book

Cyber Security and Network Security

by Sabyasachi Pramanik, Debabrata Samanta, M. Vinay, Abhijit Guha

April 2022

Intermediate to advanced

320 pages

7h 49m

English

Wiley-Scrivener

Read now

Unlock full access

1.1 Introduction1.2 Background and Related Works1.3 System Design and Architecture1.4 Methodology1.5 Performance Analysis1.6 Future Research Direction1.7 ConclusionReferences
2.1 Introduction2.2 Aim of the Study2.3 Motivation for the Study2.4 Literature Review2.5 Research Methodology2.6 Testing Environment Plan2.7 Testing2.8 Recommendations2.9 Limitations of Present Study2.10 Conclusions2.11 Scope for the Future WorkAcknowledgementsReferences
3.1 Introduction3.2 Background and Related Works3.3 Proposed System Design Architecture3.4 Methodology3.5 Performance Analysis3.6 Future Research Direction3.7 ConclusionReferences
4.1 Introduction4.2 Related Work4.3 ConclusionReferences

5.1 Introduction5.2 Preliminaries5.3 Blockchain-Based Identity Management System5.4 Discussion5.5 Conclusion5.6 Future ScopeReferences
6.1 Introduction6.2 Convolution Network Learning6.3 Recurrent Neural Networks6.4 Long Short-Term Memory Networks6.5 Back Propagation in Neural Networks6.6 Literature Survey on Neural Networks in Steganography6.7 Optimization Algorithms in Neural Networks6.8 ConclusionReferences
7.1 Introduction7.2 Problem Formulation7.3 Proposed Mechanism7.4 Experimental Results7.5 Future Scope7.6 ConclusionReferences
8.1 Introduction8.2 Review of Literature8.3 Methodology Used8.4 Results and Discussion8.5 ConclusionsReferences
9.1 Introduction9.2 Overview of 5G9.3 Key Enabling Techniques for 5G9.4 5G Green Network9.5 5G Technologies: Security and Privacy Issues9.6 5G-GN Assets and Threats9.7 5G-GN Security Strategies and Deployments9.8 Risk Analysis of 5G Applications9.9 Countermeasures Against Security and Privacy Risks9.10 Protecting 5G Green Networks Against Attacks9.11 Future Challenges9.12 ConclusionReferences
10.1 Introduction10.2 Literature Survey10.3 Problem Statement10.4 Green it Using Virtualization10.5 Proposed Work10.6 ConclusionAcknowledgmentsReferences
11.1 Introduction to Big Data11.2 Technology Used to Big Data11.3 Working Process of Techniques11.4 Proposed Work11.5 Comparative Analysis11.6 Conclusion and Future ScopeReferences

Content preview from Cyber Security and Network Security

4Robust Fraud Detection Mechanism

Balajee Maram¹^*, Veerraju Gampala², Satish Muppidi¹ and T. Daniya³

¹Department of CSE, GMR Institute of Technology, Rajam, Srikakulam, Andhra Pradesh, India

²Department of Computer Science and Engineering, KoneruLakshmaiah Education Foundation, Vaddeswaram, Guntur, Andhra Pradesh, India

³Department of IT, GMR Institute of Technology, Rajam, Srikakulam, Andhra Pradesh, India

Abstract

In today’s world, fraud is one of the leading sources of significant financial consequences, not just for businesses but also for personal customers. The extraction of user profiles based on their past transaction data, and then determining whether or not an incoming transaction is a fraud based on their profiles, is an essential method of detecting fraud. The proposed blockchain method allows certified users to store, examine, and exchange digital data in a secure atmosphere, which aids in the development of trust, integrity, and visibility in online business relationships. Blockchain systematically analyzes the robustness of blockchain-based reputation systems, which focuses on the extraction and transmission to customers in a safe and trustworthy manner. Blockchain employs cryptographic hashes, which are produced from summarized shopping blocks that are signed and transmitted that provides a safe and secured online shopping for an highly efficient manner without any interference of third parties.

Keywords: Blockchain, robust, cryptographic hashes, key frames, ...