the default NTPv4 maxpoll (interval) parameter.  Hence, if
  Khronos queries are targeted at servers in pool.ntp.org, any target
  increase in server load (in terms of multiplicative increase in
  queries or number of bytes per second) is controlled by the poll
  interval configuration, which was analyzed in [Ananke].

  Consider the scenario where an attacker attempts to generate
  significant load on NTP servers by triggering multiple consecutive
  panic modes at multiple NTP clients.  We note that to accomplish
  this, the attacker must have MITM capabilities with respect to the
  communication between each and every client in a large group of
  clients and a large fraction of all NTP servers in the queried pool.
  This implies that the attacker must either be physically located at a
  central location (e.g., at the egress of a large ISP) or launch a
  wide-scale attack (e.g., on BGP or DNS); thereby, it is capable of
  carrying similar and even higher impact attacks regardless of Khronos
  clients.

5.  Security Considerations

5.1.  Threat Model

  The threat model encompasses a broad spectrum of attackers impacting
  a subset (e.g., one-third) of the servers in NTP pools.  These
  attackers can range from a fairly weak (yet dangerous) MITM attacker
  that is only capable of delaying and dropping packets (e.g., using
  the Bufferbloat attack [RFC8033]) to an extremely powerful attacker
  who is in control of (even authenticated) NTP servers and is capable
  of fully determining the values of the time samples returned by these
  NTP servers (see detailed attacker discussion in [RFC7384]).

  For example, the attackers covered by this model might be:

  1.  in direct control of a fraction of the NTP servers (e.g., by
      exploiting a software vulnerability),

  2.  an ISP (or other attacker at the Autonomous System level) on the
      default BGP paths from the NTP client to a fraction of the
      available servers,

  3.  a nation state with authority over the owners of NTP servers in
      its jurisdiction, or

  4.  an attacker capable of hijacking (e.g., through DNS cache
      poisoning or BGP prefix hijacking) traffic to some of the
      available NTP servers.

  The details of the specific attack scenario are abstracted by
  reasoning about attackers in terms of the fraction of servers with
  respect to which the attacker has adversarial capabilities.
  Attackers that can impact communications with (or control) a higher
  fraction of the servers (e.g., all servers) are out of scope.
  Considering the pool size across the world to be in the thousands,
  such attackers will most likely be capable of creating far worse
  damage than time-shifting attacks.

  Notably, Khronos provides protection from MITM and powerful attacks
  that cannot be achieved by cryptographic authentication protocols
  since, even with such measures in place, an attacker can still
  influence time by dropping/delaying packets.  However, adding an
  authentication layer (e.g., NTS [RFC8915]) to Khronos will enhance
  its security guarantees and enable the detection of various spoofing
  and modification attacks.

  Moreover, Khronos uses randomness to independently select the queried
  servers in each poll interval, preventing attackers from exploiting
  observations of past server selections.

5.2.  Attack Detection

  Khronos detects time-shifting attacks by constantly monitoring
  NTPv4's (or potentially any other current or future time protocol)
  clock and the offset computed by Khronos and checking whether the
  offset exceeds a predetermined threshold (H).  NTPv4 controls the
  client's clock unless an attack was detected.  Under attack, Khronos
  takes control over the client's clock in order to prevent its shift.

  Analytical results (in [Khronos]) indicate that if a local Khronos
  pool consists of 500 servers, one-seventh of whom are controlled by a
  MITM attacker, and 15 of those servers are queried in each Khronos
  poll interval, then success in shifting time of a Khronos client by
  even a small degree (100 ms) takes many years of effort (over 20
  years in expectation).  See a brief overview of Khronos's security
  analysis below.

5.3.  Security Analysis Overview

  Time samples that are at most w away from UTC are considered "good",
  whereas other samples are considered "malicious".  Two scenarios are
  considered:

  *  Scenario A: Less than two-thirds of the queried servers are under
     the attacker's control.

  *  Scenario B: The attacker controls more than two-thirds of the
     queried servers.

  Scenario A consists of two sub-cases:

  1.  There is at least one good sample in the set of samples not
      eliminated by Khronos (in the middle third of samples), and

  2.  there are no good samples in the remaining set of samples.

  In sub-case 1, the other remaining samples, including those provided
  by the attacker, must be close to a good sample (otherwise, the first
  condition of Khronos's system process in Section 3.2 is violated and
  a new set of servers is chosen).  This implies that the average of
  the remaining samples must be close to UTC.

  In sub-case 2, since more than a third of the initial samples were
  good, both the (discarded) third-lowest-value samples and the
  (discarded) third-highest-value samples must each contain a good
  sample.  Hence, all the remaining samples are bounded from both above
  and below by good samples, and so is their average value, implying
  that this value is close to UTC [RFC5905].

  In Scenario B, the worst possibility for the client is that all
  remaining samples are malicious (i.e., more than w away from UTC).
  However, as proved in [Khronos], the probability of this scenario is
  extremely low, even if the attacker controls a large fraction (e.g.,
  one-fourth) of the n servers in the local Khronos pool.  Therefore,
  the probability that the attacker repeatedly reaches this scenario
  decreases exponentially, rendering the probability of a significant
  time shift negligible.  We can express the improvement ratio of
  Khronos over NTPv4 by the ratios of their single-shift probabilities.
  Such ratios are provided in Table 2, where higher values indicate
  higher improvement of Khronos over NTPv4 and are also proportional to
  the expected time until a time-shift attack succeeds once.


    +========+==========+==========+==========+==========+==========+
    | Attack |    6     |    12    |    18    |    24    |    30    |
    | Ratio  | Samples  | Samples  | Samples  | Samples  | Samples  |
    +========+==========+==========+==========+==========+==========+
    |  1/3   | 1.93e+01 | 3.85e+02 | 7.66e+03 | 1.52e+05 | 3.03e+06 |
    +--------+----------+----------+----------+----------+----------+
    |  1/5   | 1.25e+01 | 1.59e+02 | 2.01e+03 | 2.54e+04 | 3.22e+05 |
    +--------+----------+----------+----------+----------+----------+
    |  1/7   | 1.13e+01 | 1.29e+02 | 1.47e+03 | 1.67e+04 | 1.90e+05 |
    +--------+----------+----------+----------+----------+----------+
    |  1/9   | 8.54e+00 | 7.32e+01 | 6.25e+02 | 5.32e+03 | 4.52e+04 |
    +--------+----------+----------+----------+----------+----------+
    |  1/10  | 5.83e+00 | 3.34e+01 | 1.89e+02 | 1.07e+03 | 6.04e+03 |
    +--------+----------+----------+----------+----------+----------+
    |  1/15  | 3.21e+00 | 9.57e+00 | 2.79e+01 | 8.05e+01 | 2.31e+02 |
    +--------+----------+----------+----------+----------+----------+

                       Table 2: Khronos Improvement


  In addition to evaluating the probability of an attacker successfully
  shifting time at the client's clock, we also evaluated the
  probability that the attacker succeeds in launching a DoS attack on
  the servers by causing many clients to enter panic mode (and querying
  all the servers in their local Khronos pools).  This probability
  (with the previous parameters of n=500, m=15, w=25, and K=3) is
  negligible even for an attacker who controls a large number of
  servers in clients' local Khronos pools, and it is expected to take
  decades to force a panic mode.

  Further details about Khronos's security guarantees can be found in
  [Khronos].

6.  Khronos Pseudocode

  The pseudocode for Khronos Time Sampling Scheme, which is invoked in
  each Khronos poll interval, is as follows:

  counter = 0
  S = []
  T = []
  While counter < K do
     S = sample(m) //get samples from (tens of) randomly chosen servers
     T = bi_side_trim(S,1/3) //trim lowest and highest thirds
     if (max(T) - min(T) <= 2w) and (|avg(T) - tk| < ERR + 2w), then
         return avg(T) // Normal case
     end
     counter ++
  end
  // panic mode
  S = sample(n)
  T = bi-sided-trim(S,1/3) //trim lowest and highest thirds
  return avg(T)

  Note that if clock disciplines can be called during this pseudocode's
  execution, then each time offset sample, as well as the final output
  (Khronos time offset), should be normalized with the sum of the clock
  disciplines offsets (tk) at the time of computing it.

7.  Precision vs. Security

  Since NTPv4 updates the clock at times when no time-shifting attacks
  are detected, the precision and accuracy of a Khronos client are the
  same as NTPv4 at these times.  Khronos is proved to maintain an
  accurate estimation of the UTC with high probability.  Therefore,
  when Khronos detects that client's clock error exceeds a threshold
  (H), it considers it to be an attack and takes control over the
  client's clock.  As a result, the time shift is mitigated and high
  accuracy is guaranteed (the error is bounded by H).

  Khronos is based on crowdsourcing across servers and regions, changes
  the set of queried servers more frequently than NTPv4 [Khronos], and
  avoids some of the filters in NTPv4's system process.  These factors
  can potentially harm its precision.  Therefore, a smoothing mechanism
  can be used where instead of a simple average of the remaining
  samples, the smallest (in absolute value) offset is used unless its
  distance from the average is higher than a predefined value.
  Preliminary experiments demonstrated promising results with precision
  similar to NTPv4.

  In applications such as multi-source media streaming, which are
  highly sensitive to time differences among hosts, note that it is
  advisable to use Khronos at all hosts in order to obtain high
  precision, even in the presence of attackers that try to shift each
  host in a different magnitude and/or direction.  Another approach
  that is more efficient for these cases may be to allow direct time
  synchronization between one host who runs Khronos to others.

8.  IANA Considerations

  This document has no IANA actions.

9.  References

9.1.  Normative References

  [RFC5905]  Mills, D., Martin, J., Ed., Burbank, J., and W. Kasch,
             "Network Time Protocol Version 4: Protocol and Algorithms
             Specification", RFC 5905, DOI 10.17487/RFC5905, June 2010,
             <https://www.rfc-editor.org/info/rfc5905>.

  [RFC7384]  Mizrahi, T., "Security Requirements of Time Protocols in
             Packet Switched Networks", RFC 7384, DOI 10.17487/RFC7384,
             October 2014, <https://www.rfc-editor.org/info/rfc7384>.

  [RFC8033]  Pan, R., Natarajan, P., Baker, F., and G. White,
             "Proportional Integral Controller Enhanced (PIE): A
             Lightweight Control Scheme to Address the Bufferbloat
             Problem", RFC 8033, DOI 10.17487/RFC8033, February 2017,
             <https://www.rfc-editor.org/info/rfc8033>.

  [RFC8915]  Franke, D., Sibold, D., Teichel, K., Dansarie, M., and R.
             Sundblad, "Network Time Security for the Network Time
             Protocol", RFC 8915, DOI 10.17487/RFC8915, September 2020,
             <https://www.rfc-editor.org/info/rfc8915>.

9.2.  Informative References

  [Ananke]   Perry, Y., Rozen-Schiff, N., and M. Schapira, "A Devil of
             a Time: How Vulnerable is NTP to Malicious Timeservers?",
             Network and Distributed Systems Security (NDSS) Symposium,
             Virtual, DOI 10.14722/ndss.2021.24302, February 2021,
             <https://www.ndss-symposium.org/wp-content/uploads/
             ndss2021_1A-2_24302_paper.pdf>.

  [Khronos]  Deutsch, O., Rozen-Schiff, N., Dolev, D., and M. Schapira,
             "Preventing (Network) Time Travel with Chronos", Network
             and Distributed Systems Security (NDSS) Symposium, San
             Diego, CA, USA, DOI 10.14722/ndss.2018.23231, February
             2018, <https://www.ndss-symposium.org/wp-
             content/uploads/2018/02/ndss2018_02A-2_Deutsch_paper.pdf>.

Acknowledgements

  The authors would like to thank Erik Kline, Miroslav Lichvar, Danny
  Mayer, Karen O'Donoghue, Dieter Sibold, Yaakov (J) Stein, Harlan
  Stenn, Hal Murray, Marcus Dansarie, Geoff Huston, Roni Even, Benjamin
  Schwartz, Tommy Pauly, Rob Sayre, Dave Hart, and Ask Bjorn Hansen for
  valuable contributions to this document and helpful discussions and
  comments.

Authors' Addresses

  Neta Rozen-Schiff
  Hebrew University of Jerusalem
  Jerusalem
  Israel
  Phone: +972 2 549 4599
  Email: [email protected]


  Danny Dolev
  Hebrew University of Jerusalem
  Jerusalem
  Israel
  Phone: +972 2 549 4588
  Email: [email protected]


  Tal Mizrahi
  Huawei Network.IO Innovation Lab
  Israel
  Email: [email protected]


  Michael Schapira
  Hebrew University of Jerusalem
  Jerusalem
  Israel
  Phone: +972 2 549 4570
  Email: [email protected]