AT&T Labs Research - Vesonder, Gregory T.

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Awards
AT&T Fellow, 1996. Artificial intelligence applications: Honored for pioneering work in artificial intelligence applications and technology, and outstanding contributions in enabling organizations throughout AT&T to realize benefits from this technology.

Projects
Connecting Your World, The need to be connected is greater than ever, and AT&T Researchers are creating new ways for people to connect with one another and with their environments, whether it's their home, office, or car.

This version of the work is reprinted here with permission of IEEE for your personal use. Not for redistribution. The definitive version was published in 2012 , 2012-10-08

{Low Power Listening (LPL) is a widely used asynchronous technique to reduce idle listening energy cost in wireless sensor networks. Early LPL protocols like B-MAC that were designed for bit streaming radios achieve low duty cycle by keeping the radio transceiver awake for short time periods. However, they require a transmitter node to precede a packet transmission with a long preamble. Furthermore, they cannot be used with modern packet radios like widely used IEEE 802.15.4 based radio transceivers, which cannot transmit arbitrarily long preambles. Recent LPL schemes like X-MAC, on the other hand, reduce the length of the preamble and are designed to work with packet radios. However, in order to ensure that a receiver can detect a transmitter's preamble transmission, these schemes need to turn the radio transceiver on for longer time duration than the early schemes like B-MAC. In this paper, we present a novel LPL scheme called QuickMAC, that achieves the best of both worlds---small radio awake periods, compatibility with packet (and bit stream) radios, and short preamble length. From our experiments using TMote sky motes, we show that QuickMAC reduces duty cycle by a factor of about 4 compared to X-MAC. }

The definitive version was published in USENIX LISA'11: 25th Large Installation System Administration Conference, Usenix. , 2011-12-04

{Protecting computer and information systems from security attacks is becoming an increasingly important task for system administrators. Honeypots are a technology often used to detect attacks and collect information about techniques and targets (e.g., services, ports, operating systems) of attacks. However, managing a large and complex honeynet of honeypots becomes a challenge in itself given the amount of data collected as well as the risk that the honeypots may themselves become infected and start attacking other machines. In this paper, we present DarkNOC, a management and monitoring tool for complex honeynets consisting of different types of honeypots as well as other data collection devices. DarkNOC has been actively used to manage a honeynet consisting of multiple subnets and hundreds of IP addresses. This paper describes the architecture and a number of case studies demonstrating the use of the tool.}

The definitive version was published in LISAI '10., 2010-11-07

Network awareness is highly critical for network and security administrators. It enables informed planning and management of network resources, as well as detection and a comprehensive understanding of malicious activity. It requires a set of tools to efficiently collect, process and represent network data. While many of such tools already exist, there is a lack of a flexible and practical solution to visualize network activity at various granularities, and to quickly gain insights about the status of net- work assets. To address this issue, we developed Nfsight, a Netflow processing and visualization application designed to offer a comprehensive network awareness solution. Nfsight leverages the use of bidirectional flows to provide client/server identification and intrusion detection capabilities. We present in this paper the internal architecture of Nfsight, the evaluation of the service and intrusion detection algorithms. We illustrate the contributions of Nfsight through several case studies conducted by security administrators on a large campus network.

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