Linkboost: A Link Prediction Algorithm to Solve the Problem of Network Vulnerability in Cases Involving Incomplete Information

Abstract

e vulnerability of network information systems has attracted considerable research attention in various domains including financial networks, transportation networks, and infrastructure systems. To comprehensively investigate the network vulnerability, well-designed attack strategies are necessary. However, it is difficult to formulate a global attack strategy as the complete information of the network is usually unavailable. To overcome this limitation, this paper proposes a novel prediction algorithm named Linkboost, which, by predicting the hidden edges of the network, can complement the seemingly missing but potentially existing connections of the network with limited information. e key aspect of this algorithm is that it can deal with the imbalanced class distribution present in the network data. e proposed approach was tested on several types of networks, and the experimental results indicated that the proposed algorithm can successfully enhance the destruction rate of the network even with incomplete information. Furthermore, when the proportion of the missing information is relatively small, the proposed attack strategy relying on the high degree nodes performs even better than that with complete information. is finding suggests that the nodes important to the network structure and connectivity can be more easily identified by the links added by Linkboost. erefore, the use of Linkboost can provide useful insight into the operation guidance and design of a more effective attack strategy.

Intelligent Link Prediction Management Based on Community Discovery and User Behavior Preference in Online Social Networks

“…In this section, we present the results obtained in our experiments conducted on real-world short-text data collections in order to demonstrate the effectiveness of our proposed method. We consider four typical algorithms as our benchmark methods, namely, CPM [9], COPRA [18], LFM [19], and GCE [20]. We also introduce the collection of the dataset, experimental setup, analysis, the baseline approach, and the model evaluation.…”

“…It is worthy of note that most of the interconnected things can be abstracted as social networks. Typical networks, such as the cooperative network between scientists in the academic field, and the network structure of protein molecules in the biological field [18][19][20] resemble the topology of social networks. The ultimate purpose of studying the topological structure and properties of different types of networks is to understand the evolution principle of social networks, predict the future evolution direction and trend of social networks, estimate links [21] to better cope with the sudden changes in social networks, and apply this 2…”

Design of link prediction algorithm for complex network based on the comprehensive influence of predicting nodes and neighbor nodes

“…The incompleteness or partial observability of complex network structure will make the theory and engineering research of real network be confronted with challenges. In order to make up for the missing link in a real data set, the link prediction based on topology structure is introduced into various real networks (Jia, Ma, Liu, Zhang, & Han, 2020). Searching the factors of link prediction in complex network topology is the premise of studying the evolution mechanism of complex network reconstruction.…”

Research on university laboratory network security based on Cloud Computing

“…However, the development of the Internet has coexisted with opportunities and threats, and governments, enterprises, and people are enjoying the convenience of the Internet while suffering from the increasing threat of attacks on the Internet [14][15][16]. With the wide application of smart products and information platforms, the number of vulnerabilities and cyber-attacks has increased dramatically [17][18]. The security of the network is facing great challenges, which seriously affects the security of people's information and property, so effectively enhancing the security of network systems has become an important goal at present [19][20][21].…”