By Aboul Ella Hassanien, Tai-Hoon Kim, Janusz Kacprzyk, Ali Ismail Awad

This quantity offers fresh learn in cyber defense and experiences how firms can achieve aggressive benefits through utilising the various protection ideas in real-world situations. the amount presents stories of cutting–edge applied sciences, algorithms, purposes and insights for bio-inspiring cyber security-based structures. The e-book might be a important significant other and accomplished reference for either postgraduate and senior undergraduate scholars who're taking a path in cyber safety. the quantity is equipped in self-contained chapters to supply maximum studying flexibility.

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Extra resources for Bio-inspiring Cyber Security and Cloud Services: Trends and Innovations

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We also retrieved the output of Nessus [38], a network vulnerability scanner, and Nmap [39], a network mapping utility, to check for known network vulnerabilities and network port status. Finally, we collected log files for CERIAS services as follows: FTP log messages, error messages and requests associated with FTP, a listing of files transferred over FTP, HTTP log messages, HTTP requests, errors associated with HTTP requests, HTTPS (SSL) requests, HTTPS (SSL) errors associated with HTTPS, SSH logs which includes error messages associated with SSH, and Firewall Router log messages which contain a list of blocked network packets from outside world.

The total correlation time by ABCM is calculated as follows: TABCM = Tlearning + Tcorrelation where Tcorrelation of ACCL components as optimal serial sequence without unneeded components and in proper order is as follow: n Tcorrelation = tj j=1 1 A Bio-inspired Comprehensive Distributed Correlation Approach 15 where n is the count of ACCL components. Total TABCM is much lower than total correlation time by CAM. 2 Dynamic Parallel Correlation Model Dynamic Parallel Correlation Model DPCM [34] has parallel processing correlation to assure using the suitable component and its order.

DACM determines the most repeated IPs as sources for different attacks. DACM produces maximum priority report, which displays the most common IPs which was detected by different agent’s results or by DACM central agent. The report shows the top n IPs which has the highest count of repeated alerts for different alerts type and/or reconnaissance activity. 6 DACM summary result Day 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 Alerts count 28664 46703 54759 34303 51823 49609 34879 152240 15175 11788 49336 39786 27753 70686 36072 57598 52035 25139 Detection of correlated alerts IDS Other Logs DACM Detection Percentage IDS Other logs DACM 277 393 380 449 449 458 373 469 248 166 444 414 427 451 411 421 389 334 45 62 57 60 60 59 51 58 50 37 59 54 54 59 56 61 63 57 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 339 241 290 304 300 322 357 342 248 288 306 354 370 317 322 266 224 248 616 634 670 753 749 780 730 811 496 454 750 768 797 768 733 687 613 582 55 38 43 40 40 41 49 42 50 63 41 46 46 41 44 39 37 43 DACM summarizes the total daily alerts and classify them depending on their source of detection.

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