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Titlebook: Computational Intelligence in Security for Information Systems; 4th International Co álvaro Herrero,Emilio Corchado Conference proceedings

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樓主: External-Otitis
31#
發(fā)表于 2025-3-26 21:52:29 | 只看該作者
32#
發(fā)表于 2025-3-27 01:14:22 | 只看該作者
33#
發(fā)表于 2025-3-27 05:53:49 | 只看該作者
Computational Intelligence in Security for Information Systems978-3-642-21323-6Series ISSN 0302-9743 Series E-ISSN 1611-3349
34#
發(fā)表于 2025-3-27 11:46:55 | 只看該作者
35#
發(fā)表于 2025-3-27 15:53:55 | 只看該作者
,Theorien zur Ausschüttungspolitik,This paper presents a selection of those most important and popular to the date, focusing on centralized schemes due to their high popularity and the recent publication of alternatives that do not appear in previous revisions. Comparisons are provided and special attention is paid to communications and storage overhead.
36#
發(fā)表于 2025-3-27 18:25:55 | 只看該作者
Digging into IP Flow Records with a Visual Kernel Methodmporal aggregated IP flows for the off/online processing of Netflow records and full packet captures from ISP and honeypot input data and is operating on aggregated Netflow records and is supporting network management activities related to the anomaly and attack detection.
37#
發(fā)表于 2025-3-28 00:23:27 | 只看該作者
Keeping Group Communications Private: An Up-to-Date Review on Centralized Secure MulticastThis paper presents a selection of those most important and popular to the date, focusing on centralized schemes due to their high popularity and the recent publication of alternatives that do not appear in previous revisions. Comparisons are provided and special attention is paid to communications and storage overhead.
38#
發(fā)表于 2025-3-28 04:51:17 | 只看該作者
Collective Classification for Spam Filteringature machine-learning algorithms trained using statistical representations of the terms that usually appear in the e-mails. Still, these methods require a training step with labelled data. Dealing with the situation where the availability of labelled training instances is limited slows down the pro
39#
發(fā)表于 2025-3-28 08:25:28 | 只看該作者
Detecting Bad-Mouthing Attacks on Reputation Systems Using Self-Organizing Maps security, support decision-making and promote node collaboration. Nevertheless, these systems are vulnerable to deliberate false or unfair testimonies. In one scenario the attackers collude to give negative feedback on the victim in order to lower or destroy its reputation. This attack is known as
40#
發(fā)表于 2025-3-28 13:50:46 | 只看該作者
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