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Full-Text Articles in Physical Sciences and Mathematics
Streaming Estimation Of Information-Theoretic Metrics For Anomaly Detection (Extended Abstract), Sergey Bratus, Joshua Brody, David Kotz, Anna Shubina
Streaming Estimation Of Information-Theoretic Metrics For Anomaly Detection (Extended Abstract), Sergey Bratus, Joshua Brody, David Kotz, Anna Shubina
Dartmouth Scholarship
Information-theoretic metrics hold great promise for modeling traffic and detecting anomalies if only they could be computed in an efficient, scalable ways. Recent advances in streaming estimation algorithms give hope that such computations can be made practical. We describe our work in progress that aims to use streaming algorithms on 802.11a/b/g link layer (and above) features and feature pairs to detect anomalies.
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 …
Detecting 802.11 Mac Layer Spoofing Using Received Signal Strength, Yong Sheng, Keren Tan, Guanling Chen, David Kotz, Andrew T. Campbell
Detecting 802.11 Mac Layer Spoofing Using Received Signal Strength, Yong Sheng, Keren Tan, Guanling Chen, David Kotz, Andrew T. Campbell
Dartmouth Scholarship
MAC addresses can be easily spoofed in 802.11 wireless LANs. An adversary can exploit this vulnerability to launch a large number of attacks. For example, an attacker may masquerade as a legitimate access point to disrupt network services or to advertise false services, tricking nearby wireless stations. On the other hand, the received signal strength (RSS) is a measurement that is hard to forge arbitrarily and it is highly correlated to the transmitter's location. Assuming the attacker and the victim are separated by a reasonable distance, RSS can be used to differentiate them to detect MAC spoofing, as recently proposed …
Refocusing In 802.11 Wireless Measurement, Udayan Deshpande, Chris Mcdonald, David Kotz
Refocusing In 802.11 Wireless Measurement, Udayan Deshpande, Chris Mcdonald, David Kotz
Dartmouth Scholarship
The edge of the Internet is increasingly wireless. To understand the Internet, one must understand the edge, and yet the measurement of wireless networks poses many new challenges. IEEE 802.11 networks support multiple wireless channels and any monitoring technique involves capturing traffic on each of these channels to gather a representative sample of frames from the network. We call this procedure \emphchannel sampling, in which each sniffer visits each channel periodically, resulting in a sample of the traffic on each of the channels. \par This sampling approach may be sufficient, for example, for a system administrator or anomaly detection module …
Active Behavioral Fingerprinting Of Wireless Devices, Sergey Bratus, Cory Cornelius, David Kotz, Dan Peebles
Active Behavioral Fingerprinting Of Wireless Devices, Sergey Bratus, Cory Cornelius, David Kotz, Dan Peebles
Dartmouth Scholarship
We propose a simple active method for discovering facts about the chipset, the firmware or the driver of an 802.11 wireless device by observing its responses (or lack thereof) to a series of crafted non-standard or malformed 802.11 frames. We demonstrate that such responses can differ significantly enough to distinguish between a number of popular chipsets and drivers. We expect to significantly expand the number of recognized device types through community contributions of signature data for the proposed open fingerprinting framework. Our method complements known fingerprinting approaches, and can be used to interrogate and spot devices that may be spoofing …