Situational Awareness provides a user centric approach to security and privacy. The human factor is often recognised as the weakest link in security, therefore situational perception and risk awareness play a leading role in the adoption and implementation of security mechanisms. In this study we assess the understanding of security and privacy of users in possession of wearable devices. The findings demonstrate privacy complacency, as the majority of users trust the application and the wearable device manufacturer.
Submitted by xavier bellekens on November 17th, 2016
This award provides NSF support to sponsor students and faculty mentors from US institutions to participate in a doctoral symposium held during the First Workshop on Privacy and Security in Pervasive e-Health and Assistive Environments in Corfu, Greece, June 9-13, 2009. This workshop is in conjunction with the Second International Conference on Pervasive Technologies Related to Assistive Environments (PETRA?09 http://www.petrae.org).
The doctoral symposium shares the aims of the PSPAE workshop, seeking new directions in security and privacy research and education. The focus of the PSPAE workshop is a multidisciplinary discussion aimed towards developing new insights into privacy and security issues for pervasive technologies that will be deployed for the benefit of society. The scientific community is expected to benefit from discussions on the crossover between security and privacy and on the issues arising in complex application areas such as healthcare. The doctoral consortium seeks to open new horizons for graduate students who may pursue privacy and security research in healthcare and other pervasive assistive environments. Another objective is to create an international forum that can expose graduate students to the differences in privacy policies around the world, especially regarding health privacy and security.
Award Number
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Co-PIs
Zhengyi Le
Heng Huang
Institution
University of Texas at Arlington
Lead PI
Fillia Makedon
Project URL
Performance Period
-
Sponsor
National Science Foundation
Submitted by Fillia Makedon on January 11th, 2016
Event
CPSSC 2016
1st International Workshop on Cyber-Physical Systems in the Context of Smart Cities
23 February 2016 | Vienna, Austria | @SE2016
Submitted by Katie Dey on December 2nd, 2015
Event
INTRICATE-SEC 2016
4th International Workshop on Security Intricacies in Cyber-Physical Systems and Services (INTRICATE-SEC 2016)
held in conjunction with the 30th International Conference on Advanced Information Networking and Applications (AINA-2016)
Topics of Interest
Submitted by Anonymous on October 2nd, 2015
Abstract:
The electric power grid is a critical infrastructure that is vulnerable to physical and cyber attacks. As a result, data describing grid topology and components is considered sensitive information. There is also increasing need to foster cooperation among the participants in microgrid-enabled electric marketplace.
Submitted by Parmesh Ramanathan on November 10th, 2014
Abstract:
The electric power grid is a critical infrastructure that is vulnerable to physical and cyber attacks. As a result, data describing grid topology and components is considered sensitive information. There is also increasing need to foster cooperation among the participants in microgrid-enabled electric marketplace.
Submitted by Parmesh Ramanathan on November 10th, 2014
File
Learned Helplessness
Submitted by Sara Kiesler on May 29th, 2014
Speaker Bio:
Submitted by George Pappas on October 17th, 2013
The provenance captured from different layers of abstraction (workflow/process/OS) provides the highest benefit when integrated through a unified provenance framework. To build such a framework, a comprehensive provenance model able to represent the provenance of data objects with various semantics and granularity is the first step. In this poster we present a provenance model able to represent the provenance of any data object captured at any abstraction layer and present an abstract schema of the model.
Submitted by Katie Dey on December 11th, 2012
This poster will present secure network provenance (SNP), a novel capability that enables networked systems to explain to their operators why they are in a certain state – e.g., why a suspicious routing table entry is present on a certain router, or where a given cache entry originated. SNP provides network forensics capabilities by permitting operators to track down faulty or misbehaving nodes, and to assess the damage such nodes may have caused to the rest of the system.
Submitted by Anonymous on December 11th, 2012