I2NSF Working Group J. Yang
Internet-Draft J. Jeong
Intended status: Standards Track J. Kim
Expires: September 12, 2019 Sungkyunkwan University
March 11, 2019
Security Policy Translation in Interface to Network Security Functions
draft-yang-i2nsf-security-policy-translation-03
Abstract
This document proposes a scheme of security policy translation (i.e.,
Security Policy Translator) in Interface to Network Security
Functions (I2NSF) Framework. When I2NSF User delivers a high-level
security policy for a security service, Security Policy Translator in
Security Controller translates it into a low-level security policy
for Network Security Functions (NSFs).
Status of This Memo
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provisions of BCP 78 and BCP 79.
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This Internet-Draft will expire on September 12, 2019.
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include Simplified BSD License text as described in Section 4.e of
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the Trust Legal Provisions and are provided without warranty as
described in the Simplified BSD License.
Table of Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . 2
2. Terminology . . . . . . . . . . . . . . . . . . . . . . . . . 3
3. Necessity for Policy Translator . . . . . . . . . . . . . . . 3
4. Design of Policy Translator . . . . . . . . . . . . . . . . . 4
4.1. Overall Structure of Policy Translator . . . . . . . . . 4
4.2. DFA-based Data Extractor . . . . . . . . . . . . . . . . 6
4.2.1. Design of DFA-based Data Extractor . . . . . . . . . 6
4.2.2. Example Scenario for Data Extractor . . . . . . . . . 7
4.3. Data Converter . . . . . . . . . . . . . . . . . . . . . 9
4.3.1. Role of Data Converter . . . . . . . . . . . . . . . 9
4.3.2. NSF Database . . . . . . . . . . . . . . . . . . . . 10
4.3.3. Data Conversion in Data Converter . . . . . . . . . . 10
4.3.4. Policy Provisioning . . . . . . . . . . . . . . . . . 12
4.4. CFG-based Policy Generator . . . . . . . . . . . . . . . 13
4.4.1. Content Production . . . . . . . . . . . . . . . . . 13
4.4.2. Structure Production . . . . . . . . . . . . . . . . 14
4.4.3. Generator Construction . . . . . . . . . . . . . . . 14
5. Implementation Considerations . . . . . . . . . . . . . . . . 18
5.1. Data Model Auto-adaptation . . . . . . . . . . . . . . . 18
5.2. Data Conversion . . . . . . . . . . . . . . . . . . . . . 19
5.3. Policy Provisioning . . . . . . . . . . . . . . . . . . . 19
6. Features of Policy Translator Design . . . . . . . . . . . . 19
7. Security Considerations . . . . . . . . . . . . . . . . . . . 20
8. Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . 20
9. References . . . . . . . . . . . . . . . . . . . . . . . . . 20
9.1. Normative References . . . . . . . . . . . . . . . . . . 20
9.2. Informative References . . . . . . . . . . . . . . . . . 21
Appendix A. Changes from draft-yang-i2nsf-security-policy-
translation-02 . . . . . . . . . . . . . . . . . . . 22
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 22
1. Introduction
This document defines a scheme of a security policy translation in
Interface to Network Security Functions (I2NSF) Framework [RFC8329].
First of all, this document explains the necessity of a security
policy translator (shortly called policy translator) in the I2NSF
framework.
The policy translator resides in Security Controller in the I2NSF
framework and translates a high-level security policy to a low-level
security policy for Network Security Functions (NSFs). A high-level
policy is specified by I2NSF User in the I2NSF framework and is
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delivered to Security Controller via Consumer-Facing Interface
[consumer-facing-inf-dm]. It is translated into a low-level policy
by Policy Translator in Security Controller and is delivered to NSFs
to execute the rules corresponding to the low-level policy via NSF-
Facing Interface [nsf-facing-inf-dm].
2. Terminology
This document uses the terminology specified in [i2nsf-terminology]
[RFC8329].
3. Necessity for Policy Translator
Security Controller acts as a coordinator between I2NSF User and
NSFs. Also, Security Controller has capability information of NSFs
that are registered via Registration Interface [registration-inf-dm]
by Developer's Management System [RFC8329]. As a coordinator,
Security Controller needs to generate a low-level policy in the form
of security rules intended by the high-level policy, which can be
understood by the corresponding NSFs.
A high-level security policy is specified by RESTCONF/YANG
[RFC8040][RFC6020], and a low-level security policy is specified by
NETCONF/YANG [RFC6241][RFC6020]. The translation from a high-level
security policy to the corresponding low-level security policy will
be able to rapidly elevate I2NSF in real-world deployment. A rule in
a high-level policy can include a broad target object, such as
employees in a company for a security service (e.g., firewall and web
filter). Such employees may be from human resource (HR) department,
software engineering department, and advertisement department. A
keyword of employee needs to be mapped to these employees from
various departments. This mapping needs to be handled by a policy
translator in a flexible way while understanding the intention of a
policy specification. Let us consider the following two policies:
o Block my son's computers from malicious websites.
o Drop packets from the IP address 10.0.0.1 and 10.0.0.3 to harm.com
and illegal.com
The above two sentences are examples of policies for blocking
malicious websites. Both policies are for the same operation.
However, NSF cannot understand the first policy, because the policy
does not have any specified information for NSF. To set up the
policy at an NSF, the NSF MUST receive at least the source IP address
and website address for an operation. It means that the first
sentence is NOT compatible for an NSF policy. Conversely, when I2NSF
Users request a security policy to the system, they never make a
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security policy like the second example. For generating a security
policy like the second sentence, the user MUST know that the NSF
needs to receive the specified information, source IP address and
website address. It means that the user understands the NSF
professionally, but there are not many professional users in a small
size of company or at a residential area. In conclusion, the I2NSF
User prefers to issue a security policy in the first sentence, but an
NSF will require the same policy as the second sentence with specific
information. Therefore, an advanced translation scheme of security
policy is REQUIRED in I2NSF.
This document proposes an approach using Automata theory [Automata]
for the policy tranlation, such as Deterministic Finite Automaton
(DFA) and Context Free Grammar (CFG). Note that Automata theory is
the foundation of programming language and compiler. Thus, with this
approach, I2NSF User can easily specify a high-level security policy
that will be enforced into the corresponding NSFs with a compatibly
low-level security policy with the help of Policy Translator. Also,
for easy management, a modularized translator structure is proposed.
4. Design of Policy Translator
Commonly used security policies are created as XML(Extensible Markup
Language) [XML] files. A popular way to change the format of an XML
file is to use an XSLT (Extensible Stylesheet Language
Transformation) [XSLT] document. XSLT is an XML-based language to
transform an input XML file into another output XML file. However,
the use of XSLT makes it difficult to manage the policy translator
and to handle the registration of new capabilities of NSFs. With the
necessity for a policy translator, this document describes a policy
translator based on Automata theory.
4.1. Overall Structure of Policy Translator
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High-Level Policy
Security |
Controller V Consumer-Facing Interface
+------------------------+-------------------------+
| Policy | |
| Translator | |
| +---------------------+----------------------+ |
| | | | |
| | +-------+--------+ | |
| | | DFA-based | | |
| | | Data Extractor | | |
| | +-------+--------+ | |
| | | Extracted Data from | |
| | V High-Level Policy | |
| | +-----+-----+ +--------+ | |
| | | Data | <-> | NSF DB | | |
| | | Converter | +--------+ | |
| | +-----+-----+ | |
| | | Required Data for | |
| | V Target NSFs | |
| | +--------+---------+ | |
| | | CFG-based | | |
| | | Policy Generator | | |
| | +--------+---------+ | |
| | | | |
| +---------------------+----------------------+ |
| | |
+------------------------+-------------------------+
| NSF-Facing Interface
V
Low-Level Policy
Figure 1: The Overall Design of Policy Translator
Figure 1 shows the overall design for Policy Translator in Security
Controller. There are three main components for Policy Translator:
Data Extractor, Data Converter, and Policy Generator.
Extractor is a DFA-based module for extracting data from a high-level
policy which I2NSF User delivered via Consumer-Facing Interface.
Data Converter converts the extracted data to the capabilities of
target NSFs for a low-level policy. It refers to NSF Database (DB)
in order to convert an abstract subject or object into the
corresponding concrete subject or object (e.g., IP address and
website URL). Policy Generator generates a low-level policy which
will execute the NSF capabilities from Converter.
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4.2. DFA-based Data Extractor
4.2.1. Design of DFA-based Data Extractor
+----------+
| accepter |
+----------+
| ^
| |
v |
+------------------------------------------------------+
| middle 1 |
+------------------------------------------------------+
| ^ | ^ | ^
| | | | ... | |
v | v | v |
... ... ...
+-------------+ +-------------+ +-------------+
| extractor 1 | | extractor 2 | ... | extractor m |
+-------------+ +-------------+ +-------------+
data:1 data:2 data:m
Figure 2: DFA Architecture of Data Extractor
Figure 2 shows a design for Data Extractor in the policy translator.
If a high-level policy contains data along the hierarchical structure
of the standard Consumer-Facing Interface YANG data model
[consumer-facing-inf-dm], data can be easily extracted using the
state transition machine, such as DFA. The extracted data can be
processed and used by an NSF to understand it. Extractor can be
constructed by designing a DFA with the same hierarchical structure
as a YANG data model.
After constructing a DFA, Data Extractor can extract all of data in
the enterred high-level policy by using state transitions. Also, the
DFA can easily detect the grammar errors of the high-level policy.
The extracting algorithm of Data Extractor is as follows:
1. Start from the 'accepter' state.
2. Read the next tag from the high-level policy.
3. Transit to the corresponding state.
4. If the current state is in 'extractor', extract the corresponding
data, and then go back to step 2.
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5. If the current state is in 'middle', go back to step 2.
6. If there is no possible transition and arrived at 'accepter'
state, the policy has no grammar error. Otherwise, there is a
grammar error, so stop the process with failure.
4.2.2. Example Scenario for Data Extractor
block_web
Son's_PC
malicious_websites
block
Figure 3: The Example of High-level Policy
+----------+
| accepter |
+----------+
| ^
| |
v |
+------------------------------------------------------+
| middle 1 |
+------------------------------------------------------+
| ^ | ^ | ^
| | | | | |
v | v | v |
+-------------+ +----------------------+ +-------------+
| extractor 1 | | middle 2 | | extractor 4 |
+-------------+ +----------------------+ +-------------+
block_web | ^ | ^ block
| | | |
v | v |
+-------------+ +-------------+
| extractor 2 | | extractor 3 |
+-------------+ +-------------+
Son's_PC malicious
_websites
Figure 4: The Example of Data Extractor
To explain the Data Extractor process by referring to an example
scenario, assume that Security Controller received a high-level
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policy for a web-filtering as shown in Figure 3. Then we can
construct DFA-based Data Extractor by using the design as shown in
Figure 2. Figure 4 shows the architecture of Data Extractor that is
based on the architection in Figure 2 along with the input high-level
policy in Figure 3. Data Extractor can automatically extract all of
data in the high-level policy according to the following process:
1. Start from the 'accepter' state.
2. Read the first opening tag called '', and transit to the
'middle 1' state.
3. Read the second opening tag called '', and transit to the
'extractor 1' state.
4. The current state is an 'extractor' state. Extract the data of
'name' field called 'block_web'.
5. Read the second closing tag called '', and go back to the
'middle 1' state.
6. Read the third opening tag called '', and transit to the
'middle 2' state.
7. Read the fourth opening tag called '', and transit to the
'extractor 2' state.
8. The current state is an 'extractor' state. Extract the data of
'src' field called 'Son's_PC'.
9. Read the fourth closing tag called '', and go back to the
'middle 2' state.
10. Read the fifth opening tag called '', and transit to the
'extractor 3' state.
11. The current state is an 'extractor' state. Extract the data of
'dest' field called 'malicious_websites'.
12. Read the fifth closing tag called '', and go back to the
'middle 2' state.
13. Read the third closing tag called '', and go back to the
'middle 1' state.
14. Read the sixth opening tag called '', and transit to the
'extractor 4' state.
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15. The current state is an 'extractor' state. Extract the data of
'action' field called 'block'.
16. Read the sixth closing tag called '', and go back to
the 'middle 1' state.
17. Read the first closing tag called '', and go back to the
'accepter' state.
18. There is no further possible transition, and the state is
finally on 'accepter' state. There is no grammar error in
Figure 3 so the scanning for data extraction is finished.
The above process is constructed by an extracting algorithm. After
finishing all the steps of the above process, Data Extractor can
extract all of data in Figure 3, 'block_web', 'Son's_PC',
'malicious', and 'block'.
Since the translator is modularized into a DFA structure, a visual
understanding is feasible. Also, The performance of Data Extractor
is excellent compared to one-to-one searching of data for a
particular field. In addition, the management is efficient because
the DFA completely follows the hierarchy of Consumer-Facing
Interface. If I2NSF User wants to modify the data model of a high-
level policy, it only needs to change the connection of the relevant
DFA node.
4.3. Data Converter
4.3.1. Role of Data Converter
Every NSF has its own unique capabilities. The capabilities of an
NSF are registered into Security Controller by a Developer's
Management System, which manages the NSF, via Registration Interface.
Therefore, Security Controller already has all information about the
capabilities of NSFs. This means that Security Controller can find
target NSFs with only the data (e.g., subject and object for a
security policy) of the high-level policy by comparing the extracted
data with all capabilities of each NSF. This search process for
appropriate NSFs is called by policy provisioning, and it eliminates
the need for I2NSF User to specify the target NSFs explicitly in a
high-level security policy.
Data Converter selects target NSFs and converts the extracted data
into the capabilities of selected NSFs. If Security Controller uses
this data convertor, it can provide the policy provisioning function
to I2NSF User automatically. Thus, the translator design provides
big benefits to the I2NSF Framework.
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4.3.2. NSF Database
The NSF Database contains all the information needed to convert high-
level policy data to low-level policy data. The contents of NSF
Database are classified as the following two: "endpoint information"
and "NSF capability information".
The first is "endpoint information". Endpoint information is
necessary to convert an abstract high-level policy data such as
Son's_PC, malicious to a specific low-level policy data such as
10.0.0.1, illegal.com. In the high-level policy, the range of
endpoints for applying security policy MUST be provided abstractly.
Thus, endpoint information is needed to specify the abstracted high-
level policy data. Endpoint information is provided by I2NSF User as
the high-level policy through Consumer-Facing Interface, and Security
Controller builds NSF Database based on received information.
The second is "NSF capability information". Since capability is
information that allows NSF to know what features it can support, NSF
capability information is used in policy provisioning process to
search the appropriate NSFs through the security policy. NSF
capability information is provided by Developer's Management System
(DMS) through Registration Interface, and Security Controller builds
NSF Database based on received information. In addition, if the NSF
sends monitoring information such as initiating information to
Security Controller through NSF-Facing Interface, Security Controller
can modify NSF Database accordingly.
4.3.3. Data Conversion in Data Converter
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High-level Low-level
Policy Data Policy Data
+---------------+ +------------------------------+
| Rule Name | | Rule Name |
| +-----------+ | The Same value | +-------------------------+ |
| | block_web |-|------------------->|->| block_web | |
| +-----------+ | | +-------------------------+ |
| | | |
| Source | Conversion into | Source IPv4 |
| +-----------+ | User's IP address | +-------------------------+ |
| | Son's_PC |-|------------------->|->| [10.0.0.1, 10.0.0.3] | |
| +-----------+ | | +-------------------------+ |
| | | |
| Destination | Conversion into | URL Category |
| +-----------+ | malicious websites | +-------------------------+ |
| | malicious |-|------------------->|->| [harm.com, | |
| | _websites | | | | illegal.com] | |
| +-----------+ | | +-------------------------+ |
| | | |
| Action | Conversion into | Log Action Drop Action |
| +-----------+ | NSF Capability | +----------+ +----------+ |
| | block |-|------------------->|->| True | | True | |
| +-----------+ | | +----------+ +----------+ |
+---------------+ +------------------------------+
Figure 5: Example of Data Conversion
Figure 5 shows an example for describing a data conversion in Data
Converter. High-level policy data MUST be converted into low-level
policy data which are compatible with NSFs. If a ystem administrator
attaches a database to Data Converter, it can convert contents by
referring to the database with SQL queries. Data conversion in
Figure 5 is based on the following list:
o 'Rule Name' field does NOT need the conversion.
o 'Source' field SHOULD be converted into a list of target IPv4
addresses.
o 'Destination' field SHOULD be converted into a URL category list
of malicious websites.
o 'Action' field SHOULD be converted into the corresponding
action(s) in NSF capabilities.
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4.3.4. Policy Provisioning
Log-keeper Low-level Web-filter
NSF Policy Data NSF
+-------------------+ +--------------------+ +-------------------+
| Rule Name | | Rule Name | | Rule Name |
| +--------------+ | | +--------------+ | | +--------------+ |
| | block_web |<-|<-|<-| block_web |->|->|->| block_web | |
| +--------------+ | | +--------------+ | | +--------------+ |
| | | | | |
| Source IPv4 | | Source IPv4 | | Source IPv4 |
| +--------------+ | | +--------------+ | | +--------------+ |
| | [10.0.0.1, |<-|<-|<-| [10.0.0.1, |->|->|->| [10.0.0.1, | |
| | 10.0.0.3] | | | | 10.0.0.3] | | | | 10.0.0.3] | |
| +--------------+ | | +--------------+ | | +--------------+ |
| | | | | |
| | | URL Category | | URL Category |
| | | +--------------+ | | +--------------+ |
| | | | [harm.com, |->|->|->| [harm.com, | |
| | | | illegal.com] | | | | illegal.com] | |
| | | +--------------+ | | +--------------+ |
| | | | | |
| Log Action | | Log Action | | |
| +--------------+ | | +--------------+ | | |
| | True |<-|<-|<-| True | | | |
| +--------------+ | | +--------------+ | | |
+-------------------+ | | | |
| Drop Action | | Drop Action |
| +--------------+ | | +--------------+ |
| | True |->|->|->| True | |
| +--------------+ | | +--------------+ |
+--------------------+ +-------------------+
Figure 6: Example of Policy Provisioning
Generator searches for proper NSFs which can cover all of
capabilities in the high-level policy. Generator searches for target
NSFs by comparing only NSF capabilities which is registered by Vendor
Management System. This process is called by "policy provisioning"
because Generator finds proper NSFs by using only the policy. If
target NSFs are found by using other data which is not included in a
user's policy, it means that the user already knows the specific
knowledge of an NSF in the I2NSF Framework. Figure 6 shows an
example of policy provisioning. In this example, log-keeper NSF and
web-filter NSF are selected for covering capabilities in the security
policy. All of capabilities can be covered by two selected NSFs.
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4.4. CFG-based Policy Generator
Generator makes low-level security policies for each target NSF with
the extracted data. We constructed Generator by using Context Free
Grammar (CFG). CFG is a set of production rules which can describe
all possible strings in a given formal language(e.g., programming
language). The low-level policy also has its own language based on a
YANG data model of NSF-Facing Interface. Thus, we can construct the
productions based on the YANG data model. The productions that makes
up the low-level security policy are categorized into two types,
'Content Production' and 'Structure Production'.
4.4.1. Content Production
Content Production is for injecting data into low-level policies to
be generated. A security manager(i.e., a person (or software) to
make productions for security policies) can construct Content
Productions in the form of an expression as the following
productions:
o [cont_prod] -> [cont_prod][cont_prod] (Where duplication is
allowed.)
o [cont_prod] -> [cont_data]
o [cont_data] -> data_1 | data_2 | ... | data_n
Square brackets mean non-terminal state. If there are no non-
terminal states, it means that the string is completely generated.
When the duplication of content tag is allowed, the security manager
adds the first production for a rule. If there is no need to allow
duplication, the first production can be skipped because it is an
optional production.
The second production is the main production for Content Production
because it generates the tag which contains data for low-level
policy. Last, the third production is for injecting data into a tag
which is generated by the second production. If data is changed for
an NSF, the security manager needs to change "only the third
production" for data mapping in each NSF.
For example, if the security manager wants to express a low-level
policy for source IP address, Content Production can be constructed
in the following productions:
o [cont_ipv4] -> [cont_ipv4][cont_ipv4] (Allow duplication.)
o [cont_ipv4] -> [cont_ipv4_data]
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o [cont_ipv4_data] -> 10.0.0.1 | 10.0.0.3
4.4.2. Structure Production
Structure Production is for grouping other tags into a hierarchy.
The security manager can construct Structure Production in the form
of an expression as the following production:
o [struct_prod] -> [prod_1]...[prod_n]
Structure Production can be expressed as a single production. The
above production means to group other tags by the name of a tag which
is called by 'struct_tag'. [prod_x] is a state for generating a tag
which wants to be grouped by Structure Production. [prod_x] can be
both Content Production and Structure Production. For example, if
the security manager wants to express the low-level policy for the
I2NSF tag, which is grouping 'name' and 'rules', Structure Production
can be constructed as the following production where [cont_name] is
the state for Content Production and [struct_rule] is the state for
Structure Production.
o [struct_i2nsf] -> [cont_name][struct_rules]
4.4.3. Generator Construction
The security manager can build a generator by combining the two
productions which are described in Section 4.4.1 and Section 4.4.2.
Figure 7 shows the CFG-based Generator construction of the web-filter
NSF. It is constructed based on the NSF-Facing Interface Data Model
in [nsf-facing-inf-dm]. According to Figure 7, the security manager
can express productions for each clause as in following CFG:
1. [cont_name] -> [cont_name_data]
2. [cont_name_data] -> block_web
3. [cont_ipv4] -> [cont_ipv4][cont_ipv4] (Allow duplication)
4. [cont_ipv4] -> [cont_ipv4_data]
5. [cont_ipv4_data] -> 10.0.0.1 | 10.0.0.3
6. [cont_url] -> [cont_url][cont_url] (Allow duplication)
7. [cont_url] -> [cont_url_data]
8. [cont_url_data] -> harm.com | illegal.com
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9. [cont_action] -> [cont_action_data]
10. [cont_action_data] -> drop
11. [struct_packet] -> [cont_ipv4]
12. [struct_payload] -> [cont_url]
13. [struct_cond] ->
[struct_packet][struct_payload]
14. [struct_rules] -> [struct_cond][cont_action]
15. [struct_i2nsf] -> [cont_name][struct_rules]
Then, Generator generates a low-level policy by using the above CFG.
The low-level policy is generated by the following process:
1. Start: [struct_i2nsf]
2. Production 15: [cont_name][struct_rules]
3. Production 1: [cont_name_data][struct_rules]
4. Production 2: block_web[struct_rules]
5. Production 14: block_web[struct_cond][cont_action]
6. Production 13: block_web[struct_packet][struct_payload][cont_action]
7. Production 11: block_web[cont_ipv4][struct_payload]
[cont_action]
8. Production 3: block_web[cont_ipv4][cont_ipv4][struct_payload]
condition>[cont_action]
9. Production 4: block_web[cont_ipv4_data][cont_ipv4_dat
a][struct_payload][cont_action]
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10. Production 5: block_web10.0.0.110.0.0.3[struct_payload][cont_action]
11. Production 12: block_web10.0.0.110.0.0.3[cont_url][cont_action]
12. Production 6: block_web10.0.0.110.0.0.3[cont_url][cont_url][cont_actio
n]
13. Production 7: block_web10.0.0.110.0.0.3[cont_url_data][cont_url_data]<
/payload>[cont_action]
14. Production 8: block_web10.0.0.110.0.0.3harm.comillegal.com
condition>[cont_action]
15. Production 9: block_web10.0.0.110.0.0.3harm.comillegal.com
condition>[cont_action_data]
16. Production 10: block_web10.0.0.110.0.0.3harm.comillegal.com<
/condition>drop
The last production has no non-terminal state, and the low-level
policy is completely generated. Figure 8 shows the generated low-
level policy where tab characters and newline characters are added.
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+-----------------------------------------------------+
| +----------+ +----------+ +----------+ +----------+ |
Content | | Rule | | Source | | URL | | Drop | |
Production | | Name | | IPv4 | | Category | | Action | |
| +-----+----+ +-----+----+ +----+-----+ +----+-----+ |
| | | | | |
+--------------------+-----------+--------------------+
| | | |
V V V V
+-------+------------+-----------+------------+-------+
| | | | | |
| | V V | |
| | +----------+ +----------+ | |
| | | Packet | | Payload | | |
| | | Clause | | Clause | | |
| | +-----+----+ +----+-----+ | |
| | | | | |
| | V V | |
| | +---------------+ | |
| | | Condition | | |
Structure | | | Clause | | |
Production | | +-------+-------+ | |
| | | | |
| | V V |
| | +----------------------+ |
| | | Rule Clause | |
| | +-----------+----------+ |
| | | |
| V V |
| +-----------------------------------------+ |
| | I2NSF Clause | |
| +--------------------+--------------------+ |
| | |
+--------------------------+--------------------------+
|
V
Low-Level Policy
Figure 7: Generator Construction for Web-Filter NSF
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block_web
10.0.0.1
10.0.0.3
harm.com
illegal.com
drop
Figure 8: Example of Low-Level Policy
5. Implementation Considerations
The implementation considerations in this document include the
following three: "data model auto-adaptation", "data conversion", and
"policy provisioning".
5.1. Data Model Auto-adaptation
Security Controller which acts as the intermediary MUST process the
data according to the data model of the connected interfaces.
However, the data model can be changed flexibly depending on the
situation, and Security Controller may adapt to the change.
Therefore, Security Controller can be implemented for convenience so
that the security policy translator can easily adapt to the change of
the data model.
The translator constructs and uses the DFA to adapt to Consumer-
Facing Interface Data Model. In addition, the CFG is constructed and
used to adapt to NSF-Facing Interface Data Model. Both the DFA and
the CFG follow the same tree structure of YANG Data Model.
The DFA starts at the a node and expands operations by changing the
state according to the input. Based on the YANG Data Model, a
container node is defined as a middle state and a leaf node is
defined as an extractor node. After that, if the nodes are connected
in the same way as the hierarchical structure of the data model,
Security Controller can automatically construct the DFA. The DFA can
be conveniently built by investigating the link structure using the
stack, starting with the root node.
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The CFG starts at the leaf nodes and is grouped into clauses until
all the nodes are merged into one node. A leaf node is defined as
the content production, and a container node is defined as the
structure production. After that, if the nodes are connected in the
same way as the hierarchy of the data model, Security Controller can
automatically construct the CFG. The CFG can be conveniently
constructed by investigating the link structure using the priority
queue data, starting with the leaf nodes.
5.2. Data Conversion
Security Controller requires the ability to materialize the abstract
data in the high-level security policy and forward it to NSFs.
Security Controller can receive endpoint information as keywords
through the high-level security policy. At this time, if the
endpoint information corresponding to the keyword is mapped and the
query is transmitted to the NSF Database, the NSF Database can be
conveniently registered with necessary information for data
conversion. When a policy tries to establish a policy through the
keyword, Security Controller searches the details corresponding to
the keyword registered in the NSF Database and converts the keywords
into the appropriate and specified data.
5.3. Policy Provisioning
This document stated that policy provisioning function is necessary
to enable users without expert security knowledge to create policies.
Policy provisioning is determined by the capability of the NSF. If
the NSF has information about the capability in the policy, the
probability of selection increases.
Most importantly, selected NSFs may be able to performe all
capabilities in the security policy. This document recommends a
study of policy provisioning algorithms that are highly efficient and
can satisfy all capabilities in the security policy.
6. Features of Policy Translator Design
First, by showing a visualized translator structure, the security
manager can handle various policy changes. Translator can be shown
by visualizing DFA and Context-free Grammar so that the manager can
easily understand the structure of Policy Translator.
Second, if I2NSF User only keeps the hierarchy of the data model,
I2NSF User can freely create high-level policies. In the case of
DFA, data extraction can be performed in the same way even if the
order of input is changed. The design of the policy translator is
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more flexible than the existing method that works by keeping the tag
's position and order exactly.
Third, the structure of Policy Translator can be updated even while
Policy Translator is operating. Because Policy Translator is
modularized, the translator can adapt to changes in the NSF
capability while the I2NSF framework is running. The function of
changing the translator's structure can be provided through
Registration Interface.
7. Security Considerations
There is no security concern in the proposed security policy
translator as long as the I2NSF interfaces (i.e., Consumer-Facing
Interface, NSF-Facing Interface, and Registration Interface) are
protected by secure communication channels.
8. Acknowledgments
This work was supported by Institute for Information & communications
Technology Promotion (IITP) grant funded by the Korea MSIT (Ministry
of Science and ICT) (R-20160222-002755, Cloud based Security
Intelligence Technology Development for the Customized Security
Service Provisioning).
This work was supported in part by the MSIT under the ITRC
(Information Technology Research Center) support program (IITP-
2018-2017-0-01633) supervised by the IITP.
9. References
9.1. Normative References
[Automata]
Peter, L., "Formal Languages and Automata, 6th Edition",
January 2016.
[RFC6020] Bjorklund, M., "YANG - A Data Modeling Language for the
Network Configuration Protocol (NETCONF)", RFC 6020,
October 2010.
[RFC6241] Enns, R., Bjorklund, M., Schoenwaelder, J., and A.
Bierman, "Network Configuration Protocol (NETCONF)",
RFC 6241, June 2011.
[RFC8040] Bierman, A., Bjorklund, M., and K. Watsen, "RESTCONF
Protocol", RFC 8040, January 2017.
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[RFC8329] Lopez, D., Lopez, E., Dunbar, L., Strassner, J., and R.
Kumar, "Framework for Interface to Network Security
Functions", RFC 8329, February 2018.
[XML] W3C, "On Views and XML (Extensible Markup Language)", June
1999.
9.2. Informative References
[consumer-facing-inf-dm]
Jeong, J., Kim, E., Ahn, T., Kumar, R., and S. Hares,
"I2NSF Consumer-Facing Interface YANG Data Model", draft-
ietf-i2nsf-consumer-facing-interface-dm-03 (work in
progress), March 2019.
[i2nsf-terminology]
Hares, S., Strassner, J., Lopez, D., Xia, L., and H.
Birkholz, "Interface to Network Security Functions (I2NSF)
Terminology", draft-ietf-i2nsf-terminology-07 (work in
progress), July 2019.
[nsf-facing-inf-dm]
Kim, J., Jeong, J., Park, J., Hares, S., and Q. Lin,
"I2NSF Network Security Function-Facing Interface YANG
Data Model", draft-ietf-i2nsf-nsf-facing-interface-dm-03
(work in progress), March 2019.
[registration-inf-dm]
Hyun, S., Jeong, J., Roh, T., Wi, S., and J. Park, "I2NSF
Registration Interface YANG Data Model", draft-ietf-i2nsf-
registration-interface-dm-02 (work in progress), March
2019.
[XSLT] W3C, "Extensible Stylesheet Language Transformations
(XSLT) Version 1.0", November 1999.
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Appendix A. Changes from draft-yang-i2nsf-security-policy-
translation-02
The following changes are made from draft-yang-i2nsf-security-policy-
translation-02:
o Section 4.3.2 is added for describing 'NSF Database'. This
section reinforces the ambiguous description of the NSF Database.
o Section 5 is added for describing 'Implementation Considerations'.
This section provides guidelines for a convenient implementation
of security policy translator.
Authors' Addresses
Jinhyuk Yang
Department of Computer Engineering
Sungkyunkwan University
2066 Seobu-Ro, Jangan-Gu
Suwon, Gyeonggi-Do 16419
Republic of Korea
Phone: +82 10 8520 8039
EMail: jin.hyuk@skku.edu
Jaehoon Paul Jeong
Department of Software
Sungkyunkwan University
2066 Seobu-Ro, Jangan-Gu
Suwon, Gyeonggi-Do 16419
Republic of Korea
Phone: +82 31 299 4957
Fax: +82 31 290 7996
EMail: pauljeong@skku.edu
URI: http://iotlab.skku.edu/people-jaehoon-jeong.php
Jinyong Tim Kim
Department of Computer Engineering
Sungkyunkwan University
2066 Seobu-Ro, Jangan-Gu
Suwon, Gyeonggi-Do 16419
Republic of Korea
Phone: +82 10 8273 0930
EMail: timkim@skku.edu
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