Research on cyberspace multi-objective security algorithm and decision mechanism of Energy Internet
| Autor: | Lijun Liu, Rui Hou, Guowen Ren, Wei Gao |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Authentication
Optimization problem Computer Networks and Communications business.industry Network security Computer science Distributed computing Vulnerability 020206 networking & telecommunications Context (language use) 02 engineering and technology Intrusion detection system Firewall (construction) Hardware and Architecture 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing The Internet business Host (network) Software Vulnerability (computing) |
| Zdroj: | Future Generation Computer Systems. 120:119-124 |
| ISSN: | 0167-739X |
| DOI: | 10.1016/j.future.2021.02.007 |
| Popis: | The existing energy network security defense system uses firewall, intrusion detection, host monitoring, identity authentication, anti-virus software and vulnerability repair to build a fortress type rigid defense system to block or isolate external invasion. This static layered deep defense system is based on prior knowledge and has the advantages of rapid response and effective protection in the face of constant attacks When confronting the unknown attacking opponent, he is not able to do his best, and he is in danger of being attacked easily. In this context, multi-objective decision has more than two decision-making objectives and needs to use multiple criteria to evaluate and optimize the decision-making of alternatives. Due to the objectives of economic benefit, safety in production and environmental protection, it is necessary to use a variety of criteria to evaluate and optimize schemes. In this paper, we propose RBF neural network and weight-based algorithm to achieve multi-objective decision. We leverage RBF neural network to construct objective weight assignment model. The goal of our weight-based algorithm is that the multi-objective optimization problem is formulated as a single-objective optimization problem by assigning certain weights to each objective, and then the non-inferior solution of the multi-objective optimization problem is generated by changing the weights of each objective extensive. |
| Databáze: | OpenAIRE |
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