Titlebook: Anti-fragile ICT Systems; Kjell J?rgen Hole Book‘‘‘‘‘‘‘‘ 2016 The Editor(s) (if applicable) and The Author(s) 2016 Anomaly detection.Anti-

Opulent

書目名稱Anti-fragile ICT Systems影響因子(影響力)




書目名稱Anti-fragile ICT Systems影響因子(影響力)學(xué)科排名




書目名稱Anti-fragile ICT Systems網(wǎng)絡(luò)公開度




書目名稱Anti-fragile ICT Systems網(wǎng)絡(luò)公開度學(xué)科排名




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書目名稱Anti-fragile ICT Systems被引頻次學(xué)科排名




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書目名稱Anti-fragile ICT Systems年度引用學(xué)科排名




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書目名稱Anti-fragile ICT Systems讀者反饋學(xué)科排名

單調(diào)女

有效

GIBE

Strength

ARC

Heart-Rate

Robustness to Malware Reinfections are infected. Furthermore, nodes recover from infections with given probabilities, only to be reinfected later. An incident from 2007, where the same worm repeatedly infected the internal networks of a Norwegian bank, illustrates how reinfections can occur in real networks.

Repetitions

領(lǐng)帶

The HTM Learning Algorithm classes of negative events. The earlier we can detect problems, the smaller the negative consequences are and the faster we can start learning how to improve the systems. Since humans are not good at detecting anomalies, especially in streaming data from large cloud applications, a form of automati

透明

Anomaly Detection with HTMcomplex systems, real-time monitoring is needed to detect local failures before they propagate into global failures with an intolerable impact. In particular, monitoring is required to determine the consequences of injecting artificial errors into production systems and to learn how to avoid or limi