4 options
Silicon Valley Cybersecurity Conference : Third Conference, SVCC 2022, Virtual Event, August 17–19, 2022, Revised Selected Papers / edited by Luis Bathen, Gokay Saldamli, Xiaoyan Sun, Thomas H. Austin, Alex J. Nelson.
Springer Nature - Springer Nature Link Journals and eBooks - Fully Open Access Available online
View online- Format:
- Book
- Author/Creator:
- Bathen, Luis.
- Series:
- Communications in Computer and Information Science, 1865-0937 ; 1683
- Language:
- English
- Subjects (All):
- Data protection.
- Image processing--Digital techniques.
- Image processing.
- Computer vision.
- Artificial intelligence.
- Computer engineering.
- Computer networks.
- Data and Information Security.
- Computer Imaging, Vision, Pattern Recognition and Graphics.
- Artificial Intelligence.
- Computer Engineering and Networks.
- Local Subjects:
- Data and Information Security.
- Computer Imaging, Vision, Pattern Recognition and Graphics.
- Artificial Intelligence.
- Computer Engineering and Networks.
- Physical Description:
- 1 online resource (144 pages)
- Edition:
- 1st ed. 2022.
- Place of Publication:
- Cham : Springer Nature Switzerland : Imprint: Springer, 2022.
- Summary:
- This open access book constitutes refereed proceedings of the Third Conference on Silicon Valley Cybersecurity Conference, SVCC 2022, held as virtual event, in August 17–19, 2022. The 8 full papers included in this book were carefully reviewed and selected from 10 submissions. The contributions are divided into the following thematic blocks: Malware Analysis; Blockchain and Smart Contracts; Remote Device Assessment. This is an open access book.
- Contents:
- Malware Analysis
- Robustness of Image-Based Malware Analysis
- Word Embeddings for Fake Malware Generation
- Twitter bots detection with Benford’s Law and Machine Learning
- Blockchain and Smart Contracts
- A Blockchain-based Retribution Mechanism for Collaborative Intrusion Detection
- Smart Contracts in the Cloud
- A Blockchain-based Tamper-resistant Logging Framework
- Remote Device Assessment
- Impact of Location Spoofing Attacks on Performance Prediction in Mobile Networks
- Deep IoT Monitoring: Filtering IoT Traffic Using Deep Learning.
- ISBN:
- 3-031-24049-9
- OCLC:
- 1369644381
The Penn Libraries is committed to describing library materials using current, accurate, and responsible language. If you discover outdated or inaccurate language, please fill out this feedback form to report it and suggest alternative language.