Internet DRAFT - draft-morais-iotops-inxu
draft-morais-iotops-inxu
IOT Operations Working Group S.V. Morais
Internet-Draft IFRN
Intended status: Standards Track C.M. Farias
Expires: 27 November 2022 UFRJ
26 May 2022
Intra-Network eXposure analyzer Utility Specification
draft-morais-iotops-inxu-01
Abstract
This document proposes the Intra-Network eXposure analyzer Utility
(INXU) as a vulnerability management solution for IoT networks. The
goal of INXU is to take advantage of the functions of the RFC 8520 to
allow a Security Experts Team on protecting multiple heterogeneous
IoT networks, even when there is a few or none private information of
the networks.
INXU identifies and analyzes the capability of an IoT device being
exploited by an well known malicious activity. We also propose the
Malicious Traffic Description (MTD), a data-model to describe traffic
related to malicious activities.
Status of This Memo
This Internet-Draft is submitted in full conformance with the
provisions of BCP 78 and BCP 79.
Internet-Drafts are working documents of the Internet Engineering
Task Force (IETF). Note that other groups may also distribute
working documents as Internet-Drafts. The list of current Internet-
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Internet-Drafts are draft documents valid for a maximum of six months
and may be updated, replaced, or obsoleted by other documents at any
time. It is inappropriate to use Internet-Drafts as reference
material or to cite them other than as "work in progress."
This Internet-Draft will expire on 27 November 2022.
Copyright Notice
Copyright (c) 2022 IETF Trust and the persons identified as the
document authors. All rights reserved.
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This document is subject to BCP 78 and the IETF Trust's Legal
Provisions Relating to IETF Documents (https://trustee.ietf.org/
license-info) in effect on the date of 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
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provided without warranty as described in the Revised BSD License.
Table of Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . 3
1.1. Simple Example . . . . . . . . . . . . . . . . . . . . . 5
1.2. Key Aspects . . . . . . . . . . . . . . . . . . . . . . . 5
1.3. INXU Intended Use . . . . . . . . . . . . . . . . . . . . 5
1.4. Terminology . . . . . . . . . . . . . . . . . . . . . . . 6
2. The MTD Data Model . . . . . . . . . . . . . . . . . . . . . 7
2.1. The draft-inxu-mtd YANG Module . . . . . . . . . . . . . 8
2.2. MTD Data Model Definition of Control Fields in the Root
"mtd" Container . . . . . . . . . . . . . . . . . . . . . 10
2.2.1. mtd-url . . . . . . . . . . . . . . . . . . . . . . . 10
2.2.2. mtd-signature . . . . . . . . . . . . . . . . . . . . 10
2.2.3. last-update . . . . . . . . . . . . . . . . . . . . . 10
2.2.4. cache-validity . . . . . . . . . . . . . . . . . . . 10
2.3. MTD Data Model Definition of Traffic Description Fields in
the Root "mtd" Container . . . . . . . . . . . . . . . . 10
2.3.1. traffic-list . . . . . . . . . . . . . . . . . . . . 11
2.3.1.1. name . . . . . . . . . . . . . . . . . . . . . . 11
2.3.1.2. specific-devices . . . . . . . . . . . . . . . . 11
2.3.2. malicious-descriptions . . . . . . . . . . . . . . . 11
2.3.2.1. name . . . . . . . . . . . . . . . . . . . . . . 11
2.3.2.2. specific-devices . . . . . . . . . . . . . . . . 11
2.3.2.3. critical-acl-sets . . . . . . . . . . . . . . . . 11
2.3.2.4. to-device-attacks . . . . . . . . . . . . . . . . 12
2.3.2.5. from-device-attacks . . . . . . . . . . . . . . . 12
2.3.2.6. not-attack-traffic . . . . . . . . . . . . . . . 12
2.4. Augmentation to the ACL Model . . . . . . . . . . . . . . 12
2.4.1. mtd:local-networks . . . . . . . . . . . . . . . . . 12
2.4.2. direction-initiated . . . . . . . . . . . . . . . . . 12
2.4.3. src-dnsname and dst-dnsname . . . . . . . . . . . . . 13
2.4.4. risk . . . . . . . . . . . . . . . . . . . . . . . . 13
2.4.5. risk-threshold . . . . . . . . . . . . . . . . . . . 13
2.4.6. alert-threshold . . . . . . . . . . . . . . . . . . . 13
2.5. The MTD YANG Model . . . . . . . . . . . . . . . . . . . 13
2.6. MTD File Example . . . . . . . . . . . . . . . . . . . . 21
3. The Intra-Network eXposure analyzer Utility . . . . . . . . . 29
3.1. INXU Architecture and Components . . . . . . . . . . . . 30
3.2. Workflow . . . . . . . . . . . . . . . . . . . . . . . . 31
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3.3. Acquiring a MTD File . . . . . . . . . . . . . . . . . . 32
3.4. Processing a MTD URL . . . . . . . . . . . . . . . . . . 32
3.5. INXU Vulnerability Analysis Process . . . . . . . . . . . 32
3.5.1. Exposure Identification . . . . . . . . . . . . . . . 33
3.5.2. ACL Risk Assessment . . . . . . . . . . . . . . . . . 33
3.5.3. Threat Analysis . . . . . . . . . . . . . . . . . . . 34
4. Further Considerations and Next Steps . . . . . . . . . . . . 34
5. Security Considerations . . . . . . . . . . . . . . . . . . . 35
6. IANA Considerations . . . . . . . . . . . . . . . . . . . . . 35
7. References . . . . . . . . . . . . . . . . . . . . . . . . . 35
7.1. Normative References . . . . . . . . . . . . . . . . . . 36
7.2. Informative References . . . . . . . . . . . . . . . . . 36
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 37
1. Introduction
While more Internet of Things (IoT) devices are deployed, the
vulnerability management process turns even more difficult. This is
mostly caused by the high heterogeneity and density of the IoT
systems and devices, and challenges security teams on keeping
Firewall and Intrusion Detection/Prevention Systems (IDS/IPS) rules
up to date.
In some way, the Manufacturer Usage Description (MUD) [RFC8520]
provides an alternative protection by reducing the capability of an
IoT device being exploited -- as vector or target -- by malicious
activities over the Internet. MUD does this by providing means to
automatically build an allow-list of the IoT devices in a network
based on the device manufacturers specification of expected traffic.
This improves devices security by reducing their threat surface by
blocking traffic with unexpected nodes/protocols, but still allows
attacks which exploit vulnerabilities into the allowed traffic.
Besides this lack, the implementation of the [RFC8520] provides
information that can support the identification of well-known
vulnerabilities, as mentioned in its specification. This can be done
by combining the allow-lists provided by the MUD manager into a
communication graph of the connected IoT devices. With the
communication graph, we can compare the traffic allowed by MUD with
signatures of well-known malicious activities to identify -- and
potentially block -- exposure of vulnerabilities into the network.
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Integrating this analysis in traditional IDS or IPS can improve their
efficacy and cover the MUD lack, but they only apply for scenarios
where there is a security management team, such as corporate, smart
grid and industrial IoT networks. On the other hand, in scenarios
where there is a high heterogeneity of devices and low (or none)
specialized support, such as in Home IoT Networks and Smart Cities,
the process for keeping the attack signatures updated is not that
simple.
Therefore, envisioning to overcome this gap, this document proposes
INXU (Intra Network eXposure analyzer Utility) as a security tool
that takes advantage of the MUD-based network communication graph to
prevent the exploitation of well-known vulnerabilities. To do this,
INXU blocks threats on the Local Area Network (LAN) after identifying
them by comparing the signature of well-known malicious activities
with the traffic flow allowed by the MUD. In short words, while MUD
builds allow-lists, INXU builds a blocklist on top of MUD's allow-
lists.
The core component of INXU is Malicious Traffic Description (MTD), a
document produced by a security specialist that describes ongoing
malicious activities and well-known vulnerabilities and helps INXU
find chains of connected IoT devices that can expose them to a
threat. On top of MUD's threat surface reduction, INXU adds another
security layer that enables protection against incidents not
addressed or even caused by the manufacturers.
The MTD data model, as in MUD, abstracts network addresses to allow
describing the traffic without the need to know the network's
addressing schema or the connected devices. This resource allows
creating portable descriptions of malicious traffic and protects the
privacy in the LAN by not exposing private information to third
parties in the security decision-making process. At the same time,
it simplifies the sharing of knowledge about attacks between distinct
networks.
Another relevant feature in INXU is its architecture that enables one
Security Operation Center (SOC) to protect multiple distinct networks
by sharing MTDs in a process similar to computer antivirus vaccines.
This feature makes INXU a tool to protect LANs and the entire
Internet ecosystem by making the operation of botnets and other
attacks that affect the Internet's stability more difficult.
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1.1. Simple Example
An Internet Service Provider (ISP) connects tens to hundreds of
houses to the Internet. Each one of these homes contains a wide
range of IoT devices connected in their internal networks, in diverse
topologies, and with different usages by each end-user. By the
variety of scenarios, these home networks potentially contain a few
devices infected by a DDoS capable botnet.
Due to the attacks carried by this botnet, frequently the ISP has a
considerable part of its traffic being consumed by DDoS attacks, and
often the clients call helpdesk for problems with devices caused by
the botnet. The ISP knows that the malware's infection occurs by a
TCP/23 connection with a neighbour host, and the command and control
occurs by a TCP/80 connection with a server located at
mybotnet.example.com.
With this information, the ISP releases an MTD File describing this
traffic, which can be used by its clients. In the home networks, the
Customer Premises Equipment (CPE) collects the MTD File and compares
it to the network communication graph provided by MUD, identifies
exposures of vulnerabilities internally into the network, INXU
evaluates the risk of the exposures and suggests blocks to prevent
exploitations.
1.2. Key Aspects
This work in progress aims to propose a tool that reinforces IoT
networks' security by taking advantage of the functions provided by
the [RFC8520]. The specific contributions of INXU are listed below:
* Simplify the process of sharing attack signatures that targets or
exploits IoT systems;
* Allow a small team of security specialists to protect multiple
distinct IoT networks without expose the networks' privacy;
* Protect the Internet's ecosystem by hindering distributed attacks
that targets its infrastructure.
1.3. INXU Intended Use
The intended use for INXU is in the support of the vulnerability
management of diverse heterogeneous IoT networks in scenarios where
there is a small team of security specialists (e.g. Smart Cities).
It is also intended to be used in scenarios where the end networks
need their privacy kept, as Home IoT networks.
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The deployment of INXU in networks populated by both IoT and general
purpose devices is NOT RECOMMENDED. Due to the greater computing
power and wider openness to other attacks, general purpose devices
might expose the IoT network to unnecessary risk. Instead of having
both types on the same sub-network, we recomend to isolate IoT
devices in a separate sub-network as they announce their MUD URLs,
and developers should take advantage of MUD's "controller" and "my-
controller" hosts as application gateway between general purpose and
IoT devices. In the case of needing a direct communication between
the two categories, this could be specified with MUD's "local-
networks" specification.
1.4. Terminology
* INXU: Intra-Network eXposure analyzer Utility.
* INXU Module: a system that crosses data from malicious activities
and MUD's allow-lists to identify and analyze the exposure of
vulnerabilities in the connected IoT devices.
* MTD: Malicious Traffic Description data model.
* MTD File: a file that contains descriptions of traffic associated
with malicious activities that targets or exploits IoT devices.
* MTD Manager: a system that requests and receives the MTD File. It
is responsible for verifying MUD File's authenticity and
integrity. The MTD Manager also requests the MTD File after it's
cache validity expires.
* MTD URL: a URL, configured in the MTD Manager, that locates the
MTD File provided by the SOC in charge to protect the client
network.
* MTD Server: a web server, managed by the SOC, that hosts the MTD
File.
The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT",
"SHOULD", "SHOULD NOT", "RECOMMENDED", "NOT RECOMMENDED", "MAY", and
"OPTIONAL" in this document are to be interpreted as described in BCP
14 [RFC2119][RFC8174] when, and only when, they appear in all
capitals, as shown here.
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2. The MTD Data Model
The main aim of this data model is to enable describing malicious
traffic so that distinct networks can interpret and implement
security measures, no matter the connected IoT devices or network
topology. Another feature addressed by this data model is allowing
the association between the detected exposure and the malicious
activity that exploits it, as well as the grouping of vulnerabilities
related to the same malicious activity.
The MTD data model makes use of Access Control Lists (ACLs) [RFC8519]
under YANG language [RFC7950] to describe the malicious traffic,
addressing the classification feature. Furthermore, such as in MUD,
there are available two network address abstractions to describe the
traffic so that different networks can adapt the description to its
context: one abstraction for addresses in the local networks, and the
other for using domain names to hosts on the Internet. The data
model also includes control fields that support the manageability of
the MTD File, so the contained data can be categorized in control
data and description data.
This data model covers the complete description of malicious
activities from simple attacks with just a few ACE inputs to complex
malware that exploits many different vulnerabilities and network
resources. Furthermore, to prevent false-positive threat detections,
the MTD data model allows inserting context information into the
descriptions. The context information in the MTD data model plays
the role of specifying the correlation between the described
malicious traffic, determining the combinations of exposures that
become a risk, and suggesting the action to be taken with each
detected threat. This feature supports reducing false-positive
detection, as a single traffic exposure may not represent a threat
itself.
Basically the context information supports the categorization of a
set of vulnerabilities as an effective threat or not. To incorporate
the contextual information, we considered the statements listed
below, which were assimilated from the IoTSec ontology in
[Mozzaquatro2015]:
* A Threat represents an effective risk if the exposure of one or
more vulnerabilities can be exploited by an attacker;
* A Vulnerability does not represent a risk by itself, as it can be
hidden behind security mechanisms, such as blocking its exposure
for potential attackers.
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So, in short words, an asset is under threat only when an attacker
can exploit one or more vulnerabilities to take advantage of it.
Thus, merging the concepts from the ontology and the aims on MTD data
model, this document considers the following statements:
* Each Access Control Entry (ACE) has an associated severity defined
by the unsigned integer field named risk. When the exposure to
the ACE is detected, its risk is considered part of its ACL's
vulnerability classification;
* Each ACL has alert-threshold and risk-threshold fields, both
represented by unsigned integer values. When the sum of the
exposed ACEs risks reaches the risk threshold, the exposure to the
ACL is considered as a vulnerability;
* Each malicious activity described contains a list of critical ACL
sets. A malware or attack is classified as a threat when at least
one set of critical ACLs contains all its ACLs classified as a
vulnerability exposure. When one set's condition is satisfied,
its associated action-to-take has to be triggered.
The three possible actions to be taken are listed below:
* block-all: blocks all ACLs that expose vulnerabilities related to
the description. Expected to be used when any traffic associated
with the malware or attack threatens the IoT device;
* block-attack: blocks all ACLs that expose vulnerabilities under
the attack-traffic group. Expected to be used when only risky
ACLs associated with attacks (isolated or in the context of a
malware) threatens the IoT device;
* block-not-attack: blocks all ACLs that expose vulnerabilities
under the malware's not-attack-traffic group. Expected to be used
when just blocking the operation traffic of a malware prevents
exploitation.
2.1. The draft-inxu-mtd YANG Module
A simplified graphical representation of the data models is used in
this document. The meaning of the symbols in these diagrams is
explained in [RFC8340].
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module: draft-inxu-mtd
+--rw mtd!
+--rw mtd-url inet:uri
+--rw last-update yang:date-and-time
+--rw mtd-signature? inet:uri
+--rw cache-validity? uint8
+--rw malicious-descriptions
+--rw malicious-list* [name]
+--rw name string
+--rw specific-devices* inet:uri
+--rw critical-acl-sets* [name]
| +--rw name string
| +--rw critical-acl-set* -> /acl:acls/acl/name
| +--rw action-to-take draft-inxu-mtd:action-to-take
+--rw to-device-attacks
| +--rw traffic-lists
| +--rw traffic-list* [name]
| +--rw name -> /acl:acls/acl/name
| +--rw specific-devices* inet:uri
+--rw from-device-attacks
| +--rw traffic-lists
| +--rw traffic-list* [name]
| +--rw name -> /acl:acls/acl/name
| +--rw specific-devices* inet:uri
+--rw to-device-not-attacks
| +--rw traffic-lists
| +--rw traffic-list* [name]
| +--rw name -> /acl:acls/acl/name
| +--rw specific-devices* inet:uri
+--rw from-device-not-attacks
+--rw traffic-lists
+--rw traffic-list* [name]
+--rw name -> /acl:acls/acl/name
+--rw specific-devices* inet:uri
augment /acl:acls/acl:acl/acl:aces/acl:ace/acl:matches:
+--rw mtd
+--rw local-networks? empty
augment /acl:acls/acl:acl/acl:aces/acl:ace:
+--rw risk? uint8
augment /acl:acls/acl:acl:
+--rw risk-threshold? uint8
+--rw alert-threshold? uint8
augment /acl:acls/acl:acl/acl:aces/acl:ace/acl:matches/acl:l4/acl:tcp/
acl:tcp:
+--rw direction-initiated? mud:direction
augment /acl:acls/acl:acl/acl:aces/acl:ace/acl:matches/acl:l3/
acl:ipv4/acl:ipv4:
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+--rw src-dnsname? inet:host
+--rw dst-dnsname? inet:host
augment /acl:acls/acl:acl/acl:aces/acl:ace/acl:matches/acl:l3/
acl:ipv6/acl:ipv6:
+--rw src-dnsname? inet:host
+--rw dst-dnsname? inet:host
2.2. MTD Data Model Definition of Control Fields in the Root "mtd"
Container
Here we describe the leafs placed into the "mtd" root container that
plays the role of controlling the operation of the MTD File.
2.2.1. mtd-url
Required field that stores the URL where the security authority hosts
the MTD File.
2.2.2. mtd-signature
Optional field used to store a URL where the MTD File signature file
can be found. It is applicable for offline authenticity verification
of the file.
2.2.3. last-update
Required field that contains the timestamp information of the MTD
File generation.
2.2.4. cache-validity
Optional field that contains the number of hours to the expiration of
the MTD File, starting from "last-update". This field supports
integer values between 1 and 160, and if not defined, it is assumed
to be 48 hours by the MTD Manager.
2.3. MTD Data Model Definition of Traffic Description Fields in the
Root "mtd" Container
The traffic description fields are organized under the "malicious-
descriptions" container. The description of a malicious activity
allows the aggregation of different attacks, and also other not
attack traffic that only turn into malicious when related to the
malware operation. This aggregation is important for the security
measures decision-making process, as sometimes only a traffic
combination makes the threat effective or blocking just one type of
traffic can almost disable it, such as the Mirai's Command and
Control traffic.
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The description of each leaf is detailed in the Sub-Sections below.
2.3.1. traffic-list
List type field to specify all the traffic in the same direction
(incoming/outgoing) that is associated with one attack-traffic or
not-attack-traffic.
2.3.1.1. name
Required string field with the name of the ACL that describes one
attack-traffic or not-attack-traffic;
2.3.1.2. specific-devices
Optional list to specify the MUD URLs of the IoT devices affected by
the described traffic. When this field is filled, INXU only
considers the devices here listed as targets of these ACLs.
2.3.2. malicious-descriptions
List that holds the traffic description of all the malicious
activities covered by the MTD File.
2.3.2.1. name
Required string field to uniquely name the described malicious
activity.
2.3.2.2. specific-devices
Optional list to specify the MUD URLs of the IoT devices that can be
affected by the malicious activity. When this field is filled, INXU
only considers the devices here listed as affected by this malicious
activity.
2.3.2.3. critical-acl-sets
List to specify all the sets of critical ACL and their respective
actions to take when all listed ACLs get classified as risky.
2.3.2.3.1. critical-acl-set
List to specify a set of ACLs that, when all listed ACLs get
classified as risky, represents a threat caused by the malicious
activity.
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2.3.2.3.2. action-to-take
Mandatory leaf to specify the action to be taken when the respective
set of critical ACLs turns into a threat. The action can be "block-
all", "block-attack", or "block-not-attack".
2.3.2.4. to-device-attacks
Container that holds all the malicious activity's attack traffic
targeting an IoT device on the LAN.
2.3.2.5. from-device-attacks
Container that holds all the malicious activity's attack traffic
outgoing from an IoT device on the LAN.
2.3.2.6. not-attack-traffic
Container that holds the traffic not related to attacks, but that
turns into malicious when in this context.
2.3.2.6.1. to-device-not-attack-traffic
List with all the ACLs that describe malicious not attack traffic
targeting an IoT device on the LAN.
2.3.2.6.2. from-device-not-attack-traffic
List with all the ACLs that describe malicious not attack traffic
outgoing from an IoT device on the LAN.
2.4. Augmentation to the ACL Model
This section describes the proposed augments to the ACL model. These
augments are responsible for creating the abstraction for the traffic
descriptions, enabling the portability of the knowledge to the
different networks, and supporting the risk assessment of each
vulnerability exposure.
2.4.1. mtd:local-networks
Optional leaf that, when present, means that the current ACE applies
to any device on the local IP networks.
2.4.2. direction-initiated
Optional field incorporated from MUD to specify the TCP initiator.
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2.4.3. src-dnsname and dst-dnsname
Optional field to enable the usage of DNS domain names to specify the
remote host instead of using IPv4 or IPv6 addresses.
2.4.4. risk
Optional unsigned integer field to specify the risk associated with
the exposure of the specified ACE. Its default value is 1.
2.4.5. risk-threshold
Optional unsigned integer field to specify the minimal ACL risk value
to classify it as a vulnerability exposure. The ACL's risk value is
calculated by the sum of all its child ACE exposures' risks. Its
default value is 1.
2.4.6. alert-threshold
Optional unsigned integer field to specify the minimal ACL risk value
to trigger an alert to the exposure. The ACL's risk value is
calculated by the sum of all its child ACE exposures' risks. Its
default value is 1.
2.5. The MTD YANG Model
<CODE BEGINS>file "draft-inxu-mtd@2021-11-22.yang"
module draft-inxu-mtd{
yang-version 1.1;
namespace "urn:ietf:params:xml:ns:yang:draft-inxu-mtd";
prefix draft-inxu-mtd;
import ietf-yang-types {
prefix yang;
}
import ietf-access-control-list {
prefix acl;
}
import ietf-inet-types {
prefix inet;
}
import ietf-mud {
prefix mud;
}
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import ietf-acldns {
prefix acldns;
}
organization "IETF IOTOPS (IOT Operations) Working Group";
contact
"WG Web: http://tools.ietf.org/wg/iotops/
WG List: iotops@ietf.org
Author: Sávyo Morais
savyovm@gmail.com
Author: Claudio Farias
cmicelifarias@gmail.com";
description
"This module is a data-model to describe malicious network
traffic.
This module is intended to be serialized via JSON and stored
as a file, as described in I-D draft-morais-iotops-inxu-01.
The key words 'MUST', 'MUST NOT', 'REQUIRED', 'SHALL', 'SHALL
NOT', 'SHOULD', 'SHOULD NOT', 'RECOMMENDED', 'NOT RECOMMENDED',
'MAY', and 'OPTIONAL' in this document are to be interpreted as
described in BCP 14 (RFC 2119) (RFC 8174) when, and only when,
they appear in all capitals, as shown here.
Copyright (c) 2022 IETF Trust and the persons identified as
authors of the code. All rights reserved.
Redistribution and use in source and binary forms, with or
without modification, is permitted pursuant to, and subject
to the license terms contained in, the Simplified BSD License
set forth in Section 4.c of the IETF Trust's Legal Provisions
Relating to IETF Documents
(http://trustee.ietf.org/license-info).
This version of this YANG module is part of
I-D draft-morais-iotops-inxu-01; see the I-D itself for
full legal notices.";
revision 2022-05-15{
description
"Simplifying the data model to one single description of
malicious traffic.";
reference
"draft-morais-iotops-inxu-01: Intra-Network eXposure analyzer
Utility Specification";
}
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typedef action-to-take {
type enumeration {
enum "alert" {
value 0;
description
"Alert user about a risky exposure";
}
description
"Type to specify the action to take when a threat is detected";
enum "block-not-attack" {
value 1;
description
"Block risky exposures of not-attack-traffic and warns uses
about attack-traffic alert exposures";
}
enum "block-attack" {
value 2;
description
"Block attack-traffic risky exposures and alert users about
the block";
}
enum "block-all" {
value 3;
description
"Block all risky exposures and alert users about the block";
}
}
}
container mtd {
presence "Enabled for this particular MTD URL";
description "MTD-related information";
uses mtd-groupig;
}
grouping mtd-groupig {
description
"This grouping is to create a set of definitions of
malicious traffic of malware and attacks.";
leaf mtd-url{
type inet:uri;
mandatory true;
description
"This is the MTD URL associated with the entry found
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in a MTD File";
}
leaf last-update {
type yang:date-and-time;
mandatory true;
description
"This is intended to be set when the current MTD File is
generated. MTD Managers SHOULD NOT check for updates
between this time plus cache validity.";
}
leaf mtd-signature {
type inet:uri;
description
"A URI that resolves to a signature file to verify the
autenticity of the MTD File.";
}
leaf cache-validity {
type uint8 {
range "1..168";
}
units "hours";
default "48";
description
"The information retrieved from the MTD Server is
valid for these many hours, after which it should be
refreshed. MTD Manager implementations do not need to
discard MTD Files beyond this period.";
}
container malicious-descriptions {
description
"This container has the descriptions of the malware and
attacks that can exploit or target the devices";
uses malicious-list;
}
}
grouping traffic-lists {
description
"A grouping for acess lists of malicious traffic in the context
of malware or attacks.";
container traffic-lists {
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description
"The access lists of the attack's malicious traffic
targeting or departing from the local IoT devices.";
list traffic-list {
key "name";
description
"Each entry on this list refers to an malicious
traffic defined by an ACL that should present the
overall network communication of the attack.";
leaf name {
type leafref{
path "/acl:acls/acl:acl/acl:name";
}
description
"The name of the ACL for this entry.";
}
leaf-list specific-devices {
type inet:uri;
description
"List of MUD URLs of specific devices
related with the vulnerability";
}
}
}
}
grouping malicious-list {
description
"A grouping for acess control lists of malicious traffic in the
context of malware or attacks.";
list malicious-list {
key "name";
description
"The access lists of the malware's or attack's malicious
traffic targeting or departing from the local IoT devices,";
leaf name {
type string;
description
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"The unique name of the described malicious activity for
each entry.";
}
leaf-list specific-devices {
type inet:uri;
description
"List of MUD URLs of specific devices
related with the vulnerability";
}
list critical-acl-sets{
key "name";
description
"Each list entry represents a malicious activity's critical
set of risky ACL exposures, followed by the action to take
when a critical set be detected.";
leaf name {
type string;
description
"The critical ACL set name";
}
leaf-list critical-acl-set {
type leafref{
path "/acl:acls/acl:acl/acl:name";
}
description
"A list to specify a set of ACLs that, when all listed
ACLs get classified as risky, represents a threat caused
by the malicious activity";
}
leaf action-to-take {
type draft-inxu-mtd:action-to-take;
mandatory true;
description
"A leaf to specify the action to be taken when
the respective set of critical ACLs turns into
a threat.";
}
}
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container to-device-attacks {
description
"The set of attack traffic performed by the
infected IoT device";
uses traffic-lists;
}
container from-device-attacks {
description
"The set of attack traffic performed targeting
the infected IoT device";
uses traffic-lists;
}
container to-device-not-attacks {
description
"The set of attack traffic performed by the
infected IoT device";
uses traffic-lists;
}
container from-device-not-attacks {
description
"The set of attack traffic performed targeting
the infected IoT device";
uses traffic-lists;
}
}
}
augment "/acl:acls/acl:acl/acl:aces/acl:ace/acl:matches" {
description
"adding abstraction to avoid the need of IP addresses.";
container mtd {
description
"MTD-specific match.";
leaf local-networks {
type empty;
description
"IP addresses will match this node if they are
considered local addresses. A local address may be
a list of locally defined prefixes and masks
that indicate a particular administrative scope.";
}
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}
}
augment "/acl:acls/acl:acl/acl:aces/acl:ace" {
description
"Add the risk level information associated to the ACE";
leaf risk {
type uint8;
default "1";
description
"Represents risk level of a device being exploited
when exposes the device through traffic matching the
described ACE.";
}
}
augment "/acl:acls/acl:acl" {
description
"Add an acceptable risk threshold and an alert risk threshold
to the ACL";
leaf risk-threshold {
type uint8;
default "1";
description
"The acceptable risk threshold represents the minimum
risk value for the exposure be considered a risk.
The actual risk of an ACL is calculated by the sum of
all the ACEs that matched on the INXU Module analysis";
}
leaf alert-threshold {
type uint8;
default "1";
description
"The acceptable alert threshold represents the minimum
risk value for the exposure trigger an alert.
The actual risk of an ACL is calculated by the sum of
all the ACEs that matched on the INXU Module analysis";
}
}
augment "/acl:acls/acl:acl/acl:aces/acl:ace/acl:matches"
+ "/acl:l4/acl:tcp/acl:tcp" {
description
"Add direction-initiated";
leaf direction-initiated {
type mud:direction;
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description
"This node matches based on which direction a
connection was initiated.";
}
}
augment "/acl:acls/acl:acl/acl:aces/acl:ace/acl:matches"
+ "/acl:l3/acl:ipv4/acl:ipv4" {
description
"Adding domain names to matching.";
uses acldns:dns-matches;
}
augment "/acl:acls/acl:acl/acl:aces/acl:ace/acl:matches"
+ "/acl:l3/acl:ipv6/acl:ipv6" {
uses acldns:dns-matches;
description
"Adding domain names to matching.";
}
deviation "/acl:acls/acl:acl/acl:aces/acl:ace/acl:actions" {
deviate not-supported;
description
"Field not used in this specification";
}
}
<CODE ENDS>
2.6. MTD File Example
This MTD file describes the traffic of an hipotetic variant of the
Mirai botnet. In its attack model, this malware scans for other
vulnerable devices in the same network, and its management services
(Command and Control, Scan Report, and Loader) are placed in the
network edge.
<CODE BEGINS>file "mirai-lan-variant.json"
{
"draft-inxu-mtd":"mtd",
"mtd-url":"https://example.com/mirai-lan-variant.json",
"last-update":"2022-05-15T18:17:00-03:00",
"malicious-descriptions":{
"malicious-list":[
{
"name":"Mirai-Example",
"critical-acl-sets":[
{
"name":"mirai-prevent-spread",
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"critical-acl-set":
[
{"name":"mirai_infect_v4from"},
{"name":"mirai_infect_v4to"},
{"name":"mirai_scan_v4from"},
{"name":"mirai_scan_v4to"}
],
"action-to-take": "BLOCK_ATTACK"
},
{
"name":"mirai-prevet-cnc",
"critical-acl-set":
[
{"name":"mirai_cnc_v4from"},
{"name":"mirai_cnc_v4to"}
],
"action-to-take": "BLOCK_N_ATTACK"
},
{
"name":"mirai-prevet-minimal",
"critical-acl-set":
[
{"name":"mirai_cnc_v4from"},
{"name":"mirai_cnc_v4to"},
{"name":"mirai_infect_v4from"},
{"name":"mirai_infect_v4to"}
],
"action-to-take": "BLOCK_ALL"
},
],
"to-device-attacks": {
"traffic-lists": {
"traffic-list": [
{"name":"mirai_infect_v4to"},
{"name":"mirai_scan_v4to"}
]
}
},
"from-device-attacks": {
"traffic-lists": {
"traffic-list": [
{"name":"mirai_infect_v4from"},
{"name":"mirai_scan_v4from"}
]
}
},
"to-device-not-attacks": {
"traffic-lists": {
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"traffic-list": [
{"name":"mirai_cnc_v4to"}
]
}
},
"from-device-not-attacks": {
"traffic-lists": {
"traffic-list": [
{"name":"mirai_cnc_v4from"}
]
}
},
}
]
},
"ietf-access-control-list:acls": {
"acl": [
{
"name":"mirai_infect_v4to",
"risk-threshold":11,
"type": "ipv4-acl-type",
"aces": {
"ace": [
{
"name":"infect_23_to",
"risk":10,
"matches":{
"ipv4":{
"ietf-acldns:dst-dnsname":"urn:ietf:params:\
mud:gateway",
"protocol":6
},
"tcp":{
"destination-port":{
"operator":"eq",
"port":23
}
}
}
},
{
"name":"infect_2323_to",
"risk":10,
"matches":{
"ipv4":{
"ietf-acldns:dst-dnsname":"urn:ietf:params:\
mud:gateway",
"protocol":6
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},
"tcp":{
"destination-port":{
"operator":"eq",
"port":2323
}
}
}
},
{
"name":"bin_download_to",
"risk":1,
"matches":{
"ipv4":{
"ietf-acldns:dst-dnsname":"urn:ietf:params:\
mud:gateway",
"protocol":6
},
"tcp":{
"source-port":{
"operator":"eq",
"port":80
},
}
}
}
]
}
},
{
"name":"mirai_scan_v4to",
"risk-threshold":11,
"type": "ipv4-acl-type",
"aces": {
"ace": [
{
"name":"scan_23_to",
"risk":10,
"matches":{
"ietf-mud:mud":{
"local-networks":[ null ]
},
"ipv4":{
"protocol":6
},
"tcp":{
"source-port":{
"operator":"eq",
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"port":23
},
}
}
},
{
"name":"scan_2323_to",
"risk":10,
"matches":{
"ietf-mud:mud":{
"local-networks":[ null ]
},
"ipv4":{
"protocol":6
},
"tcp":{
"source-port":{
"operator":"eq",
"port":2323
},
}
}
},
{
"name":"scan_report_to",
"risk":1,
"matches":{
"ipv4":{
"ietf-acldns:dst-dnsname":"urn:ietf:params:\
mud:gateway",
"protocol":6
},
"tcp":{
"source-port":{
"operator":"eq",
"port":48101
},
}
}
}
]
}
},
{
"name":"mirai_infect_v4from",
"risk-threshold":11,
"type": "ipv4-acl-type",
"aces": {
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"ace": [
{
"name":"infect_23_from",
"risk":10,
"matches":{
"ipv4":{
"ietf-acldns:dst-dnsname":"urn:ietf:params:\
mud:gateway",
"protocol":6
},
"tcp":{
"source-port":{
"operator":"eq",
"port":23
},
}
}
},
{
"name":"infect_2323_from",
"risk":10,
"matches":{
"ipv4":{
"ietf-acldns:dst-dnsname":"urn:ietf:params:\
mud:gateway",
"protocol":6
},
"tcp":{
"source-port":{
"operator":"eq",
"port":2323
},
}
}
},
{
"name":"bin_download_from",
"risk":1,
"matches":{
"ipv4":{
"ietf-acldns:dst-dnsname":"urn:ietf:params:\
mud:gateway",
"protocol":6
},
"tcp":{
"destination-port":{
"operator":"eq",
"port":80
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}
}
}
}
]
}
},
{
"name":"mirai_scan_v4from",
"risk-threshold":11,
"type": "ipv4-acl-type",
"aces": {
"ace": [
{
"name":"scan_23_from",
"risk":10,
"matches":{
"ietf-mud:mud":{
"local-networks":[ null ]
},
"ipv4":{
"protocol":6
},
"tcp":{
"destination-port":{
"operator":"eq",
"port":23
}
}
}
},
{
"name":"scan_2323_from",
"risk":10,
"matches":{
"ietf-mud:mud":{
"local-networks":[ null ]
},
"ipv4":{
"protocol":6
},
"tcp":{
"destination-port":{
"operator":"eq",
"port":2323
}
}
}
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},
{
"name":"scan_report_from",
"risk":1,
"matches":{
"ipv4":{
"ietf-acldns:dst-dnsname":"urn:ietf:params:\
mud:gateway",
"protocol":6
},
"tcp":{
"destination-port":{
"operator":"eq",
"port":48101
}
}
}
}
]
}
},
{
"name":"mirai_cnc_v4to",
"type": "ipv4-acl-type",
"aces": {
"ace": [
{
"name":"cnc_socket_to",
"risk":1,
"matches":{
"ipv4":{
"ietf-acldns:dst-dnsname":"urn:ietf:params:\
mud:gateway",
"protocol":6
},
"tcp":{
"source-port":{
"operator":"eq",
"port":2030
},
}
}
}
]
}
},
{
"name":"mirai_cnc_v4from",
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"type": "ipv4-acl-type",
"aces": {
"ace": [
{
"name":"cnc_socket_from",
"risk":1,
"matches":{
"ipv4":{
"ietf-acldns:dst-dnsname":"urn:ietf:params:\
mud:gateway",
"protocol":6
},
"tcp":{
"destination-port":{
"operator":"eq",
"port":2030
}
}
}
}
]
}
}
]
}
}
<CODE ENDS>
3. The Intra-Network eXposure analyzer Utility
INXU was designed to have as main features: (i) enable quick
responses to new vulnerabilities; (ii) allow mitigation of the
damages of a new vulnerability, simultaneously in multiple distinct
networks; and (iii) enable a decision-making process about security
measures on the network edge, avoiding the disclosure of private
information to third parties.
To cover these requirements, INXU enables a security expert team -
such as a SOC or an ISP Abuse Desk - to describe the traffic of
ongoing malicious activities using the MTD data model (more details
of the MTD data model are discussed in Section 3). With these
descriptions, the security experts team can use the INXU to prevent
multiple distinct networks when releasing new MTD Files for every new
malicious activity discovered, in a process similar to the antivirus
programs vaccines.
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3.1. INXU Architecture and Components
The ASCII diagram below shows the architecture of INXU. The proposed
architecture contains 4 main components: MTD Server, MTD Manager,
INXU Module, and MUD manager [RFC8520].
...................................................
. End system network edge .
. _____________ .
. | | .
. | MUD manager | Communication .
. | [RFC8520] |--->graph>----+ .
. |_____________| | ________ .
. +---->| | .
. ___________ | INXU | .
. | | +---->|________| .
. | MTD | | .
. | Manager |---->MTD File>--+ .
. |___________| .
. | ^ .
......|..|.........................................
| |
| | __________
| +--<MTD File<--| |
| (https) | MTD |
+----->get URL>-->| Server |
|__________|
The MTD Server is responsible for storing and delivering the
malicious traffic descriptions made by a security expert. This
component was designed to enable trusted third-party specialists to
share knowledge about well-known malicious activities affecting IoT
and allow IoT networks to make use of this knowledge to protect
themselves. The MTD Server is composed by a HTTPS server that hosts
and delivers the MTD File for the clients. The MTD File is a file
where the network traffic associated with malicious activities are
described to INXU. This component also contains data for version
control, authenticity, and validity time. The content of a MTD File
is defined by a security expert in a JSON file, following the YANG
data model described in the Section 2.
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The MTD Manager has the function of managing the MTD File on the
system. It is responsible for requesting the file to the MTD Server,
verifying authenticity, and requesting a new file when the current
file validity expires. The default way to ensure MTD File
authenticity is by HTTPS protocol, but the MTD Manager can also use
the means described in the Section 3.1 of the [RFC2818]. At the end
of the process, the MTD Manager forwards the MTD File to the INXU
Module.
The INXU (Intra-Network eXposure analyzer Utility) module is the main
component of this proposal. It is responsible for verifying all the
network communications trying to identify possible exposures to
malicious traffic. To do this, the INXU Module compares the
malicious traffic described in a MTD File with the network graph
generated by MUD manager. The exposure analysis process is detailed
in Section 3.5.
3.2. Workflow
The workflow adopted to INXU may vary, but it will mostly follow the
process described below.
1. MTD Manager fetches the MTD File.
2. After confirming MTD File authenticity, the MTD Manager sends it
for the INXU Module.
3. The MUD manager sends the network communication graph --
including the devices' MUD URLs -- to the INXU Module.
4. INXU Module identifies potential vulnerability exposures into the
network.
5. INXU analyzes the detected vulnerabilities to evaluate if they
represent an effective threat. After detecting threats, INXU may
act as an Intrusion Prevention System and block the exposures, or
serve as input source for other security systems, depending on
the implementation.
6. If the MUD manager detects any change in the network topology, or
the MTD Manager gets new definitions from MTD Files, the process
returns to step 4.
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3.3. Acquiring a MTD File
The main method for acquiring a MTD File is by configuring the MTD
URL into the MTD Manager. The MTD URL is a Universal Resource
Locator (URL) [RFC3986] provided by the Security Experts team
designated for protecting the network.
MTD URLs MUST use the "https" scheme [RFC7230].
An alternative manner for acquiring a MTD File is by manually
importing and its respective signature file into the MTD Manager.
The mechanisms for doing so are not described in this document.
3.4. Processing a MTD URL
Disclaimer: The specification in this section is in our roadmap but
still not done. Our initial intention is to use the same
specification as [RFC8520] in Section 1.6. To simplify
understanding, we copied the original MUD text, pasted it below, and
replaced the MUD references with MTD.
MTD Managers that are able to do so SHOULD retrieve MTD URLs and
signature files as per [RFC7230], using the GET method [RFC7231].
They MUST validate the certificate using the rules in [RFC2818],
Section 3.1.
Requests for MTD URLs SHOULD include an "Accept" header field
([RFC7231], Section 5.3.2) containing "application/mtd+json", an
"Accept-Language" header field ([RFC7231], Section 5.3.5), and a
"User-Agent" header field ([RFC7231], Section 5.5.3).
MTD Managers SHOULD automatically process 3xx response status codes.
If a MTD Manager is not able to fetch a MTD URL, other means MAY be
used to import the MTD File and its associated signature file. So
long as the signature of the file can be validated, the file can be
used. In such environments, controllers SHOULD warn administrators
when cache-validity expiry is approaching so that they may check for
new files.
3.5. INXU Vulnerability Analysis Process
The exposure analysis algorithm of the INXU Module uses malicious
traffic descriptions from a MTD File to compare with the IoT traffic
flows allowed by MUD -- provided by the network communication graph
generated by MUD manager -- and tries to detect vulnerabilities on
the network. In this context, INXU identifies one exposure when some
graph edge matches with any entry of the MTD File.
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Based on the MUD files, each host expected to communicate with the
IoT devices, or the IoT devices themselves, are represented by nodes
on the network communication graph generated by MUD manager. The
host network address represents the nodes, and in the case of IoT
devices on the LAN, the MUD URL is associated with the node
information. The graph edges represent TCP or UDP sockets, or ICMP
communications, where a directed edge represents a communication
path.
3.5.1. Exposure Identification
For each IoT node in the MUD-based communication graph, the Exposure
Identification process verifies if five information match between
edge and ACEs: source and destination host addresses, communication
protocol, and source and destination ports -- for transport protocols
-- or ICMP message type and code. We only consider an exposure when
all five information match.
The ACEs considered here MUST be applicable for any device OR include
the IoT device's MUD URL in the specific-devices list.
A match on source or destination host address happens when the
addresses are equals OR when the ACE uses the local address
abstraction and the node is local.
Protocols match when the specified protocols (TCP, UDP, ICMP, or any)
are equal both on ACE and edge OR when the ACE specifies any
protocol.
For the ICMP message type and code or for transport's source and
destination ports, a match happens when the specified values are
equals OR when the ACE specifies any value.
3.5.2. ACL Risk Assessment
Each vulnerability exposure is associated with an ACE and is in the
context of an ACL. Therefore, a set of vulnerability exposures of a
device becomes a risk when the sum of their ACE risks is bigger than
the ACL's risk threshold. There is also a possibility of triggering
an alert state when the ACL's risk exceeds the alert threshold.
The risk threshold SHOULD be equals or bigger than the alert
threshold.
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3.5.3. Threat Analysis
After assessing the risk of each ACL, the next step in the process is
the threat analysis. This analysis iterates over the list of the
critical ACL sets of a malicious activity.
In this step, the INXU Module verifies if all the ACLs contained in a
critical set are classified as risky for a device. If this condition
becomes true, the INXU Module SHOULD take the action specified in the
set's action-to-take field. If a malicious activity threatens the
device with more than one set of critical ACLs, the INXU Module MUST
take an action based into a merge of all the threatening sets'
action-to-take.
4. Further Considerations and Next Steps
During the development of INXU, we found some important points that
could further enhance the proposal in the near future. First of all,
although INXU sticks to the Network and Transport layers, many
recently reported DDoS attacks exploited the DNS platform to cause
damage. This issue requires some treatment in this application layer
protocol of the TCP/IP model. As it is a crucial application for the
Internet's functioning as we know it today, it is impossible to block
traffic over the protocol completely, but we believe that some level
of filtering will not negatively impact the devices' usability nor
the network's performance.
Another interesting future direction is that although INXU allows
identifying, classifying, and mitigating malicious activities on the
other hand it does that without any intervention from the user. All
the blocking processes do not allow the end-users intervention on the
blocks and may lead them to not adopt INXU. An option to overcome
this issue is by integrating Software Bill of Materials (SBOM)
related information into the MTD data model and in the Threat
Analysis process, and allowing end-users feedback on blocking
decisions. This may reduce INXU's impact on usability with low
security loss and consequently improve its adoption.
Also in this sense, we could use the MTD as a standard data model for
attacks signatures involving IoT. It is a useful way to share how
attacks can alter the network traffic to be used in controlled
experiments and simulations. Also it can be seen also as a
systematic way to share information on attacks -- in this sense
network administrators, scientists and security analysts could have
the same view over a given event in the network.
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Finally, also coming from the previous statement, INXU's output could
be used as an input filter for IPS/IDS systems in order to prevent
attacks and any other malicious event in the network. Since by using
the MTD we could classify the traffic into appropriate or not.
Furthermore INXU -- specially the MTD -- could be paired with an AI
engine to learn about new network patterns and classify them as an
attack or some new device in the network -- the system could write
some new MTDs as it learns from the network.
5. Security Considerations
Since INXU uses MUD as a data source, the problems presented at the
Security Considerations session of the [RFC8520] are still valid for
this proposal, and some new ones arise.
The first new risk is the possibility of INXU causing Denial of
Service on their protected IoT devices depending on how the malicious
activities are described in the MTD File. To prevent this issue,
while describing a malicious activity, the Security Specialist SHOULD
be as specific as possible by describing, for example, the specific
devices that can be affected by the attack or malware and being
assertive while defining ACE risks and ACL risk thresholds.
As with MUD, the MTD Manager may receive a fake MTD File from a rogue
MTD Server with a certificate issued by an accredited certification
authority (CA). In this case, the same MUD mitigations apply: First,
if the signer changes, this may be flagged as an exception by the MTD
manager. Second, if the MTD file also changes, the MTD manager
SHOULD seek administrator approval (it should do this in any case).
In all circumstances, the MUD manager MUST maintain a cache of
trusted CAs for this purpose. When such a rogue is discovered, it
SHOULD be removed.
Finally, INXU is not effective against attacks that are occurring
prior to a new MTD file arriving or ongoing at the moment of an
update. The classification of the attack is not accurate since it
does not know the rules. A countermeasure is to use an anomaly
detection system to identify such attacks. INXU is not responsible
for that part.
Further security considerations might arise during this document's
evolution.
6. IANA Considerations
This memo includes no request to IANA.
7. References
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7.1. Normative References
[RFC2119] Bradner, S., "Key words for use in RFCs to Indicate
Requirement Levels", BCP 14, RFC 2119,
DOI 10.17487/RFC2119, March 1997,
<https://www.rfc-editor.org/info/rfc2119>.
[RFC3986] Berners-Lee, T., Fielding, R. T., and L. M. Masinter,
"Uniform Resource Identifier (URI): Generic Syntax",
January 2005, <https://rfc-editor.org/rfc/rfc3986.txt>.
[RFC7230] Fielding, R. T. and J. Reschke, "Hypertext Transfer
Protocol (HTTP/1.1): Message Syntax and Routing", June
2014, <https://rfc-editor.org/rfc/rfc7230.txt>.
[RFC7231] Fielding, R. T. and J. Reschke, "Hypertext Transfer
Protocol (HTTP/1.1): Semantics and Content", June 2014,
<https://rfc-editor.org/rfc/rfc7231.txt>.
[RFC7950] Bjorklund, M., "The YANG 1.1 Data Modeling Language",
August 2016, <https://rfc-editor.org/rfc/rfc7950.txt>.
[RFC8174] Leiba, B., "Ambiguity of Uppercase vs Lowercase in RFC
2119 Key Words", May 2017,
<https://rfc-editor.org/rfc/rfc8174.txt>.
[RFC8340] Björklund, M. and L. Berger, "YANG Tree Diagrams", March
2018, <https://rfc-editor.org/rfc/rfc8340.txt>.
[RFC8519] Jethanandani, M., Agarwal, S., Huang, L., and D. Blair,
"YANG Data Model for Network Access Control Lists (ACLs)",
March 2019, <https://rfc-editor.org/rfc/rfc8519.txt>.
[RFC8520] Lear, E., Droms, R., and D. Romascanu, "Manufacturer Usage
Description Specification", March 2019,
<https://rfc-editor.org/rfc/rfc8520.txt>.
7.2. Informative References
[Mozzaquatro2015]
Mozzaquatro, B. A., Jardim-Goncalves, R., and C.
Agostinho, "Towards a reference ontology for security in
the Internet of Things", 2015,
<https://doi.org/10.1109/IWMN.2015.7322984>.
[RFC2818] Rescorla, E., "HTTP Over TLS", May 2000,
<https://rfc-editor.org/rfc/rfc2818.txt>.
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Authors' Addresses
Sávyo Vinícius de Morais
IFRN
Natal-
Brazil
Email: savyovm@gmail.com
Claudio Miceli de Farias
UFRJ
Rio de Janeiro-
Brazil
Email: cmicelifarias@gmail.com
Morais & Farias Expires 27 November 2022 [Page 37]
