The industry has recognized the risk of cyber-attacks targeting to the advanced metering infrastructure (AMI). A potential adversary can modify or inject malicious data, and can perform security attacks over an insecure network. Also, the network operators at intermediate devices can reveal private information, such as the identity of the individual home and metering data units, to the third-party. Existing schemes generate large overheads and also do not ensure the secure delivery of correct and accurate metering data to all AMI entities, including data concentrator at the utility and the billing center. In this paper, we propose a secure and privacy-preserving data aggregation scheme based on additive homomorphic encryption and proxy re-encryption operations in the Paillier cryptosystem. The scheme can aggregate metering data without revealing the actual individual information (identity and energy usage) to intermediate entities or to any third-party, hence, resolves identity and related data theft attacks. Moreover, we propose a scalable algorithm to detect malicious metering data injected by the adversary. The proposed scheme protects the system against man-in-the-middle, replay, and impersonation attacks, and also maintains message integrity and undeniability. Our performance analysis shows that the scheme generates manageable computation , communication, and storage overheads and has efficient execution time suitable for AMI networks.

Wireless Sensor Networks (WSNs) are defined as dynamic, self-deployed, highly constrained structured network. It`s high computational environment with limited and controlled transmission range, processing, as well as limited energy sources. The sever power constraints strongly affect the existence of active nodes and hence the network lifetime. In order to prolong the network life time we have to overcome the scarcity in energy resources and preserve the processing of the sensor nodes as long as possible. Power management approaches efficiently reduce the sensor nodes energy consumption individually in each sensor node and the adaptive efficient routing technique has greatly appeals a great attention in research. The potential paradigms of soft-computing (SC) highly addressed their adaptability and compatibility to overwhelm the complex challenges in WSNs. This paper is introducing and surveying some of the Soft Computing proposed routing models for WSNs that optimally prolongs its life time.

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