System recovery after intentional attacks
Many complex networks in the real-world context are found to be scale-free networks. Its structure is found to be generally robust because of its high error tolerance. This means that in most cases, the structure and connectivity of the network is not compromised even when many nodes fail. However,...
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Format: | Final Year Project |
Language: | English |
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Nanyang Technological University
2020
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Online Access: | https://hdl.handle.net/10356/139853 |
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Institution: | Nanyang Technological University |
Language: | English |
Summary: | Many complex networks in the real-world context are found to be scale-free networks. Its structure is found to be generally robust because of its high error tolerance. This means that in most cases, the structure and connectivity of the network is not compromised even when many nodes fail. However, scale free networks are found to be extremely vulnerable to coordinated attacks. When the attack deliberately disrupts the highly connected nodes in the network, the structure of the network breaks drastically and become fragmented. This paper presents the study of intentional attacks on systems and its recovery. Systems, as with many other networks, has scale-free properties. Intentional attacks refer to a deliberate attack on the system’s hubs instead of a random node. This includes the initial degree attack and the recalculated degree attack. Since the system is highly dependent on such hubs, its failure would result in a single system broken into many smaller fragments of the system. To recover from such attacks, the remaining nodes of the systems must establish new links in hopes to reconnect the fragmented network. This study proposes several recovery techniques and algorithms the system can deploy in the event of intentional attacks. Each recovery technique randomly selects different type of nodes such as global nodes, neighbours, and even two-hop neighbours of the attacked hub. Hence, this study examines which two type of nodes, when connected, would be the most effective solution for the recovery. The performance of these recovery techniques is assessed by comparing the largest cluster size of the resulting network. |
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