You are presented with multiple paper abstracts, alongside the associated literature review and chapter titles. Given the provided information, you are going to do a literature review. Please generate a coherent literature review that synthesizes the content, draws connections between different works, highlights major findings, and identifies any gaps in the existing research.

Literature Review Title: Integrity Protecting and Privacy Preserving Data Aggregation Protocols in Wireless Sensor Networks: A Survey 
Chapter Title:  a) PIA 
1. Abstract of Cited Paper (BIB001):  Encryption is a well established technology for protecting sensitive data. However, once encrypted, data can no longer be easily queried aside from exact matches. We present an order-preserving encryption scheme for numeric data that allows any comparison operation to be directly applied on encrypted data. Query results produced are sound (no false hits) and complete (no false drops). Our scheme handles updates gracefully and new values can be added without requiring changes in the encryption of other values. It allows standard databse indexes to be built over encrypted tables and can easily be integrated with existing database systems. The proposed scheme has been designed to be deployed in application environments in which the intruder can get access to the encrypted database, but does not have prior domain information such as the distribution of values and annot encrypt or decrypt arbitrary values of his choice. The encryption is robust against estimation of the true value in such environments. 
2. Abstract of Cited Paper (BIB002):  In-network aggregation is an essential primitive for performing queries on sensor network data. However, most aggregation algorithms assume that all intermediate nodes are trusted. In contrast, the standard threat model in sensor network security assumes that an attacker may control a fraction of the nodes, which may misbehave in an arbitrary (Byzantine) manner.We present the first algorithm for provably secure hierarchical in-network data aggregation. Our algorithm is guaranteed to detect any manipulation of the aggregate by the adversary beyond what is achievable through direct injection of data values at compromised nodes. In other words, the adversary can never gain any advantage from misrepresenting intermediate aggregation computations. Our algorithm incurs only O(Δ log2 n) node congestion, supports arbitrary tree-based aggregator topologies and retains its resistance against aggregation manipulation in the presence of arbitrary numbers of malicious nodes. The main algorithm is based on performing the sum aggregation securely by first forcing the adversary to commit to its choice of intermediate aggregation results, and then having the sensor nodes independently verify that their contributions to the aggregate are correctly incorporated. We show how to reduce secure median , count , and average to this primitive. 
3. Abstract of Cited Paper (BIB003):  Data aggregation in sensor network can improve both efficiency and privacy of network traffic.Recent work in integrity-assured data aggregation has considered aggregation as only an efficiency primitive. In this work, we address for the first time the problem of integrity-assured data aggregation with efficiency and privacy as a joint objective. Our solutions show the inherent tension between privacy-preservation and integrity-assurance of data aggregation.

Literature Review:
The PIA (Privacy Preserving Integrity Assured data aggregation) BIB004 addresses the integrity assured data aggregation with efficiency and privacy as joint objective. Two types of Integrity Verification (IV): centralized and distributed. In both types, the integrity of aggregate is verified by re-computing the aggregation function of the raw data. In centralized IV, after receiving data from sensor node, the server checks the integrity. In distributed IV, the sensor node recompute the aggregation function using the data from other sensors. If all the results obtained from sensor node is same, then aggregation is considered as secure. It distributes the communication throughput in the network. The PIA proposed four symmetric key solutions for the single aggregator model. In the first solution, homomorphic encryption scheme hides data during transmission in a centralized IV . combines the homomorphism and MAC BIB001 to construct an authenticated encryption scheme for the aggregator node. The MAC is used to check the integrity of the aggregated result at the sink. It only supports additive aggregation functions such as SUM, average and standard deviation. The second solution uses the Order Preserving Encryption Scheme (OPES) BIB002 to preserve the privacy of distribution of data. OPES uses to verify the integrity of comparison based aggregation function. Sensors encrypt the data by using OPES with master secret key shared by all sensors then aggregator calculates and sends to the user. The user decrypts the aggregated data in centralized IV. The third solution uses a secure hierarchical in networking aggregation (SHIA) BIB003 scheme for adapting distributed IV. This scheme supports any aggregation function because the sensor nodes have the access to all raw data. The communication overhead of each node is O(N). Where N is the total number of sensor node in a network. This scheme preserves privacy without using any additional privacy preservation mechanism such as encryption. A commitment is constructed during the aggregation process. After calculating the aggregate, each sensor node independently reconstructs the commit tree and ensure that the data is not modified or discard the contribution of the node by any adversary. The fourth solution used to improve the privacy and integrity of the third solution by using a logical aggregation tree within the aggregator node. Each sensor node has a communication overhead of O (log N). It only supports decomposable functions such as mean, standard deviation, count, MIN/MAX. It uses distributed IV. III.