NFC technology is considered extremely secure for communication and the number of phones that can support NFC is also at a rise. The technology is gaining worldwide recognition and as it is easy to implement and since it is really economical numerous applications are using it. Most of NFC applications involve the usage of tags, which can easily be duplicated or can be replaced by a fake one. Therefore, though the technology is so useful and secure, this weakness makes it vulnerable to certain attacks.
NFC has numerous applications but in this thesis, I will be discussing various security threats related to NFC applications involving NFC tag and an NFC enabled smartphone, for example smart posters. This thesis will evaluate various security threats like phishing, exposure to adult content etc., what they are and how an attacker can carry out these attacks. Further discussion will be on what an artificial neural network (ANN) is and how it can be used to eliminate these threats. The thesis also proposes a security model that will use ANN, to provide security against threats and will also provide user confidentiality, anonymity and privacy, and a category classifier to increase the overall efficiency of the model and to decrease the memory usage, and will also provide users with an added feature of personalizing their security according to their requirements.
Table of Contents
Abstract
Chapter 1 Introduction
Chapter 2
Background
2.1 Near Field Communication
2.1.1 Tag Reader/Writer Mode
2.1.2 Peer to Peer Mode
2.1.3 Card Emulation Mode
2.2 NFC tags
2.2.1 Tag types
2.3 NFC Data Exchange Format (NDEF)
2.4 Reading NDEF data from an NFC tag
2.5 Cryptography
2.5.1 Symmetric Key Cryptography
2.5.2 Public Key Cryptography
2.6 Artificial Neural Network (ANN)
2.7 Category Classifier
Chapter 3
NFC Security Threats
3.1 Exposure to Adult/Objectionable content
3.2 Phishing
3.3 Automated malware download and malicious web pages
3.4 Eavesdropping
3.5 Data Corruption
3.6 Data Modification
Chapter 4
Counter-Measures
4.1 Exposure to Adult/Objectionable content
4.2 Phishing
4.3 Automated malware downloads and malicious websites
Chapter 5
Proposed Security Model
5.1 Components
5.2 User Sign-Up
5.3 Working
5.3.1 Personalised Security List
5.3.2 Data Uploading
5.3.3 Data Retrieval
5.4 Anonymity
Chapter 6
Conclusion and Future Work
6.1 Conclusion
6.2 Future work
Bibliography
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Upload your own papers! Earn money and win an iPhone X. -
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