REISCH: incorporating lightweight and reliable algorithms into healthcare applications of WSNs

Healthcare institutions require advanced technology to collect patients' data accurately and continuously. The tradition technologies still suffer from two problems: performance and security efficiency. The existing research has serious drawbacks when using public-key mechanisms such as digital signature algorithms. In this paper, we propose Reliable and Efficient Integrity Scheme for Data Collection in HWSN (REISCH) to alleviate these problems by using secure and lightweight signature algorithms. The results of the performance analysis indicate that our scheme provides high efficiency in data integration between sensors and server (saves more than 24% of alive sensors compared to traditional algorithms). Additionally, we use Automated Validation of Internet Security Protocols and Applications (AVISPA) to validate the security procedures in our scheme. Security analysis results confirm that REISCH is safe against some well-known attacks

Software Defined Networks based Smart Grid Communication: A Comprehensive Survey

The current power grid is no longer a feasible solution due to ever-increasing user demand of electricity, old infrastructure, and reliability issues and thus require transformation to a better grid a.k.a., smart grid (SG). The key features that distinguish SG from the conventional electrical power grid are its capability to perform two-way communication, demand side management, and real time pricing. Despite all these advantages that SG will bring, there are certain issues which are specific to SG communication system. For instance, network management of current SG systems is complex, time consuming, and done manually. Moreover, SG communication (SGC) system is built on different vendor specific devices and protocols. Therefore, the current SG systems are not protocol independent, thus leading to interoperability issue. Software defined network (SDN) has been proposed to monitor and manage the communication networks globally. This article serves as a comprehensive survey on SDN-based SGC. In this article, we first discuss taxonomy of advantages of SDNbased SGC.We then discuss SDN-based SGC architectures, along with case studies. Our article provides an in-depth discussion on routing schemes for SDN-based SGC. We also provide detailed survey of security and privacy schemes applied to SDN-based SGC. We furthermore present challenges, open issues, and future research directions related to SDN-based SGC.Comment: Accepte

PoFEL: Energy-efficient Consensus for Blockchain-based Hierarchical Federated Learning

Facilitated by mobile edge computing, client-edge-cloud hierarchical federated learning (HFL) enables communication-efficient model training in a widespread area but also incurs additional security and privacy challenges from intermediate model aggregations and remains the single point of failure issue. To tackle these challenges, we propose a blockchain-based HFL (BHFL) system that operates a permissioned blockchain among edge servers for model aggregation without the need for a centralized cloud server. The employment of blockchain, however, introduces additional overhead. To enable a compact and efficient workflow, we design a novel lightweight consensus algorithm, named Proof of Federated Edge Learning (PoFEL), to recycle the energy consumed for local model training. Specifically, the leader node is selected by evaluating the intermediate FEL models from all edge servers instead of other energy-wasting but meaningless calculations. This design thus improves the system efficiency compared with traditional BHFL frameworks. To prevent model plagiarism and bribery voting during the consensus process, we propose Hash-based Commitment and Digital Signature (HCDS) and Bayesian Truth Serum-based Voting (BTSV) schemes. Finally, we devise an incentive mechanism to motivate continuous contributions from clients to the learning task. Experimental results demonstrate that our proposed BHFL system with the corresponding consensus protocol and incentive mechanism achieves effectiveness, low computational cost, and fairness