MOF-BC: A Memory Optimized and Flexible BlockChain for Large Scale Networks

BlockChain (BC) immutability ensures BC resilience against modification or removal of the stored data. In large scale networks like the Internet of Things (IoT), however, this feature significantly increases BC storage size and raises privacy challenges. In this paper, we propose a Memory Optimized and Flexible BC (MOF-BC) that enables the IoT users and service providers to remove or summarize their transactions and age their data and to exercise the "right to be forgotten". To increase privacy, a user may employ multiple keys for different transactions. To allow for the removal of stored transactions, all keys would need to be stored which complicates key management and storage. MOF-BC introduces the notion of a Generator Verifier (GV) which is a signed hash of a Generator Verifier Secret (GVS). The GV changes for each transaction to provide privacy yet is signed by a unique key, thus minimizing the information that needs to be stored. A flexible transaction fee model and a reward mechanism is proposed to incentivize users to participate in optimizing memory consumption. Qualitative security and privacy analysis demonstrates that MOF-BC is resilient against several security attacks. Evaluation results show that MOF-BC decreases BC memory consumption by up to 25\% and the user cost by more than two orders of magnitude compared to conventional BC instantiations

Identifying vital edges in Chinese air route network via memetic algorithm

Due to its rapid development in the past decade, air transportation system has attracted considerable research attention from diverse communities. While most of the previous studies focused on airline networks, here we systematically explore the robustness of the Chinese air route network, and identify the vital edges which form the backbone of Chinese air transportation system. Specifically, we employ a memetic algorithm to minimize the network robustness after removing certain edges hence the solution of this model is the set of vital edges. Counterintuitively, our results show that the most vital edges are not necessarily the edges of highest topological importance, for which we provide an extensive explanation from the microscope of view. Our findings also offer new insights to understanding and optimizing other real-world network systems

Applications of Temporal Graph Metrics to Real-World Networks

Real world networks exhibit rich temporal information: friends are added and removed over time in online social networks; the seasons dictate the predator-prey relationship in food webs; and the propagation of a virus depends on the network of human contacts throughout the day. Recent studies have demonstrated that static network analysis is perhaps unsuitable in the study of real world network since static paths ignore time order, which, in turn, results in static shortest paths overestimating available links and underestimating their true corresponding lengths. Temporal extensions to centrality and efficiency metrics based on temporal shortest paths have also been proposed. Firstly, we analyse the roles of key individuals of a corporate network ranked according to temporal centrality within the context of a bankruptcy scandal; secondly, we present how such temporal metrics can be used to study the robustness of temporal networks in presence of random errors and intelligent attacks; thirdly, we study containment schemes for mobile phone malware which can spread via short range radio, similar to biological viruses; finally, we study how the temporal network structure of human interactions can be exploited to effectively immunise human populations. Through these applications we demonstrate that temporal metrics provide a more accurate and effective analysis of real-world networks compared to their static counterparts.Comment: 25 page