Privacy-Preserving Data Aggregation Protocols for Wireless Sensor Networks: A Survey

Many wireless sensor network (WSN) applications require privacy-preserving aggregation of sensor data during transmission from the source nodes to the sink node. In this paper, we explore several existing privacy-preserving data aggregation (PPDA) protocols for WSNs in order to provide some insights on their current status. For this, we evaluate the PPDA protocols on the basis of such metrics as communication and computation costs in order to demonstrate their potential for supporting privacy-preserving data aggregation in WSNs. In addition, based on the existing research, we enumerate some important future research directions in the field of privacy-preserving data aggregation for WSNs

Cache-and-query for wide area sensor databases

Webcams, microphones, pressure gauges and other sensors pro-vide exciting new opportunities for querying and monitoring the physical world. In this paper we focus on querying wide area sen-sor databases, containing (XML) data derived from sensors spread over tens to thousands of miles. We present the first scalable sys-tem for executing XPATH queries on such databases. The system maintains the logical view of the data as a single XML document, while physically the data is fragmented across any number of host nodes. For scalability, sensor data is stored close to the sensors, but can be cached elsewhere as dictated by the queries. Our de-sign enables self-starting distributed queries that jump directly to the lowest common ancestor of the query result, dramatically re-ducing query response times. We present a novel query-evaluate-gather technique (using XSLT) for detecting (1) which data in a local database fragment is part of the query result, and (2) how to gather the missing parts. We define partitioning and cache invari-ants that ensure that even partial matches on cached data are ex-ploited and that correct answers are returned, despite our dynamic query-driven caching. Experimental results demonstrate that our techniques dramatically increase query throughputs and decrease query response times in wide area sensor databases. 1

Group-based secure communication for wireless sensor networks

Wireless Sensor Networks (WSNs) are a newly developed networking technology consisting of multifunctional sensor nodes that are small in size and communicate over short distances. Continuous growth in the use of Wireless Sensor Networks (WSN) in sensitive applications such as military or hostile environments and also generally has resulted m a requirement for effective security mechanisms in the system design In order to protect the sensitive data and the sensor readings, shared keys should be used to encrypt the exchanged messages between communicating nodes. Many key management schemes have been developed recently and a serious threat highlighted in all of these schemes is that of node capture attacks, where an adversary gains full control over a sensor node through direct physical access. This can lead an adversary to compromise the communication of an entire WSN. Additionally ignoring security issues related to data aggregation can also bring large damage to WSNs. Furthermore, in case an aggregator node, group leader or cluster head node fails there should be a secure and efficient way of electing or selecting a new aggregator or group leader node in order to avoid adversary node to be selected as a new group leader. A key management protocol for mobile sensor nodes is needed to enable them to securely communicate and authenticate with the rest of the WSN

ABSTRACT Cache-and-Query for Wide Area Sensor Databases

Webcams, microphones, pressure gauges and other sensors provide exciting new opportunities for querying and monitoring the physical world. In this paper we focus on querying wide area sensor databases, containing (XML) data derived from sensors spread over tens to thousands of miles. We present the first scalable system for executing XPATH queries on such databases. The system maintains the logical view of the data as a single XML document, while physically the data is fragmented across any number of host nodes. For scalability, sensor data is stored close to the sensors, but can be cached elsewhere as dictated by the queries (auto-tuning). Our design enables self-starting distributed queries that jump directly to the lowest common ancestor of the query result, dramatically reducing query response times. We present a novel query-evaluategather technique (using XSLT) for detecting (1) which data in a local database fragment is part of the query result, and (2) how to gather the missing parts. We define partitioning and cache invariants that ensure that even partial matches on cached data are exploited and that correct answers are returned, despite our dynamic query-driven caching. Experimental results demonstrate that our techniques dramatically increase query throughputs and decrease query response times in wide area sensor databases. 1