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Ketan Kulkarni

dblp:75/4346 · DBLP profile ↗
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4ranked-venue papers
0as first author
0since 2021 · last 2013
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Security and privacy · 3Human-computer interaction and ubiquitous computing · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Network and information security
2 papers
Authentication and access control · 70% Network security · 30%
Computer networks
2 papers
Network management and operations · 100%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Network management and operations
configuration verification
0.222013
Detecting and Resolving Firewall Policy Anomalies · IEEE Trans. Dependable Secur. Comput. 2012
Discovery and Resolution of Anomalies in Web Access Control Policies · IEEE Trans. Dependable Secur. Comput. 2013
Authentication and access control
access control policy
0.212013
Discovery and Resolution of Anomalies in Web Access Control Policies · IEEE Trans. Dependable Secur. Comput. 2013
Authentication and access control › access control
web access control
0.212013
Discovery and Resolution of Anomalies in Web Access Control Policies · IEEE Trans. Dependable Secur. Comput. 2013
Network security
firewall
0.112012
Detecting and Resolving Firewall Policy Anomalies · IEEE Trans. Dependable Secur. Comput. 2012

Methods — techniques the papers use, named apart from their topics

visualization · 0.6policy-based segmentation · 0.3rule-based segmentation · 0.3grid-based representation · 0.3
YearPublicationVenuePosition
2013 Discovery and Resolution of Anomalies in Web Access Control Policies
abstract
Emerging computing technologies such as web services, service-oriented architecture, and cloud computing has enabled us to perform business services more efficiently and effectively. However, we still suffer from unintended security leakages by unauthorized actions in business services while providing more convenient services to Internet users through such a cutting-edge technological growth. Furthermore, designing and managing web access control policies are often error-prone due to the lack of effective analysis mechanisms and tools. In this paper, we represent an innovative policy anomaly analysis approach for web access control policies, focusing on extensible access control markup language policy. We introduce a policy-based segmentation technique to accurately identify policy anomalies and derive effective anomaly resolutions, along with an intuitive visualization representation of analysis results. We also discuss a proof-of-concept implementation of our method called XAnalyzer and demonstrate how our approach can efficiently discover and resolve policy anomalies.
Hongxin Hu, Gail-Joon Ahn, Ketan Kulkarni
IEEE Trans. Dependable Secur. Comput.3
2012 Detecting and Resolving Firewall Policy Anomalies
abstract
The advent of emerging computing technologies such as service-oriented architecture and cloud computing has enabled us to perform business services more efficiently and effectively. However, we still suffer from unintended security leakages by unauthorized actions in business services. Firewalls are the most widely deployed security mechanism to ensure the security of private networks in most businesses and institutions. The effectiveness of security protection provided by a firewall mainly depends on the quality of policy configured in the firewall. Unfortunately, designing and managing firewall policies are often error prone due to the complex nature of firewall configurations as well as the lack of systematic analysis mechanisms and tools. In this paper, we represent an innovative policy anomaly management framework for firewalls, adopting a rule-based segmentation technique to identify policy anomalies and derive effective anomaly resolutions. In particular, we articulate a grid-based representation technique, providing an intuitive cognitive sense about policy anomaly. We also discuss a proof-of-concept implementation of a visualization-based firewall policy analysis tool called Firewall Anomaly Management Environment (FAME). In addition, we demonstrate how efficiently our approach can discover and resolve anomalies in firewall policies through rigorous experiments.
Hongxin Hu, Gail-Joon Ahn, Ketan Kulkarni
IEEE Trans. Dependable Secur. Comput.3
2011 Ontology-based policy anomaly management for autonomic computing
abstract
The advent of emerging computing technologies such as service-oriented architecture and cloud computing has enabled us to perform business services more efficiently and effectively. However, we still suffer from unintended security leakages by unauthorized actions in business services. Moreover, des
Hongxin Hu, Gail-Joon Ahn, Ketan Kulkarni
CollaborateCom3
2011 Anomaly discovery and resolution in web access control policies
abstract
The advent of emerging technologies such as Web services, service-oriented architecture, and cloud computing has enabled us to perform business services more efficiently and effectively. However, we still suffer from unintended security leakages by unauthorized actions in business services while providing more convenient services to Internet users through such a cutting-edge technological growth. Furthermore, designing and managing Web access control policies are often error-prone due to the lack of effective analysis mechanisms and tools. In this paper, we represent an innovative policy anomaly analysis approach for Web access control policies. We focus on XACML (eXtensible Access Control Markup Language) policy since XACML has become the de facto standard for specifying and enforcing access control policies for various Web-based applications and services. We introduce a policy-based segmentation technique to accurately identify policy anomalies and derive effective anomaly resolutions. We also discuss a proof-of-concept implementation of our method called XAnalyzer and demonstrate how efficiently our approach can discover and resolve policy anomalies.
Hongxin Hu, Gail-Joon Ahn, Ketan Kulkarni
SACMAT3