Open Access. Powered by Scholars. Published by Universities.®
Physical Sciences and Mathematics Commons™
Open Access. Powered by Scholars. Published by Universities.®
Articles 1 - 4 of 4
Full-Text Articles in Physical Sciences and Mathematics
Anonysense: A System For Anonymous Opportunistic Sensing, Minho Shin, Cory Cornelius, Dan Peebles, Apu Kapadia, David Kotz, Nikos Triandopoulos
Anonysense: A System For Anonymous Opportunistic Sensing, Minho Shin, Cory Cornelius, Dan Peebles, Apu Kapadia, David Kotz, Nikos Triandopoulos
Dartmouth Scholarship
We describe AnonySense, a privacy-aware system for realizing pervasive applications based on collaborative, opportunistic sensing by personal mobile devices. AnonySense allows applications to submit sensing \emphtasks\/ to be distributed across participating mobile devices, later receiving verified, yet anonymized, sensor data \emphreports\/ back from the field, thus providing the first secure implementation of this participatory sensing model. We describe our security goals, threat model, and the architecture and protocols of AnonySense. We also describe how AnonySense can support extended security features that can be useful for different applications. We evaluate the security and feasibility of AnonySense through security analysis and prototype …
Opportunistic Sensing: Security Challenges For The New Paradigm, Apu Kapadia, David Kotz, Nikos Triandopoulos
Opportunistic Sensing: Security Challenges For The New Paradigm, Apu Kapadia, David Kotz, Nikos Triandopoulos
Dartmouth Scholarship
We study the security challenges that arise in Opportunistic people-centric sensing, a new sensing paradigm leveraging humans as part of the sensing infrastructure. Most prior sensor-network research has focused on collecting and processing environmental data using a static topology and an application-aware infrastructure, whereas opportunistic sensing involves collecting, storing, processing and fusing large volumes of data related to everyday human activities. This highly dynamic and mobile setting, where humans are the central focus, presents new challenges for information security, because data originates from sensors carried by people— not tiny sensors thrown in the forest or attached to animals. In this …
Poster Abstract: Reliable People-Centric Sensing With Unreliable Voluntary Carriers, Cory Cornelius, Apu Kapadia, David Kotz, Dan Peebles, Minho Shin, Patrick Tsang
Poster Abstract: Reliable People-Centric Sensing With Unreliable Voluntary Carriers, Cory Cornelius, Apu Kapadia, David Kotz, Dan Peebles, Minho Shin, Patrick Tsang
Dartmouth Scholarship
As sensor technology becomes increasingly easy to integrate into personal devices such as mobile phones, clothing, and athletic equipment, there will be new applications involving opportunistic, people-centric sensing. These applications, which gather information about human activities and personal social context, raise many security and privacy challenges. In particular, data integrity is important for many applications, whether using traffic data for city planning or medical data for diagnosis. Although our AnonySense system (presented at MobiSys) addresses privacy in people-centric sensing, protecting data integrity in people-centric sensing still remains a challenge. Some mechanisms to protect privacy provide anonymity, and thus provide limited …
Anonysense: Opportunistic And Privacy-Preserving Context Collection, Apu Kapadia, Nikos Triandopoulos, Cory Cornelius, Dan Peebles, David Kotz
Anonysense: Opportunistic And Privacy-Preserving Context Collection, Apu Kapadia, Nikos Triandopoulos, Cory Cornelius, Dan Peebles, David Kotz
Dartmouth Scholarship
Opportunistic sensing allows applications to “task” mobile devices to measure context in a target region. For example, one could leverage sensor-equipped vehicles to measure traffic or pollution levels on a particular street, or users' mobile phones to locate (Bluetooth-enabled) objects in their neighborhood. In most proposed applications, context reports include the time and location of the event, putting the privacy of users at increased risk—even if a report has been anonymized, the accompanying time and location can reveal sufficient information to deanonymize the user whose device sent the report. \par We propose AnonySense, a general-purpose architecture for leveraging users' mobile …