Security Designs for the Cloud, IoT, and Social Networking

Erscheinungsjahr 2022
ISBN: 978-1-77469-286-8
Verlag: Arcler Press
Format: PDF
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 260 Seiten, Electronic book text, Format (B × H): 152 mm x 229 mm

Along with providing an overview of cloud computing, this book talks about the various other dimensions involved in it such as the risk issues and security challenges in cloud computing. It highlights the appplication safety and service vulnerability in cloud network. It also gives an introduction to IoT security and its open challenges, IoT architecture security and the introduction into the social network and its security issues, as well as the cyberspace security in the digital age.

Fachgebiete

• Mathematik | Informatik EDV | Informatik Technische Informatik Computersicherheit
• Mathematik | Informatik EDV | Informatik EDV & Informatik Allgemein

Inhaltsverzeichnis

- Chapter 1 Cloud Computing Overview
- Chapter 2 Risks Issues and Security Challenges in Cloud Computing
- Chapter 3 Application Safety and Service Vulnerability in Cloud Network
- Chapter 4 Introduction to Internet of Things (IoT) Security and Its Open Challenges
- Chapter 5 IoT Architecture Security
- Chapter 6 Security in Enabling Technologies
- Chapter 7 Introduction to Social Network and Its Security Issues
- Chapter 8 Cyberspace Security in Digital Age

Über Autor(innen)

Adele Kuzmiakova is a computational engineer focusing on solving problems in machine learning, deep learning, and computer vision. Adele attended Cornell University in New York, United States for her undergraduate studies. She studied engineering with a focus on applied math. While at Cornell, she developed close relationships with professors, which enabled her to get involved in academic research to get hands-on experience with solving computational problems. She was also selected to be Accel Roundtable on Entrepreneurship Education (REE) Fellow at Stanford University and spent 3 months working on entrepreneurship projects to get a taste of entrepreneurship and high-growth ventures in engineering and life sciences. The program culminated in giving a presentation on the startup technology and was judged by Stanford faculty and entrepreneurship experts in Silicon Valley. After graduating from Cornell, Adele worked as a data scientist at Swiss Federal Institute of Technology in Lausanne, Switzerland where she focused on developing algorithms and graphical models to analyze chemical pathways in the atmosphere. Adele also pursued graduate studies at Stanford University in the United States where she entered as a recipient of American Association of University Women International Fellowship. The Fellowship enabled her to focus on tackling important research problems in machine learning and computer vision. Some research problems she worked on at Stanford include detecting air pollution from outdoor public webcam images. Specifically, she modified and set up a variety of pre-trained architectures, such as DehazeNet, VGG, and ResNet, on public webcam images to evaluate their ability to predict air quality based on the degree of haze on pictures. Other deep learning problems Adele worked on include investigating the promise of second-order optimizers in deep learning and using neural networks to predict sequences of data in energy consumption. Adele also places an emphasis on continual education and served as a Student Leader in PyTorch scholarship challenge organized by Udacity. Her roles as the Student Leader were helping students debug their code to train neural networks with PyTorch and providing mentorship on technical and career aspects. Her hobbies include skiing, playing tennis, cooking, and meeting new people.