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524
LEAP: Efficient Security Mechanisms for Large-scale Distributed Sensor Networks
, 2003
"... Protocol), a key management protocol for sensor networks that is designed to support in-network processing, while at the same time restricting the security impact of a node compromise to the immediate network neighborhood of the compromised node. The design of the protocol is motivated by the observ ..."
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Cited by 469 (22 self)
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Protocol), a key management protocol for sensor networks that is designed to support in-network processing, while at the same time restricting the security impact of a node compromise to the immediate network neighborhood of the compromised node. The design of the protocol is motivated by the observation that different types of messages exchanged between sensor nodes have different security requirements, and that a single keying mechanism is not suitable for meeting these different security requirements. LEAP supports the establishment of four types of keys for each sensor node – an individual key shared with the base station, a pairwise key shared with another sensor node, a cluster key shared with multiple neighboring nodes, and a group key that is shared by all the nodes in the network. The protocol used for establishing and updating these keys
A Public-Key Infrastructure for Key Distribution in TinyOS Based on Elliptic Curve Cryptography
"... We present the first known implementation of elliptic curve cryptography over F2p for sensor networks based on the 8-bit, 7.3828-MHz MICA2 mote. Through instrumentation of UC Berkeley’s TinySec module, we argue that, although secret-key cryptography has been tractable in this domain for some time, ..."
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Cited by 269 (4 self)
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We present the first known implementation of elliptic curve cryptography over F2p for sensor networks based on the 8-bit, 7.3828-MHz MICA2 mote. Through instrumentation of UC Berkeley’s TinySec module, we argue that, although secret-key cryptography has been tractable in this domain for some time, there has remained a need for an efficient, secure mechanism for distribution of secret keys among nodes. Although public-key infrastructure has been thought impractical, we argue, through analysis of our own implementation for TinyOS of multiplication of points on elliptic curves, that public-key infrastructure is, in fact, viable for TinySec keys ’ distribution, even on the MICA2. We demonstrate that public keys can be generated within 34 seconds, and that shared secrets can be distributed among nodes in a sensor network within the same, using just over 1 kilobyte of SRAM and 34 kilobytes of ROM.
Tinypk: securing sensor networks with public key technology
- In SASN ’04: Proceedings of the 2nd ACM Workshop on Security of Ad Hoc and Sensor Networks
, 2004
"... Wireless networks of miniaturized, low-power sensor/actuator devices are poised to become widely used in commercial and military environments. The communication security problems for these networks are exacerbated by the limited power and energy of the sensor devices. In this paper, we describe the ..."
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Cited by 151 (0 self)
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Wireless networks of miniaturized, low-power sensor/actuator devices are poised to become widely used in commercial and military environments. The communication security problems for these networks are exacerbated by the limited power and energy of the sensor devices. In this paper, we describe the design and implementation of public-key-(PK)-based protocols that allow authentication and key agreement between a sensor network and a third party as well as between two sensor networks. Our work is novel in that PK technology was commonly believed to be too inefficient for use on low-power devices. As part of our solution, we exploit the efficiency of public operations in the RSA cryptosystem and design protocols that place the computationally expensive operations on the parties external to the sensor network, when possible. Our protocols have been implemented on UC Berkeley MICA2 motes using the TinyOS development environment.
The BikeNet Mobile Sensing System for Cyclist Experience Mapping
- In Proc. of 5th ACM Conf. on Embedded Networked Sensor Systems
, 2007
"... We describe our experiences deploying BikeNet, an extensible mobile sensing system for cyclist experience mapping leveraging opportunistic sensor networking principles and techniques. BikeNet represents a multifaceted sensing system and explores personal, bicycle, and environmental sensing using dyn ..."
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Cited by 147 (13 self)
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We describe our experiences deploying BikeNet, an extensible mobile sensing system for cyclist experience mapping leveraging opportunistic sensor networking principles and techniques. BikeNet represents a multifaceted sensing system and explores personal, bicycle, and environmental sensing using dynamically role-assigned bike area networking based on customized Moteiv Tmote Invent motes and sensor-enabled Nokia N80 mobile phones. We investigate real-time and delay-tolerant uploading of data via a number of sensor access points (SAPs) to a networked repository. Among bicycles that rendezvous en route we explore inter-bicycle networking via data muling. The repository provides a cyclist with data archival, retrieval, and visualization services. BikeNet promotes the social networking of the cycling community through the provision of a web portal that facilitates back end sharing of real-time and archived cycling-related data from the repository. We present: a description and prototype implementation of the system architecture, an evaluation of sensing and inference that quantifies cyclist performance and the cyclist environment; a report on networking performance in an environment characterized by bicycle mobility and human unpredictability; and a description of BikeNet system user interfaces. Visit [4] to see how the BikeNet system visualizes a user’s rides.
SDAP: A secure hop-by-hop data aggregation protocol for sensor networks
, 2008
"... Hop-by-hop data aggregation is a very important technique for reducing the communication overhead and energy expenditure of sensor nodes during the process of data collection in a sensor network. However, because individual sensor readings are lost in the per-hop aggregation process, compromised nod ..."
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Cited by 134 (10 self)
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Hop-by-hop data aggregation is a very important technique for reducing the communication overhead and energy expenditure of sensor nodes during the process of data collection in a sensor network. However, because individual sensor readings are lost in the per-hop aggregation process, compromised nodes in the network may forge false values as the aggregation results of other nodes, tricking the base station into accepting spurious aggregation results. Here a fundamental challenge is how can the base station obtain a good approximation of the fusion result when a fraction of sensor nodes are compromised? To answer this challenge, we propose SDAP, a Secure Hop-by-hop Data Aggregation Protocol for sensor networks. SDAP is a general-purpose secure data aggregation protocol applicable to multiple aggregation functions. The design of SDAP is based on the principles of divide-andconquer and commit-and-attest. First, SDAP uses a novel probabilistic grouping technique to dynamically partition the nodes in a tree topology into multiple logical groups (subtrees) of similar sizes. A commitment-based hop-by-hop aggregation is performed in each group to generate a group aggregate. The base station then identifies the suspicious groups based on the set of group aggregates. Finally, each group under suspect participates in an attestation process to prove the
People-centric urban sensing
- In The Second Annual International Wireless Internet Conference (WICON
, 2006
"... The vast majority of advances in sensor network research over the last five years have focused on the development of a series of small-scale (100s of nodes) testbeds and specialized applications (e.g., environmental monitoring, etc.) that are built on low-powered sensor devices that self-organize to ..."
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Cited by 113 (17 self)
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The vast majority of advances in sensor network research over the last five years have focused on the development of a series of small-scale (100s of nodes) testbeds and specialized applications (e.g., environmental monitoring, etc.) that are built on low-powered sensor devices that self-organize to form application-specific multihop wireless networks. We believe that sensor networks have reached an important crossroads in their development. The question we address in this paper is how to propel sensor networks from their smallscale application-specific network origins, into the commercial mainstream of people’s every day lives; the challenge being: how do we develop large-scale general-purpose sensor networks for the general public (e.g., consumers) capable of supporting a wide variety of applications in urban settings (e.g., enterprises, hospitals, recreational areas, towns, cities, and the metropolis). We propose MetroSense, a new people-centric paradigm for urban sensing at the edge of the Internet, at very large scale. We discuss a number of challenges, interactions and characteristics in urban sensing applications, and then present the MetroSense architecture which is based fundamentally on three design principles: network symbiosis, asymmetric design, and localized interaction. The ability of MetroSense to scale to very large areas is based on the use of an opportunistic sensor networking approach. Opportunistic sensor networking leverages mobility-enabled interactions and provides coordination between people-centric mobile sensors, static sensors and edge wireless access nodes in support of opportunistic sensing, opportunistic tasking, and opportunistic data collection. We discuss architectural challenges including providing sensing coverage with sparse mobile sensors, how to hand off roles and responsibilities between sensors, improving network performance and connectivity using adaptive multihop, and importantly, providing security and privacy for people-centric sensors and data.
Wireless sensor networks: A survey on the state of the art and the 802.15.4 and ZigBee standards
, 2007
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Sensor Networks for Medical Care,”
, 2005
"... Abstract Sensor networks have the potential to greatly impact many aspects of medical care. By outfitting patients with wireless, wearable vital sign sensors, collecting detailed real-time data on physiological status can be greatly simplified. However, there is a significant gap between existing s ..."
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Cited by 109 (1 self)
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Abstract Sensor networks have the potential to greatly impact many aspects of medical care. By outfitting patients with wireless, wearable vital sign sensors, collecting detailed real-time data on physiological status can be greatly simplified. However, there is a significant gap between existing sensor network systems and the needs of medical care. In particular, medical sensor networks must support multicast routing topologies, node mobility, a wide range of data rates and high degrees of reliability, and security. This paper describes our experiences with developing a combined hardware and software platform for medical sensor networks, called CodeBlue. CodeBlue provides protocols for device discovery and publish/subscribe multihop routing, as well as a simple query interface that is tailored for medical monitoring. We have developed several medical sensors based on the popular MicaZ and Telos mote designs, including a pulse oximeter, EKG and motion-activity sensor. We also describe a new, miniaturized sensor mote designed for medical use. We present initial results for the CodeBlue prototype demonstrating the integration of our medical sensors with the publish/subscribe routing substrate. We have experimentally validated the prototype on our 30-node sensor network testbed, demonstrating its scalability and robustness as the number of simultaneous queries, data rates, and transmitting sensors are varied. We also study the effect of node mobility, fairness across multiple simultaneous paths, and patterns of packet loss, confirming the system's ability to maintain stable routes despite variations in node location and data rate.
ALARM-NET: Wireless sensor networks for assisted-living and residential monitoring
, 2006
"... We describe ALARM-NET, a wireless sensor network for assisted-living and residential monitoring. It integrates environmental and physiological sensors in a scalable, heterogeneous architecture. A query protocol allows real-time collection and processing of sensor data by user interfaces and back-end ..."
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Cited by 98 (6 self)
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We describe ALARM-NET, a wireless sensor network for assisted-living and residential monitoring. It integrates environmental and physiological sensors in a scalable, heterogeneous architecture. A query protocol allows real-time collection and processing of sensor data by user interfaces and back-end analysis programs. One such program determines circadian activity rhythms of residents, feeding activity information back into the sensor network to aid context-aware power management, dynamic privacy policies, and data association. Communication is secured end-to-end to protect sensitive medical and operational information. The ALARM-NET system has been implemented as a network of MICAz sensors, stargate gateways, iPAQ PDAs, and PCs. Customized infrared motion and dust sensors, and integrated temperature, light, pulse, and blood oxygenation sensors are present. Software components include: TinyOS query processor and security modules for motes; AlarmGate, an embedded Java application for managing power, privacy, security, queries, and client connections; Java resident monitoring and sensor data querying applications for PDAs and PCs; and a circadian activity rhythm analysis program. We show the correctness, robustness, and extensibility of the system architecture through a scenario-based evaluation of the integrated ALARM-NET system, as well as performance data for individual software components. 1
Pacemakers and implantable cardiac defibrillators: Software radio attacks and zero-power defenses
- In IEEE Symposium on Security and Privacy (SP
, 2008
"... Part of the Computer Sciences Commons This Article is brought to you for free and open access by the Computer Science at ScholarWorks@UMass Amherst. It has been accepted for inclusion in Computer Science Department Faculty Publication Series by an authorized administrator of ScholarWorks@UMass Amher ..."
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Cited by 95 (15 self)
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Part of the Computer Sciences Commons This Article is brought to you for free and open access by the Computer Science at ScholarWorks@UMass Amherst. It has been accepted for inclusion in Computer Science Department Faculty Publication Series by an authorized administrator of ScholarWorks@UMass Amherst. For more information, please contact