找回密码
 To register

QQ登录

只需一步,快速开始

扫一扫,访问微社区

Titlebook: Cyber Threat Intelligence; Ali Dehghantanha,Mauro Conti,Tooska Dargahi Book 2018 Springer International Publishing AG, part of Springer Na

[复制链接]
查看: 42884|回复: 54
发表于 2025-3-21 17:23:53 | 显示全部楼层 |阅读模式
书目名称Cyber Threat Intelligence
编辑Ali Dehghantanha,Mauro Conti,Tooska Dargahi
视频video
概述Focuses on cyber threat intelligence of recent threats (i.e. ransomware) within emerging IT environments (i.e. IoT, Cloud, Mobile devices).One of the first books that focuses on cyber threat intellige
丛书名称Advances in Information Security
图书封面Titlebook: Cyber Threat Intelligence;  Ali Dehghantanha,Mauro Conti,Tooska Dargahi Book 2018 Springer International Publishing AG, part of Springer Na
描述.This book provides readers with up-to-date research of emerging cyber threats and defensive mechanisms, which are timely and essential. It covers cyber threat intelligence concepts against a range of threat actors and threat tools (i.e. ransomware) in cutting-edge technologies, i.e., Internet of Things (IoT), Cloud computing and mobile devices. This book also provides the technical information on cyber-threat detection methods required for the researcher and digital forensics experts, in order to build intelligent automated systems to fight against advanced cybercrimes..The ever increasing number of cyber-attacks requires the cyber security and forensic specialists to detect, analyze and defend against the cyber threats in almost real-time, and with such a large number of attacks is not possible without deeply perusing the attack features and taking corresponding intelligent defensive actions – this in essence defines cyber threat intelligence notion. However, such intelligence would not be possible without the aid of artificial intelligence, machine learning and advanced data mining techniques to collect, analyze, and interpret cyber-attack campaigns which is covered in this book
出版日期Book 2018
关键词Cyber threat; Cyber security; Hacking; Threat intelligence; Machine learning; cyber forensics; threat anal
版次1
doihttps://doi.org/10.1007/978-3-319-73951-9
isbn_softcover978-3-030-08891-0
isbn_ebook978-3-319-73951-9Series ISSN 1568-2633 Series E-ISSN 2512-2193
issn_series 1568-2633
copyrightSpringer International Publishing AG, part of Springer Nature 2018
The information of publication is updating

书目名称Cyber Threat Intelligence影响因子(影响力)




书目名称Cyber Threat Intelligence影响因子(影响力)学科排名




书目名称Cyber Threat Intelligence网络公开度




书目名称Cyber Threat Intelligence网络公开度学科排名




书目名称Cyber Threat Intelligence被引频次




书目名称Cyber Threat Intelligence被引频次学科排名




书目名称Cyber Threat Intelligence年度引用




书目名称Cyber Threat Intelligence年度引用学科排名




书目名称Cyber Threat Intelligence读者反馈




书目名称Cyber Threat Intelligence读者反馈学科排名




单选投票, 共有 1 人参与投票
 

0票 0.00%

Perfect with Aesthetics

 

0票 0.00%

Better Implies Difficulty

 

0票 0.00%

Good and Satisfactory

 

1票 100.00%

Adverse Performance

 

0票 0.00%

Disdainful Garbage

您所在的用户组没有投票权限
发表于 2025-3-21 21:42:54 | 显示全部楼层
发表于 2025-3-22 03:11:23 | 显示全部楼层
Adaptive Traffic Fingerprinting for Darknet Threat Intelligence,ts to reduce the candidate data set to eliminate client-side traffic that is most unlikely to be responsible for server-side connections of interest. Our test results show that MITM manipulated server responses lead to expected changes received by the Tor client. Using simulation data generated by s
发表于 2025-3-22 07:36:13 | 显示全部楼层
发表于 2025-3-22 10:05:05 | 显示全部楼层
发表于 2025-3-22 15:34:07 | 显示全部楼层
Education as a Key Factor in Fighting AIDS2-bit malicious Portable Executable (PE32) Windows files and develop taxonomy for better understanding of these techniques. Afterwards, we offer a tutorial on how different machine learning techniques can be utilized in extraction and analysis of a variety of static characteristic of PE binaries and
发表于 2025-3-22 19:35:48 | 显示全部楼层
Triangles in Heterosexual HIV Transmissionreduction. Using the CorrelationAttributeEval method close to 100% precision can be maintained with a feature reduction of 59.5%. The CFSSubset filter achieves the highest feature reduction of 97.7% however with a slightly lower precision at 94.2%..Using a ranking method applied across the attribute
发表于 2025-3-22 21:33:46 | 显示全部楼层
Keynote Address: AIDS in the United Kingdomts to reduce the candidate data set to eliminate client-side traffic that is most unlikely to be responsible for server-side connections of interest. Our test results show that MITM manipulated server responses lead to expected changes received by the Tor client. Using simulation data generated by s
发表于 2025-3-23 02:41:34 | 显示全部楼层
发表于 2025-3-23 07:21:57 | 显示全部楼层
 关于派博传思  派博传思旗下网站  友情链接
派博传思介绍 公司地理位置 论文服务流程 影响因子官网 SITEMAP 大讲堂 北京大学 Oxford Uni. Harvard Uni.
发展历史沿革 期刊点评 投稿经验总结 SCIENCEGARD IMPACTFACTOR 派博系数 清华大学 Yale Uni. Stanford Uni.
|Archiver|手机版|小黑屋| 派博传思国际 ( 京公网安备110108008328) GMT+8, 2025-5-3 11:54
Copyright © 2001-2015 派博传思   京公网安备110108008328 版权所有 All rights reserved
快速回复 返回顶部 返回列表