SlideShare a Scribd company logo
11World-Leading Research with Real-World Impact!
Prosunjit Biswas, Ravi Sandhu and Ram Krishnan
Department of Computer Science
Department of Electrical and Computer Engineering
University of Texas, San Antonio
Institute for Cyber Security
ABAC’17, March 24, 2017, Scottsdale, AZ, USA
Attribute Transformation for
Attribute-Based Access Control
22World-Leading Research with Real-World Impact!
Outline
Summary
Motivation
Attribute Transformation
Attribute Reduction
Attribute Expansion
Conclusion
Q/A
33World-Leading Research with Real-World Impact!
Summary
We have presented a concept of attribute transformation and specify two types of
transformation---attribute reduction and attribute expansion.
44World-Leading Research with Real-World Impact!
Motivation
Attribute explosion!
Figure 1: Attributes defined for OpenStack Virtual Machines
55World-Leading Research with Real-World Impact!
Motivation (continuing)
incurs
difficulties in managing
Attribute Explosion
authorization policies attribute-value assignments
66World-Leading Research with Real-World Impact!
Motivation (continuing)
We cannot get rid of attributes we need.
But we can manage
with
Attribute Transformation
77World-Leading Research with Real-World Impact!
Attribute Transformation (assumptions)
Attribute types
Non-policy Attributes Policy Attributes
Examples:
Object attributes (Non-policy):
size, created_by, shared, location
Object attributes (Policy):
sensitivity, security-label
Assumptions:
Non-policy Attributes Policy Attributes = φ∩
Non-policy Attributes >> Policy Attributes
88
Attribute Transformation
World-Leading Research with Real-World Impact!
Types of attribute transformation
Reduction
(Non-policy Attr → Policy Attr)
Expansion
(Policy Attr → Policy Attr)
Attribute Transformation is the process of transforming one set of attribute-value
assignments into another set of assignments.
Attribute Reduction
The process of transforming non-policy attribute-value assignments into policy
attributes-value assignments.
9
size(f1)=100MB
created-by(f1) =
system-d
location(f1)=
/log/system-log
security-label(f) =
sensitiveshared(f1)= false
Deriving assignments
Derived assignments Effective assignments
Non-policy attributes
Policy attributes
Attribute
transformation
security-label(f) =
sensitive
1010
Attribute Reduction (motivation)
World-Leading Research with Real-World Impact!
Motivation from literature:
2. Concepts of Dynamic
roles by Kuhn, Coyne and
Weil [2]
1. Attribute-Based User-Role
Assignment [1]
Attribute Reduction (usefulness)
Useful for
Abstraction Modular design Hierarchical policy
11
Can-read ≡ security-label(o) = sensitive role(u)=managerʌ
VM-mapping ≡ resource-type(o) = VM image-type(o) = corporateʌ →
security-label(o) = sensitive
Firewall-mapping ≡ resource-type(o) = firewall protocol(o) = UDPʌ ʌ
network(o) = internal → security-label(o) = sensitive
Attribute Reduction (usefulness)
12
Authorization policy with Policy attributes:
Mapping rules with Non-policy Attributes:
Attribute Reduction (mapping rules)
13
Example of mapping rule:
file-length(f) = 100 MB ʌ created-by(f) = system-d ʌ is-
shared(f) = false → security-label(f) = sensitive
Attribute Reduction (issues)
resource-
type(o) = VM
encryption(o)
= plain
security-label(o)
= regular
resource-type(o)
= VM
image-type(o)
= corporate
mapping1
mapping2
Conflicts resulting from multiple mappings
14
security-label(o)
= sensitive
resource-type(o) =
VM
encryption(o) =
plain
security-label(o) =
regular
mapping1
security-label(o) =
sensitive
Derivedvalue
Explicitlyassigned
value
Attribute Reduction (issues)
Conflicts resulting from assigned and derived values
15
is-a-veteran(u)
= True
benefits(u) =
{b1,b2}
skills(u) =
{skill1, skill2}
Deriving assignments
Derived assignments Resulting assignments
Policy attributes
Policy attributes
leadership(u)
= True
Policy attributes
is-a-veteran(u)
= True
Attribute Expansion
Expansion
16
The process of transforming policy attribute-value assignments into a
different set of policy attributes-value assignments.
skills(u) =
{skill1, skill2}
Attribute Expansion (motivation)
Motivation from literature:
1. Hierarchical Group and Attribute-Based Access Control (HGABAC) [3]
17
Conclusion
What next?
- Other forms of Attribute Transformation
- Chain of Attribute Transformation
- Fitting Attribute Transformation in ABAC models
18
References
1. Servos, Daniel, and Sylvia L. Osborn. "HGABAC: Towards a formal model of hierarchical attribute-based
access control." International Symposium on Foundations and Practice of Security. Springer International
Publishing, 2014.
2. Kuhn, D. Richard, Edward J. Coyne, and Timothy R. Weil. "Adding attributes to role-based access control."
Computer 43.6 (2010): 79-81.
3. Servos, Daniel, and Sylvia L. Osborn. "HGABAC: Towards a formal model of hierarchical attribute-based
access control." International Symposium on Foundations and Practice of Security. Springer International
Publishing, 2014.
19
20

More Related Content

Similar to Abac17 prosun-slides

DSDT meetup July 2021
DSDT meetup July 2021DSDT meetup July 2021
DSDT meetup July 2021
DSDT_MTL
 
Mainproject
MainprojectMainproject
Mainproject
Ashley Mathew
 
Mainproject
MainprojectMainproject
Mainproject
Ashley Mathew
 
Events, Streams, Devops and Speed - The Next Generation of Application Archit...
Events, Streams, Devops and Speed - The Next Generation of Application Archit...Events, Streams, Devops and Speed - The Next Generation of Application Archit...
Events, Streams, Devops and Speed - The Next Generation of Application Archit...
confluent
 
Security patterns and model driven architecture
Security patterns and model driven architectureSecurity patterns and model driven architecture
Security patterns and model driven architecture
bdemchak
 
Obscenity Detection in Images
Obscenity Detection in ImagesObscenity Detection in Images
Obscenity Detection in Images
Anil Kumar Gupta
 
230208 MLOps Getting from Good to Great.pptx
230208 MLOps Getting from Good to Great.pptx230208 MLOps Getting from Good to Great.pptx
230208 MLOps Getting from Good to Great.pptx
Arthur240715
 
Keynote at IWLS 2017
Keynote at IWLS 2017Keynote at IWLS 2017
Keynote at IWLS 2017
Manish Pandey
 
Modern recommender system in large content website
Modern recommender system in large content websiteModern recommender system in large content website
Modern recommender system in large content website
Cyrus Chien-Ching Chiu
 
Synopsis_kamlesh
Synopsis_kamleshSynopsis_kamlesh
Synopsis_kamlesh
KAMLESH HINGWE
 
Software Architecture - Principles Patterns and Practices - OSI Days Workshop...
Software Architecture - Principles Patterns and Practices - OSI Days Workshop...Software Architecture - Principles Patterns and Practices - OSI Days Workshop...
Software Architecture - Principles Patterns and Practices - OSI Days Workshop...
CodeOps Technologies LLP
 
Software Architecture - Quiz Questions
Software Architecture - Quiz QuestionsSoftware Architecture - Quiz Questions
Software Architecture - Quiz Questions
Ganesh Samarthyam
 
Software Architecture - Quiz Questions
Software Architecture - Quiz QuestionsSoftware Architecture - Quiz Questions
Software Architecture - Quiz Questions
CodeOps Technologies LLP
 
Software Architecture - Principles, Patterns and Practices - OSI Days - 2017
Software Architecture - Principles, Patterns and Practices - OSI Days - 2017Software Architecture - Principles, Patterns and Practices - OSI Days - 2017
Software Architecture - Principles, Patterns and Practices - OSI Days - 2017
CodeOps Technologies LLP
 
Introduction to Deep Learning and Tensorflow
Introduction to Deep Learning and TensorflowIntroduction to Deep Learning and Tensorflow
Introduction to Deep Learning and Tensorflow
Oswald Campesato
 
End-to-end Big Data Projects with Python - StampedeCon Big Data Conference 2017
End-to-end Big Data Projects with Python - StampedeCon Big Data Conference 2017End-to-end Big Data Projects with Python - StampedeCon Big Data Conference 2017
End-to-end Big Data Projects with Python - StampedeCon Big Data Conference 2017
StampedeCon
 
What does an event mean? Manage the meaning of your data! | Andreas Wombacher...
What does an event mean? Manage the meaning of your data! | Andreas Wombacher...What does an event mean? Manage the meaning of your data! | Andreas Wombacher...
What does an event mean? Manage the meaning of your data! | Andreas Wombacher...
HostedbyConfluent
 
Started from the Bottom: Exploiting Data Sources to Uncover ATT&CK Behaviors
Started from the Bottom: Exploiting Data Sources to Uncover ATT&CK BehaviorsStarted from the Bottom: Exploiting Data Sources to Uncover ATT&CK Behaviors
Started from the Bottom: Exploiting Data Sources to Uncover ATT&CK Behaviors
JamieWilliams130
 
Rutgers Cloud Seminar 2017
Rutgers Cloud Seminar 2017Rutgers Cloud Seminar 2017
Rutgers Cloud Seminar 2017
▫️Canturk▫️ ▪️Isci▪️
 
Rutgers Cloud Seminar 2017
Rutgers Cloud Seminar 2017Rutgers Cloud Seminar 2017
Rutgers Cloud Seminar 2017
Canturk Isci
 

Similar to Abac17 prosun-slides (20)

DSDT meetup July 2021
DSDT meetup July 2021DSDT meetup July 2021
DSDT meetup July 2021
 
Mainproject
MainprojectMainproject
Mainproject
 
Mainproject
MainprojectMainproject
Mainproject
 
Events, Streams, Devops and Speed - The Next Generation of Application Archit...
Events, Streams, Devops and Speed - The Next Generation of Application Archit...Events, Streams, Devops and Speed - The Next Generation of Application Archit...
Events, Streams, Devops and Speed - The Next Generation of Application Archit...
 
Security patterns and model driven architecture
Security patterns and model driven architectureSecurity patterns and model driven architecture
Security patterns and model driven architecture
 
Obscenity Detection in Images
Obscenity Detection in ImagesObscenity Detection in Images
Obscenity Detection in Images
 
230208 MLOps Getting from Good to Great.pptx
230208 MLOps Getting from Good to Great.pptx230208 MLOps Getting from Good to Great.pptx
230208 MLOps Getting from Good to Great.pptx
 
Keynote at IWLS 2017
Keynote at IWLS 2017Keynote at IWLS 2017
Keynote at IWLS 2017
 
Modern recommender system in large content website
Modern recommender system in large content websiteModern recommender system in large content website
Modern recommender system in large content website
 
Synopsis_kamlesh
Synopsis_kamleshSynopsis_kamlesh
Synopsis_kamlesh
 
Software Architecture - Principles Patterns and Practices - OSI Days Workshop...
Software Architecture - Principles Patterns and Practices - OSI Days Workshop...Software Architecture - Principles Patterns and Practices - OSI Days Workshop...
Software Architecture - Principles Patterns and Practices - OSI Days Workshop...
 
Software Architecture - Quiz Questions
Software Architecture - Quiz QuestionsSoftware Architecture - Quiz Questions
Software Architecture - Quiz Questions
 
Software Architecture - Quiz Questions
Software Architecture - Quiz QuestionsSoftware Architecture - Quiz Questions
Software Architecture - Quiz Questions
 
Software Architecture - Principles, Patterns and Practices - OSI Days - 2017
Software Architecture - Principles, Patterns and Practices - OSI Days - 2017Software Architecture - Principles, Patterns and Practices - OSI Days - 2017
Software Architecture - Principles, Patterns and Practices - OSI Days - 2017
 
Introduction to Deep Learning and Tensorflow
Introduction to Deep Learning and TensorflowIntroduction to Deep Learning and Tensorflow
Introduction to Deep Learning and Tensorflow
 
End-to-end Big Data Projects with Python - StampedeCon Big Data Conference 2017
End-to-end Big Data Projects with Python - StampedeCon Big Data Conference 2017End-to-end Big Data Projects with Python - StampedeCon Big Data Conference 2017
End-to-end Big Data Projects with Python - StampedeCon Big Data Conference 2017
 
What does an event mean? Manage the meaning of your data! | Andreas Wombacher...
What does an event mean? Manage the meaning of your data! | Andreas Wombacher...What does an event mean? Manage the meaning of your data! | Andreas Wombacher...
What does an event mean? Manage the meaning of your data! | Andreas Wombacher...
 
Started from the Bottom: Exploiting Data Sources to Uncover ATT&CK Behaviors
Started from the Bottom: Exploiting Data Sources to Uncover ATT&CK BehaviorsStarted from the Bottom: Exploiting Data Sources to Uncover ATT&CK Behaviors
Started from the Bottom: Exploiting Data Sources to Uncover ATT&CK Behaviors
 
Rutgers Cloud Seminar 2017
Rutgers Cloud Seminar 2017Rutgers Cloud Seminar 2017
Rutgers Cloud Seminar 2017
 
Rutgers Cloud Seminar 2017
Rutgers Cloud Seminar 2017Rutgers Cloud Seminar 2017
Rutgers Cloud Seminar 2017
 

More from UT, San Antonio

digital certificate - types and formats
digital certificate - types and formatsdigital certificate - types and formats
digital certificate - types and formats
UT, San Antonio
 
Saml metadata
Saml metadataSaml metadata
Saml metadata
UT, San Antonio
 
Static Analysis with Sonarlint
Static Analysis with SonarlintStatic Analysis with Sonarlint
Static Analysis with Sonarlint
UT, San Antonio
 
Shellshock- from bug towards vulnerability
Shellshock- from bug towards vulnerabilityShellshock- from bug towards vulnerability
Shellshock- from bug towards vulnerability
UT, San Antonio
 
Recitation
RecitationRecitation
Recitation
UT, San Antonio
 
Recitation
RecitationRecitation
Recitation
UT, San Antonio
 
Big Data Processing: Performance Gain Through In-Memory Computation
Big Data Processing: Performance Gain Through In-Memory ComputationBig Data Processing: Performance Gain Through In-Memory Computation
Big Data Processing: Performance Gain Through In-Memory Computation
UT, San Antonio
 
Enumerated authorization policy ABAC (EP-ABAC) model
Enumerated authorization policy ABAC (EP-ABAC) modelEnumerated authorization policy ABAC (EP-ABAC) model
Enumerated authorization policy ABAC (EP-ABAC) model
UT, San Antonio
 
Where is my Privacy presentation slideshow (one page only)
Where is my Privacy presentation slideshow (one page only)Where is my Privacy presentation slideshow (one page only)
Where is my Privacy presentation slideshow (one page only)
UT, San Antonio
 
Three month course
Three month courseThree month course
Three month course
UT, San Antonio
 
Zerovm backgroud
Zerovm backgroudZerovm backgroud
Zerovm backgroud
UT, San Antonio
 
Security_of_openstack_keystone
Security_of_openstack_keystoneSecurity_of_openstack_keystone
Security_of_openstack_keystone
UT, San Antonio
 
Research seminar group_1_prosunjit
Research seminar group_1_prosunjitResearch seminar group_1_prosunjit
Research seminar group_1_prosunjit
UT, San Antonio
 
Ksi
KsiKsi
Attribute Based Encryption
Attribute Based EncryptionAttribute Based Encryption
Attribute Based Encryption
UT, San Antonio
 
Final Project Transciption Factor DNA binding Prediction
Final Project Transciption Factor DNA binding Prediction Final Project Transciption Factor DNA binding Prediction
Final Project Transciption Factor DNA binding Prediction
UT, San Antonio
 
Cyber Security Exam 2
Cyber Security Exam 2Cyber Security Exam 2
Cyber Security Exam 2
UT, San Antonio
 
Transcription Factor DNA Binding Prediction
Transcription Factor DNA Binding PredictionTranscription Factor DNA Binding Prediction
Transcription Factor DNA Binding Prediction
UT, San Antonio
 
Transcription Factor DNA Binding Prediction
Transcription Factor DNA Binding PredictionTranscription Factor DNA Binding Prediction
Transcription Factor DNA Binding Prediction
UT, San Antonio
 

More from UT, San Antonio (20)

digital certificate - types and formats
digital certificate - types and formatsdigital certificate - types and formats
digital certificate - types and formats
 
Saml metadata
Saml metadataSaml metadata
Saml metadata
 
Static Analysis with Sonarlint
Static Analysis with SonarlintStatic Analysis with Sonarlint
Static Analysis with Sonarlint
 
Shellshock- from bug towards vulnerability
Shellshock- from bug towards vulnerabilityShellshock- from bug towards vulnerability
Shellshock- from bug towards vulnerability
 
Recitation
RecitationRecitation
Recitation
 
Recitation
RecitationRecitation
Recitation
 
Big Data Processing: Performance Gain Through In-Memory Computation
Big Data Processing: Performance Gain Through In-Memory ComputationBig Data Processing: Performance Gain Through In-Memory Computation
Big Data Processing: Performance Gain Through In-Memory Computation
 
Enumerated authorization policy ABAC (EP-ABAC) model
Enumerated authorization policy ABAC (EP-ABAC) modelEnumerated authorization policy ABAC (EP-ABAC) model
Enumerated authorization policy ABAC (EP-ABAC) model
 
Where is my Privacy presentation slideshow (one page only)
Where is my Privacy presentation slideshow (one page only)Where is my Privacy presentation slideshow (one page only)
Where is my Privacy presentation slideshow (one page only)
 
Three month course
Three month courseThree month course
Three month course
 
One month-syllabus
One month-syllabusOne month-syllabus
One month-syllabus
 
Zerovm backgroud
Zerovm backgroudZerovm backgroud
Zerovm backgroud
 
Security_of_openstack_keystone
Security_of_openstack_keystoneSecurity_of_openstack_keystone
Security_of_openstack_keystone
 
Research seminar group_1_prosunjit
Research seminar group_1_prosunjitResearch seminar group_1_prosunjit
Research seminar group_1_prosunjit
 
Ksi
KsiKsi
Ksi
 
Attribute Based Encryption
Attribute Based EncryptionAttribute Based Encryption
Attribute Based Encryption
 
Final Project Transciption Factor DNA binding Prediction
Final Project Transciption Factor DNA binding Prediction Final Project Transciption Factor DNA binding Prediction
Final Project Transciption Factor DNA binding Prediction
 
Cyber Security Exam 2
Cyber Security Exam 2Cyber Security Exam 2
Cyber Security Exam 2
 
Transcription Factor DNA Binding Prediction
Transcription Factor DNA Binding PredictionTranscription Factor DNA Binding Prediction
Transcription Factor DNA Binding Prediction
 
Transcription Factor DNA Binding Prediction
Transcription Factor DNA Binding PredictionTranscription Factor DNA Binding Prediction
Transcription Factor DNA Binding Prediction
 

Recently uploaded

Welding Metallurgy Ferrous Materials.pdf
Welding Metallurgy Ferrous Materials.pdfWelding Metallurgy Ferrous Materials.pdf
Welding Metallurgy Ferrous Materials.pdf
AjmalKhan50578
 
Software Engineering and Project Management - Introduction, Modeling Concepts...
Software Engineering and Project Management - Introduction, Modeling Concepts...Software Engineering and Project Management - Introduction, Modeling Concepts...
Software Engineering and Project Management - Introduction, Modeling Concepts...
Prakhyath Rai
 
Generative AI leverages algorithms to create various forms of content
Generative AI leverages algorithms to create various forms of contentGenerative AI leverages algorithms to create various forms of content
Generative AI leverages algorithms to create various forms of content
Hitesh Mohapatra
 
Computational Engineering IITH Presentation
Computational Engineering IITH PresentationComputational Engineering IITH Presentation
Computational Engineering IITH Presentation
co23btech11018
 
Manufacturing Process of molasses based distillery ppt.pptx
Manufacturing Process of molasses based distillery ppt.pptxManufacturing Process of molasses based distillery ppt.pptx
Manufacturing Process of molasses based distillery ppt.pptx
Madan Karki
 
An improved modulation technique suitable for a three level flying capacitor ...
An improved modulation technique suitable for a three level flying capacitor ...An improved modulation technique suitable for a three level flying capacitor ...
An improved modulation technique suitable for a three level flying capacitor ...
IJECEIAES
 
Software Quality Assurance-se412-v11.ppt
Software Quality Assurance-se412-v11.pptSoftware Quality Assurance-se412-v11.ppt
Software Quality Assurance-se412-v11.ppt
TaghreedAltamimi
 
一比一原版(CalArts毕业证)加利福尼亚艺术学院毕业证如何办理
一比一原版(CalArts毕业证)加利福尼亚艺术学院毕业证如何办理一比一原版(CalArts毕业证)加利福尼亚艺术学院毕业证如何办理
一比一原版(CalArts毕业证)加利福尼亚艺术学院毕业证如何办理
ecqow
 
ITSM Integration with MuleSoft.pptx
ITSM  Integration with MuleSoft.pptxITSM  Integration with MuleSoft.pptx
ITSM Integration with MuleSoft.pptx
VANDANAMOHANGOUDA
 
Redefining brain tumor segmentation: a cutting-edge convolutional neural netw...
Redefining brain tumor segmentation: a cutting-edge convolutional neural netw...Redefining brain tumor segmentation: a cutting-edge convolutional neural netw...
Redefining brain tumor segmentation: a cutting-edge convolutional neural netw...
IJECEIAES
 
原版制作(Humboldt毕业证书)柏林大学毕业证学位证一模一样
原版制作(Humboldt毕业证书)柏林大学毕业证学位证一模一样原版制作(Humboldt毕业证书)柏林大学毕业证学位证一模一样
原版制作(Humboldt毕业证书)柏林大学毕业证学位证一模一样
ydzowc
 
Certificates - Mahmoud Mohamed Moursi Ahmed
Certificates - Mahmoud Mohamed Moursi AhmedCertificates - Mahmoud Mohamed Moursi Ahmed
Certificates - Mahmoud Mohamed Moursi Ahmed
Mahmoud Morsy
 
BRAIN TUMOR DETECTION for seminar ppt.pdf
BRAIN TUMOR DETECTION for seminar ppt.pdfBRAIN TUMOR DETECTION for seminar ppt.pdf
BRAIN TUMOR DETECTION for seminar ppt.pdf
LAXMAREDDY22
 
Null Bangalore | Pentesters Approach to AWS IAM
Null Bangalore | Pentesters Approach to AWS IAMNull Bangalore | Pentesters Approach to AWS IAM
Null Bangalore | Pentesters Approach to AWS IAM
Divyanshu
 
Curve Fitting in Numerical Methods Regression
Curve Fitting in Numerical Methods RegressionCurve Fitting in Numerical Methods Regression
Curve Fitting in Numerical Methods Regression
Nada Hikmah
 
Embedded machine learning-based road conditions and driving behavior monitoring
Embedded machine learning-based road conditions and driving behavior monitoringEmbedded machine learning-based road conditions and driving behavior monitoring
Embedded machine learning-based road conditions and driving behavior monitoring
IJECEIAES
 
Optimizing Gradle Builds - Gradle DPE Tour Berlin 2024
Optimizing Gradle Builds - Gradle DPE Tour Berlin 2024Optimizing Gradle Builds - Gradle DPE Tour Berlin 2024
Optimizing Gradle Builds - Gradle DPE Tour Berlin 2024
Sinan KOZAK
 
Applications of artificial Intelligence in Mechanical Engineering.pdf
Applications of artificial Intelligence in Mechanical Engineering.pdfApplications of artificial Intelligence in Mechanical Engineering.pdf
Applications of artificial Intelligence in Mechanical Engineering.pdf
Atif Razi
 
Comparative analysis between traditional aquaponics and reconstructed aquapon...
Comparative analysis between traditional aquaponics and reconstructed aquapon...Comparative analysis between traditional aquaponics and reconstructed aquapon...
Comparative analysis between traditional aquaponics and reconstructed aquapon...
bijceesjournal
 
artificial intelligence and data science contents.pptx
artificial intelligence and data science contents.pptxartificial intelligence and data science contents.pptx
artificial intelligence and data science contents.pptx
GauravCar
 

Recently uploaded (20)

Welding Metallurgy Ferrous Materials.pdf
Welding Metallurgy Ferrous Materials.pdfWelding Metallurgy Ferrous Materials.pdf
Welding Metallurgy Ferrous Materials.pdf
 
Software Engineering and Project Management - Introduction, Modeling Concepts...
Software Engineering and Project Management - Introduction, Modeling Concepts...Software Engineering and Project Management - Introduction, Modeling Concepts...
Software Engineering and Project Management - Introduction, Modeling Concepts...
 
Generative AI leverages algorithms to create various forms of content
Generative AI leverages algorithms to create various forms of contentGenerative AI leverages algorithms to create various forms of content
Generative AI leverages algorithms to create various forms of content
 
Computational Engineering IITH Presentation
Computational Engineering IITH PresentationComputational Engineering IITH Presentation
Computational Engineering IITH Presentation
 
Manufacturing Process of molasses based distillery ppt.pptx
Manufacturing Process of molasses based distillery ppt.pptxManufacturing Process of molasses based distillery ppt.pptx
Manufacturing Process of molasses based distillery ppt.pptx
 
An improved modulation technique suitable for a three level flying capacitor ...
An improved modulation technique suitable for a three level flying capacitor ...An improved modulation technique suitable for a three level flying capacitor ...
An improved modulation technique suitable for a three level flying capacitor ...
 
Software Quality Assurance-se412-v11.ppt
Software Quality Assurance-se412-v11.pptSoftware Quality Assurance-se412-v11.ppt
Software Quality Assurance-se412-v11.ppt
 
一比一原版(CalArts毕业证)加利福尼亚艺术学院毕业证如何办理
一比一原版(CalArts毕业证)加利福尼亚艺术学院毕业证如何办理一比一原版(CalArts毕业证)加利福尼亚艺术学院毕业证如何办理
一比一原版(CalArts毕业证)加利福尼亚艺术学院毕业证如何办理
 
ITSM Integration with MuleSoft.pptx
ITSM  Integration with MuleSoft.pptxITSM  Integration with MuleSoft.pptx
ITSM Integration with MuleSoft.pptx
 
Redefining brain tumor segmentation: a cutting-edge convolutional neural netw...
Redefining brain tumor segmentation: a cutting-edge convolutional neural netw...Redefining brain tumor segmentation: a cutting-edge convolutional neural netw...
Redefining brain tumor segmentation: a cutting-edge convolutional neural netw...
 
原版制作(Humboldt毕业证书)柏林大学毕业证学位证一模一样
原版制作(Humboldt毕业证书)柏林大学毕业证学位证一模一样原版制作(Humboldt毕业证书)柏林大学毕业证学位证一模一样
原版制作(Humboldt毕业证书)柏林大学毕业证学位证一模一样
 
Certificates - Mahmoud Mohamed Moursi Ahmed
Certificates - Mahmoud Mohamed Moursi AhmedCertificates - Mahmoud Mohamed Moursi Ahmed
Certificates - Mahmoud Mohamed Moursi Ahmed
 
BRAIN TUMOR DETECTION for seminar ppt.pdf
BRAIN TUMOR DETECTION for seminar ppt.pdfBRAIN TUMOR DETECTION for seminar ppt.pdf
BRAIN TUMOR DETECTION for seminar ppt.pdf
 
Null Bangalore | Pentesters Approach to AWS IAM
Null Bangalore | Pentesters Approach to AWS IAMNull Bangalore | Pentesters Approach to AWS IAM
Null Bangalore | Pentesters Approach to AWS IAM
 
Curve Fitting in Numerical Methods Regression
Curve Fitting in Numerical Methods RegressionCurve Fitting in Numerical Methods Regression
Curve Fitting in Numerical Methods Regression
 
Embedded machine learning-based road conditions and driving behavior monitoring
Embedded machine learning-based road conditions and driving behavior monitoringEmbedded machine learning-based road conditions and driving behavior monitoring
Embedded machine learning-based road conditions and driving behavior monitoring
 
Optimizing Gradle Builds - Gradle DPE Tour Berlin 2024
Optimizing Gradle Builds - Gradle DPE Tour Berlin 2024Optimizing Gradle Builds - Gradle DPE Tour Berlin 2024
Optimizing Gradle Builds - Gradle DPE Tour Berlin 2024
 
Applications of artificial Intelligence in Mechanical Engineering.pdf
Applications of artificial Intelligence in Mechanical Engineering.pdfApplications of artificial Intelligence in Mechanical Engineering.pdf
Applications of artificial Intelligence in Mechanical Engineering.pdf
 
Comparative analysis between traditional aquaponics and reconstructed aquapon...
Comparative analysis between traditional aquaponics and reconstructed aquapon...Comparative analysis between traditional aquaponics and reconstructed aquapon...
Comparative analysis between traditional aquaponics and reconstructed aquapon...
 
artificial intelligence and data science contents.pptx
artificial intelligence and data science contents.pptxartificial intelligence and data science contents.pptx
artificial intelligence and data science contents.pptx
 

Abac17 prosun-slides

  • 1. 11World-Leading Research with Real-World Impact! Prosunjit Biswas, Ravi Sandhu and Ram Krishnan Department of Computer Science Department of Electrical and Computer Engineering University of Texas, San Antonio Institute for Cyber Security ABAC’17, March 24, 2017, Scottsdale, AZ, USA Attribute Transformation for Attribute-Based Access Control
  • 2. 22World-Leading Research with Real-World Impact! Outline Summary Motivation Attribute Transformation Attribute Reduction Attribute Expansion Conclusion Q/A
  • 3. 33World-Leading Research with Real-World Impact! Summary We have presented a concept of attribute transformation and specify two types of transformation---attribute reduction and attribute expansion.
  • 4. 44World-Leading Research with Real-World Impact! Motivation Attribute explosion! Figure 1: Attributes defined for OpenStack Virtual Machines
  • 5. 55World-Leading Research with Real-World Impact! Motivation (continuing) incurs difficulties in managing Attribute Explosion authorization policies attribute-value assignments
  • 6. 66World-Leading Research with Real-World Impact! Motivation (continuing) We cannot get rid of attributes we need. But we can manage with Attribute Transformation
  • 7. 77World-Leading Research with Real-World Impact! Attribute Transformation (assumptions) Attribute types Non-policy Attributes Policy Attributes Examples: Object attributes (Non-policy): size, created_by, shared, location Object attributes (Policy): sensitivity, security-label Assumptions: Non-policy Attributes Policy Attributes = φ∩ Non-policy Attributes >> Policy Attributes
  • 8. 88 Attribute Transformation World-Leading Research with Real-World Impact! Types of attribute transformation Reduction (Non-policy Attr → Policy Attr) Expansion (Policy Attr → Policy Attr) Attribute Transformation is the process of transforming one set of attribute-value assignments into another set of assignments.
  • 9. Attribute Reduction The process of transforming non-policy attribute-value assignments into policy attributes-value assignments. 9 size(f1)=100MB created-by(f1) = system-d location(f1)= /log/system-log security-label(f) = sensitiveshared(f1)= false Deriving assignments Derived assignments Effective assignments Non-policy attributes Policy attributes Attribute transformation security-label(f) = sensitive
  • 10. 1010 Attribute Reduction (motivation) World-Leading Research with Real-World Impact! Motivation from literature: 2. Concepts of Dynamic roles by Kuhn, Coyne and Weil [2] 1. Attribute-Based User-Role Assignment [1]
  • 11. Attribute Reduction (usefulness) Useful for Abstraction Modular design Hierarchical policy 11
  • 12. Can-read ≡ security-label(o) = sensitive role(u)=managerʌ VM-mapping ≡ resource-type(o) = VM image-type(o) = corporateʌ → security-label(o) = sensitive Firewall-mapping ≡ resource-type(o) = firewall protocol(o) = UDPʌ ʌ network(o) = internal → security-label(o) = sensitive Attribute Reduction (usefulness) 12 Authorization policy with Policy attributes: Mapping rules with Non-policy Attributes:
  • 13. Attribute Reduction (mapping rules) 13 Example of mapping rule: file-length(f) = 100 MB ʌ created-by(f) = system-d ʌ is- shared(f) = false → security-label(f) = sensitive
  • 14. Attribute Reduction (issues) resource- type(o) = VM encryption(o) = plain security-label(o) = regular resource-type(o) = VM image-type(o) = corporate mapping1 mapping2 Conflicts resulting from multiple mappings 14 security-label(o) = sensitive
  • 15. resource-type(o) = VM encryption(o) = plain security-label(o) = regular mapping1 security-label(o) = sensitive Derivedvalue Explicitlyassigned value Attribute Reduction (issues) Conflicts resulting from assigned and derived values 15
  • 16. is-a-veteran(u) = True benefits(u) = {b1,b2} skills(u) = {skill1, skill2} Deriving assignments Derived assignments Resulting assignments Policy attributes Policy attributes leadership(u) = True Policy attributes is-a-veteran(u) = True Attribute Expansion Expansion 16 The process of transforming policy attribute-value assignments into a different set of policy attributes-value assignments. skills(u) = {skill1, skill2}
  • 17. Attribute Expansion (motivation) Motivation from literature: 1. Hierarchical Group and Attribute-Based Access Control (HGABAC) [3] 17
  • 18. Conclusion What next? - Other forms of Attribute Transformation - Chain of Attribute Transformation - Fitting Attribute Transformation in ABAC models 18
  • 19. References 1. Servos, Daniel, and Sylvia L. Osborn. "HGABAC: Towards a formal model of hierarchical attribute-based access control." International Symposium on Foundations and Practice of Security. Springer International Publishing, 2014. 2. Kuhn, D. Richard, Edward J. Coyne, and Timothy R. Weil. "Adding attributes to role-based access control." Computer 43.6 (2010): 79-81. 3. Servos, Daniel, and Sylvia L. Osborn. "HGABAC: Towards a formal model of hierarchical attribute-based access control." International Symposium on Foundations and Practice of Security. Springer International Publishing, 2014. 19
  • 20. 20