Advances in Cyber Security and Intelligent Analytics
CRC Press (Verlag)
978-1-032-21601-0 (ISBN)
We live in a digital world, where we use digital tools and smart devices to communicate over the Internet. In turn, an enormous amount of data gets generated. The traditional computing architectures are inefficient in storing and managing this massive amount of data. Unfortunately, the data cannot be ignored as it helps businesses to make better decisions, solve problems, understand performance, improve processes, and understand customers. Therefore, we need modern systems capable of handling and managing data efficiently. In the past few decades, many distributed computing paradigms have emerged, and we have noticed a substantial growth in the applications based on such emerging paradigms. Some well-known emerging computing paradigms include cloud computing, fog computing, and edge computing, which have leveraged the increase in the volume of data being generated every second. However, the distributed computing paradigms face critical challenges, including network management and cyber security. We have witnessed the development of various networking models—IoT, SDN, and ICN—to support modern systems requirements. However, they are undergoing rapid changes and need special attention. The main issue faced by these paradigms is that traditional solutions cannot be directly applied to address the challenges. Therefore, there is a significant need to develop improved network management and cyber security solutions. To this end, this book highlights the challenges faced by emerging paradigms and presents the recent developments made to address the challenges. More specifically, it presents a detailed study on security issues in distributed computing environments and their possible solutions, followed by applications of medical IoT, deep learning, IoV, healthcare, etc.
Abhishek Verma, Vrijendra Singh
1 Edge computing-enabled secure information-centric networking: Privacy challenges, benefits, and future trends
KAVISH TOMAR, SARISHMA DANGI, AND SACHIN SHARMA
2 Weighted attack graphs and behavioral cyber game theory for cyber risk quantification
FLORIAN K. KAISER, MARCUS WIENS, AND FRANK SCHULTMANN
3 NetFlow-based botnet detection in IoT edge environment using ensemble gradient boosting machine learning framework
D. SANTHADEVI AND B. JANET
4 Exploring the possibility of blockchain and smart contract-based digital certificate
P. RAVI KUMAR, P. HERBERT RAJ, AND SHARUL TAJUDDIN
5 Senso Scale: A framework to preserve privacy over cloud using sensitivity range
NIHARIKA SINGH, ISHU GUPTA, AND ASHUTOSH KUMAR SINGH
6 Addressing the cybersecurity issues in cloud computing
SHIVANSHU OLIYHAN AND CHANDRASHEKHAR AZAD
7 Role of medical image encryption algorithms in cloud platform for teleradiology applications
SIJU JOHN AND S. N. KUMAR
8 Machine-learning approach for detecting cyberattacks in Medical Internet of Things
THULASI M. SANTHI AND M. C. HELEN MARY
9 Secure IoV-enabled systems at Fog Computing: Layout, security, and optimization algorithms and open issues
ANSHU DEVI, RAMESH KAIT, AND VIRENDER RANGA
10 A capability maturity model and value judgment systems for a distributed network of ethical and context aware digital twin agents
MEZZOUR GHITA, BENHADOU SIHAM, MEDROMI HICHAM, AND GRIGUER HAFID
11 A detailed cram on artificial intelligence industrial systems 4.0
P. DHARANYADEVI, R. SRI SAIPRIYA, T. C. ADITYAA, B. SENTHILNAYAKI, M. JULIE THERESE, A. DEVI, AND K. VENKATALAKSHMI
12 Ensuring liveliness property in safety-critical systems
ANKUR MAURYA, SHARAD NIGAM, AND DIVYA KUMAR
13 Machine learning for intelligent analytics
JYOTI POKHARIYA, PANKAJ KUMAR MISHRA, AND JYOTI KANDPAL
14 Secure 3D route optimization of combat vehicles in war field using IoV
ALOK NATH PANDEY, PIYUSH AGARWAL, AND SACHIN SHARMA
15 Healthcare therapy for treating teenagers with internet addiction using behavioral patterns and neuro-feedback analysis
B. DHANALAKSHMI, K. SELVAKUMAR, AND L. SAI RAMESH
16 Containerization in cloud computing for OS-level virtualization
MANOJ KUMAR PATRA, BIBHUDATTA SAHOO, AND ASHOK KUMAR TURUK
17 An adaptive deep learning approach for stock price forecasting
RESHMA MO, JITENDRA KUMAR, AND ABHISHEK VERMA
| Erscheinungsdatum | 10.01.2023 |
|---|---|
| Zusatzinfo | 33 Tables, black and white; 78 Line drawings, black and white; 7 Halftones, black and white; 85 Illustrations, black and white |
| Verlagsort | London |
| Sprache | englisch |
| Maße | 156 x 234 mm |
| Gewicht | 576 g |
| Themenwelt | Informatik ► Netzwerke ► Sicherheit / Firewall |
| Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik | |
| ISBN-10 | 1-032-21601-8 / 1032216018 |
| ISBN-13 | 978-1-032-21601-0 / 9781032216010 |
| Zustand | Neuware |
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