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Chapter 12 Two-Factor Authentication (2FA) and Multi-factor Authentication (MFA) Solutions for Secure Mobile Data Communication

  • J. Viji Gripsy , M. Sowmya , S. Meera und T. Thendral
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Cybersecurity Unlocked
Ein Kapitel aus dem Buch Cybersecurity Unlocked

Abstract

The increasing reliance on mobile platforms has increased the demand for robust, scalable, and effective data security mechanisms. This paper introduces an overall framework that combines two-factor authentication (2FA), multi-factor authentication, and ciphertext-policy attribute-based proxy re-encryption (CAPRE) using elliptic curve cryptography (ECC) to secure mobile data transmission. The system under design counteracts the limitations of traditional authentication schemes, such as vulnerability to impersonation, key compromise, and inefficient key management, by utilizing a multi-dimensional authentication model that combines knowledge-based, possession-based, and biometric authentication techniques. ECC is utilized for efficient cryptographic operations and ensuring security, making the framework suitable for low-resource environments. CAPRE enables careful access control and secure delegation of decryption authority without exposing plaintext data. Experimental tests demonstrate the framework’s efficacy in curbing encryption, decryption, re-encryption times, and energy consumption without compromising good resistance to phishing, brute force, and man-in-the-middle attacks. The results confirm that the proposed approach greatly enhances data security, authentication integrity, and computational efficiency, rendering it the best for current mobile contexts.

Abstract

The increasing reliance on mobile platforms has increased the demand for robust, scalable, and effective data security mechanisms. This paper introduces an overall framework that combines two-factor authentication (2FA), multi-factor authentication, and ciphertext-policy attribute-based proxy re-encryption (CAPRE) using elliptic curve cryptography (ECC) to secure mobile data transmission. The system under design counteracts the limitations of traditional authentication schemes, such as vulnerability to impersonation, key compromise, and inefficient key management, by utilizing a multi-dimensional authentication model that combines knowledge-based, possession-based, and biometric authentication techniques. ECC is utilized for efficient cryptographic operations and ensuring security, making the framework suitable for low-resource environments. CAPRE enables careful access control and secure delegation of decryption authority without exposing plaintext data. Experimental tests demonstrate the framework’s efficacy in curbing encryption, decryption, re-encryption times, and energy consumption without compromising good resistance to phishing, brute force, and man-in-the-middle attacks. The results confirm that the proposed approach greatly enhances data security, authentication integrity, and computational efficiency, rendering it the best for current mobile contexts.

Kapitel in diesem Buch

  1. Frontmatter I
  2. Contents V
  3. Chapter 1 Emerging Cyber Threats: Challenges, Impacts, and Proactive Defenses in the Digital Age 1
  4. Chapter 2 Silent Guardians: Proactive Approaches to Modern Cyber Threats 31
  5. Chapter 3 Data Science for Threat Detection and Analysis 59
  6. Chapter 4 An Integrated Approach: Merging Cybersecurity, AI, and Threat Detection 87
  7. Chapter 5 Cybersecurity Analytics: A Review of Challenges and the Role of Machine Learning and Deep Learning in Threat Detection 103
  8. Chapter 6 Hardware-Based Authentication Techniques for Secure Data Transmission in IoT Edge Computing 141
  9. Chapter 7 Securing the IoT Networks Using a Deep Learning Paradigm for Intrusion Detection 161
  10. Chapter 8 Hybrid Malware Detection and Classification Using Explainable Deep Neural Network 177
  11. Chapter 9 Light POW for Smart Grid Communication 201
  12. Chapter 10 Zero Trust Architecture – A Beginner’s Guide 227
  13. Chapter 11 Post-quantum Cryptography for Enhanced Authentication in Mobile Data Communication: Resilience Against Quantum Attacks 265
  14. Chapter 12 Two-Factor Authentication (2FA) and Multi-factor Authentication (MFA) Solutions for Secure Mobile Data Communication 287
  15. Chapter 13 Artificial Intelligence and Machine Learning in Cybersecurity 313
  16. Chapter 14 Enhancing IoT Security with Zero Trust Networking: Protecting Wireless Sensors, Edge Devices, and Cloud Environments 343
  17. Chapter 15 Biometric Authentication Methods for Mobile Devices: Exploring Fingerprint, Face Recognition, and Iris Scanning 365
  18. Chapter 16 Robust Dynamic Voice-Based Key Generation Using Novel Fuzzy Extraction, Averaged Thresholding, and Hamming Enhancement Techniques 385
  19. Chapter 17 Enhancing Cybersecurity with Artificial Intelligence and Machine Learning Techniques 413
  20. Chapter 18 Firewall and IDS in Cybersecurity 439
  21. Index
https://doi.org/10.1515/9783111712895-012

Kapitel in diesem Buch

  1. Frontmatter I
  2. Contents V
  3. Chapter 1 Emerging Cyber Threats: Challenges, Impacts, and Proactive Defenses in the Digital Age 1
  4. Chapter 2 Silent Guardians: Proactive Approaches to Modern Cyber Threats 31
  5. Chapter 3 Data Science for Threat Detection and Analysis 59
  6. Chapter 4 An Integrated Approach: Merging Cybersecurity, AI, and Threat Detection 87
  7. Chapter 5 Cybersecurity Analytics: A Review of Challenges and the Role of Machine Learning and Deep Learning in Threat Detection 103
  8. Chapter 6 Hardware-Based Authentication Techniques for Secure Data Transmission in IoT Edge Computing 141
  9. Chapter 7 Securing the IoT Networks Using a Deep Learning Paradigm for Intrusion Detection 161
  10. Chapter 8 Hybrid Malware Detection and Classification Using Explainable Deep Neural Network 177
  11. Chapter 9 Light POW for Smart Grid Communication 201
  12. Chapter 10 Zero Trust Architecture – A Beginner’s Guide 227
  13. Chapter 11 Post-quantum Cryptography for Enhanced Authentication in Mobile Data Communication: Resilience Against Quantum Attacks 265
  14. Chapter 12 Two-Factor Authentication (2FA) and Multi-factor Authentication (MFA) Solutions for Secure Mobile Data Communication 287
  15. Chapter 13 Artificial Intelligence and Machine Learning in Cybersecurity 313
  16. Chapter 14 Enhancing IoT Security with Zero Trust Networking: Protecting Wireless Sensors, Edge Devices, and Cloud Environments 343
  17. Chapter 15 Biometric Authentication Methods for Mobile Devices: Exploring Fingerprint, Face Recognition, and Iris Scanning 365
  18. Chapter 16 Robust Dynamic Voice-Based Key Generation Using Novel Fuzzy Extraction, Averaged Thresholding, and Hamming Enhancement Techniques 385
  19. Chapter 17 Enhancing Cybersecurity with Artificial Intelligence and Machine Learning Techniques 413
  20. Chapter 18 Firewall and IDS in Cybersecurity 439
  21. Index
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Heruntergeladen am 24.1.2026 von https://www.degruyterbrill.com/document/doi/10.1515/9783111712895-012/html
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