Integrity Protecting and Privacy Preserving Data Aggregation Protocols in Wireless Sensor Networks: A Survey <s> M=c- <s> Rapid advances in networking and Internet technologies have fueled the emergence of the "software as a service" model for enterprise computing. Successful examples of commercially viable software services include rent-a-spreadsheet, electronic mail services, general storage services, disaster protection services. "Database as a Service" model provides users power to create, store, modify, and retrieve data from anywhere in the world, as long as they have access to the Internet. It introduces several challenges, an important issue being data privacy. It is in this context that we specifically address the issue of data privacy.There are two main privacy issues. First, the owner of the data needs to be assured that the data stored on the service-provider site is protected against data thefts from outsiders. Second, data needs to be protected even from the service providers, if the providers themselves cannot be trusted. In this paper, we focus on the second challenge. Specifically, we explore techniques to execute SQL queries over encrypted data. Our strategy is to process as much of the query as possible at the service providers' site, without having to decrypt the data. Decryption and the remainder of the query processing are performed at the client site. The paper explores an algebraic framework to split the query to minimize the computation at the client site. Results of experiments validating our approach are also presented. <s> BIB001 </s> Integrity Protecting and Privacy Preserving Data Aggregation Protocols in Wireless Sensor Networks: A Survey <s> M=c- <s> We consider a sensor network that is not fully trusted and ask the question how we preserve privacy for the collected data and how we verify the data reply from the network. We explore the problem in the context of a network augmented with storage nodes and target at range query. We use bucketing scheme to mix the data for a range, use message encryption for data integrity, and employ encoding numbers to prevent the storage nodes from dropping data. <s> BIB002
MPDA scheme preserves privacy against passive attack and sensor node compromise attack. The compromising of a sensor node does not disclose the data sensed by other nodes or aggregator nodes and its private key. BIB002 provide a privacy preserving storage scheme based on the bucketing scheme BIB001  . In this scheme, every sensor node generates environmental data values in a fixed rate and periodically submits the collected data to the closest storage node for each epoch (time interval between two submissions). Every sensor node has a unique ID, and it shares a distinct secret key with sink, so that compromising one sensor node does not affect the security of other sensor data. Before sending the data to the storage node, encrypt the data using the shared key between sensor node and sink, then attach a tag to the encrypted data based on which bucket the data falls into. The data values with same tag can be encrypted as a block. Upon receiving the encrypted data from source node, the storage node divides the data into multiple buckets, and each bucket is assigned a tag. The sensors and sink should agree on the same bucket partition. When a sink node wants to process a range query over the data stored on the storage node, it obtains the result based on the tag corresponding to the query range, instead of decrypting the data and return the result. This reduces the energy wasted for the decryption. At the sink, it decrypts the received data based on the key shared with the sensor node, obtain the real sensor data. The main problem is the transmission delay, i.e, the time required to send data from source to sink. It is unsuitable for applications like event detection and tracking objects because this application requires an immediate response. This scheme focus on the problem when the storage node and sensor node is compromised. The compromising of storage node leads to reveal sensed data of nodes and data fidelity attack (the adversary tries to reply wrong information for the user query and make them to accept it). To prevent the storage node from false reply, an encoding number is generated on each sensor if no data in a query range are collected from the sensor. 