標題: Titlebook: Deep Learning Techniques for IoT Security and Privacy; Mohamed Abdel-Basset,Nour Moustafa,Weiping Ding Book 2022 The Editor(s) (if applica [打印本頁] 作者: Grievous 時間: 2025-3-21 17:04
書目名稱Deep Learning Techniques for IoT Security and Privacy影響因子(影響力)
書目名稱Deep Learning Techniques for IoT Security and Privacy影響因子(影響力)學科排名
書目名稱Deep Learning Techniques for IoT Security and Privacy網(wǎng)絡公開度
書目名稱Deep Learning Techniques for IoT Security and Privacy網(wǎng)絡公開度學科排名
書目名稱Deep Learning Techniques for IoT Security and Privacy被引頻次
書目名稱Deep Learning Techniques for IoT Security and Privacy被引頻次學科排名
書目名稱Deep Learning Techniques for IoT Security and Privacy年度引用
書目名稱Deep Learning Techniques for IoT Security and Privacy年度引用學科排名
書目名稱Deep Learning Techniques for IoT Security and Privacy讀者反饋
書目名稱Deep Learning Techniques for IoT Security and Privacy讀者反饋學科排名
作者: FILTH 時間: 2025-3-21 21:53
Philosophy of Hull Structure Designibutes of IoT systems that might possibly threaten the security of the system. Firstly, the definition and of the IoT system and the detailed description of its architecture are presented along with a taxonomy for dividing its architecture into layers with different complementary roles. Secondly, th作者: 放大 時間: 2025-3-22 03:43 作者: 注意力集中 時間: 2025-3-22 07:56
Application of the VENUS Design System, determinations throughout time, which is a popular and broad challenge explored in lots of technical and industrial disciplines. RL nativey integrates an additional dimension (which is typically time, however not of necessity) into learning process, which lays it considerably near to the social awa作者: 小步走路 時間: 2025-3-22 11:10
https://doi.org/10.1007/978-981-10-0269-4ities are thought to come up with multiple crucial smart IoT applications i.e., smart manufacturing, smart transportation, autonomous driving/flight, smart buildings, smart healthcare, smart grid, and so many others (Lo et al. in ACM Comput. Surv., 2021). Effective deployment of these IoT applicatio作者: instructive 時間: 2025-3-22 16:39 作者: instructive 時間: 2025-3-22 19:44 作者: 協(xié)奏曲 時間: 2025-3-23 00:27 作者: 輕而薄 時間: 2025-3-23 02:52 作者: 廚房里面 時間: 2025-3-23 08:27
Deep Reinforcement Learning for Secure Internet of Things, determinations throughout time, which is a popular and broad challenge explored in lots of technical and industrial disciplines. RL nativey integrates an additional dimension (which is typically time, however not of necessity) into learning process, which lays it considerably near to the social awareness of AI.作者: 巨碩 時間: 2025-3-23 13:15 作者: commonsense 時間: 2025-3-23 15:58
Mohamed Abdel-Basset,Nour Moustafa,Weiping DingPresents a Machine Learning Approach to Conducting Digital Forensics.Contains state-of-the-art research and shows how to teach hands-on incident response and digital forensic courses.Covers the applic作者: 轉折點 時間: 2025-3-23 20:04
Studies in Computational Intelligencehttp://image.papertrans.cn/d/image/264582.jpg作者: inundate 時間: 2025-3-24 00:48
https://doi.org/10.1007/978-3-030-89025-4Cyber Forensics; Digital Forensic Education; Digital Forensics; Virtual Machines Forensics; Social Media作者: 儀式 時間: 2025-3-24 03:00
978-3-030-89027-8The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl作者: 討厭 時間: 2025-3-24 10:06
https://doi.org/10.1007/978-3-540-88445-3As IoT technology becomes an integral part of everyday life, enhancing productivity for businesses through automation, it should come as no surprise that attackers would seek to exploit these systems and the services they provide for profit.作者: 全能 時間: 2025-3-24 11:43 作者: Palpate 時間: 2025-3-24 18:40
Design of Sustainable Product Life CyclesThis chapter elaborates on the potential of unsupervised deep learning solutions for assuring the security of IoT-based systems to give the reader an insightful discussion of how these solutions could satisfy the IoT security requirements necessary to realize a reliable and trustworthy IoT environment.作者: 北極人 時間: 2025-3-24 19:58 作者: Criteria 時間: 2025-3-25 00:42
https://doi.org/10.1007/978-981-10-0269-4The central intention of this chapter is to discuss the primary security challenges in internet of things (IoT) environments with the main emphasis on the opportunities for deep learning for securing and maintaining the privacy of IoT-based systems.作者: Gene408 時間: 2025-3-25 04:49
Digital Forensics in Internet of Things,As IoT technology becomes an integral part of everyday life, enhancing productivity for businesses through automation, it should come as no surprise that attackers would seek to exploit these systems and the services they provide for profit.作者: 咒語 時間: 2025-3-25 08:09 作者: Decline 時間: 2025-3-25 15:40 作者: resistant 時間: 2025-3-25 19:37
Semi-supervised Deep Learning for Secure Internet of Things,Previous chapters demonstrate the great success achieved by principally in supervised settings, by leveraging a larger volume of precisely annotated dataset. Nevertheless, annotated data instances are frequently complicated, costly, or laborious to acquire.作者: FEMUR 時間: 2025-3-25 21:38
Challenges, Opportunities, and Future Prospects,The central intention of this chapter is to discuss the primary security challenges in internet of things (IoT) environments with the main emphasis on the opportunities for deep learning for securing and maintaining the privacy of IoT-based systems.作者: 角斗士 時間: 2025-3-26 01:17 作者: ALOFT 時間: 2025-3-26 08:19 作者: 包租車船 時間: 2025-3-26 09:12
Internet of Things, Preliminaries and Foundations,ibutes of IoT systems that might possibly threaten the security of the system. Firstly, the definition and of the IoT system and the detailed description of its architecture are presented along with a taxonomy for dividing its architecture into layers with different complementary roles. Secondly, th作者: 澄清 時間: 2025-3-26 14:20 作者: 注視 時間: 2025-3-26 19:41 作者: Charitable 時間: 2025-3-26 22:16
Federated Learning for Privacy-Preserving Internet of Things,ities are thought to come up with multiple crucial smart IoT applications i.e., smart manufacturing, smart transportation, autonomous driving/flight, smart buildings, smart healthcare, smart grid, and so many others (Lo et al. in ACM Comput. Surv., 2021). Effective deployment of these IoT applicatio作者: 可忽略 時間: 2025-3-27 02:17
1860-949X dent response and digital forensic courses.Covers the applic.This book states that the major aim audience are people who have some familiarity with Internet of things (IoT) but interested to get a comprehensive interpretation of the role of deep Learning in maintaining the security and privacy of Io作者: 呼吸 時間: 2025-3-27 06:48 作者: elucidate 時間: 2025-3-27 09:46
Philosophy of Hull Structure Designh a very large number of heterogeneous objects and implanting sensors to them leads to some degree of digital intelligence at devices that, empowering them to communicate instantaneous data with no human intervention.作者: FLAIL 時間: 2025-3-27 17:19
Introduction Conceptualization of Security, Forensics, and Privacy of Internet of Things: An Artifih a very large number of heterogeneous objects and implanting sensors to them leads to some degree of digital intelligence at devices that, empowering them to communicate instantaneous data with no human intervention.作者: 要控制 時間: 2025-3-27 18:49
Book 2022 interpretation of the role of deep Learning in maintaining the security and privacy of IoT. A reader should be friendly with Python and the basics of machine learning and deep learning. Interpretation of statistics and probability theory will be a plus but is not certainly vital for identifying mos作者: Synovial-Fluid 時間: 2025-3-28 01:40
https://doi.org/10.1007/978-981-10-0269-4T devices is believed to rises to 125 billion by 2030. This in turn reflects expected large growth in the amount of IoT-generated data. some other statistics show that, by 2025, the size of IoT-generated data will grow up to reach 79.4 zettabytes (ZB).作者: 苦澀 時間: 2025-3-28 04:56 作者: handle 時間: 2025-3-28 06:50
Internet of Things, Preliminaries and Foundations,e concepts of cloud computing, fog computing, and edge computing are discussed and compared in view of IoT systems. Finally, the learned lessons are summarized and pointed out in the last section of this chapter.作者: Sciatica 時間: 2025-3-28 11:50
1860-949X T. A reader should be friendly with Python and the basics of machine learning and deep learning. Interpretation of statistics and probability theory will be a plus but is not certainly vital for identifying most of the book‘s material..978-3-030-89027-8978-3-030-89025-4Series ISSN 1860-949X Series E-ISSN 1860-9503 作者: macabre 時間: 2025-3-28 14:34
Humiliation and Shame in Season One,ome in episode four (‘Cancer Man’, 1.4). Jesse’s unexpected and somewhat unwelcome visit reveals, in his promising childhood drawings, a past of diligent application; he tries to recover this quality of character in episode five (‘Gray Matter’, 1.5) through his self-guided attempts to meet Walt’s st作者: 短程旅游 時間: 2025-3-28 21:49
Darstellungstheorie der Drehgruppe,Bevor’ wir die irreduziblen Darstellungen der Lorentzgruppe suchen, behandeln wir das gleiche Problem für die Drehgruppe SO(3,.). Vier Gründe sind dafür ausschlaggebend:作者: instulate 時間: 2025-3-29 02:49
