Open Access Journal

ISSN : 2394-2320 (Online)

International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Monthly Journal for Computer Science and Engineering

Open Access Journal

International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Monthly Journal for Computer Science and Engineering

ISSN : 2394-2320 (Online)

Call For Paper : Vol 11, Issue 08, August 2024

Call for Paper

Vol 11, Issue 08, August 2024

Indexing

Security Evaluation Of Pattern Classifiers Under Attack

Author : B Soundarya 1 Sai Manogna 2 Prasad B 3

PDF

Date of Publication :7th March 2016

Abstract: Mobile nodes in military environments such as a battlefield or a hostile region are likely to suffer from intermittent network connectivity and frequent partitions. Disruption-tolerant network (DTN) technologies are becoming successful solutions that allow wireless devices carried by soldiers to communicate with each other and access the confidential information or command reliably by exploiting external storage nodes. Some of the most challenging issues in this scenario are the enforcement of authorization policies and the policies update for secure data retrieval. Cipher text-policy attribute-based encryption (CP-ABE) is a promising cryptographic solution to the access control issues. However, the problem of applying CP-ABE in decentralized DTNs introduces several security and privacy challenges with regard to the attribute revocation, key escrow, and coordination of attributes issued from different authorities. In this paper, we propose a secure data retrieval scheme using CP-ABE for decentralized DTNs where multiple key authorities manage their attributes independently. We demonstrate how to apply the proposed mechanism to securely and efficiently manage the confidential data distributed in the disruption-tolerant military network.

Reference :

    1. J. Burgess, B. Gallagher, D. Jensen, and B. N. Levine, “Maxprop: Routing for vehicle-based disruption tolerant networks,” in Proc. IEEE INFOCOM, 2006, pp. 1–11.
    2. M. Chuah and P. Yang, “Node density-based adaptive routing scheme for disruption tolerant networks,” in Proc. IEEE MILCOM, 2006, pp. 1–6.
    3. M. M. B. Tariq, M. Ammar, and E. Zequra, “Mesage ferry route design for sparse ad hoc networks with mobile nodes,” in Proc. ACM MobiHoc, 2006, pp. 37–48.
    4. S. Roy andM. Chuah, “Secure data retrieval based on ciphertext policy attribute-based encryption (CP-ABE) system for the DTNs,” Lehigh CSE Tech. Rep., 2009.
    5. M. Chuah and P. Yang, “Performance evaluation of content-based information retrieval schemes for DTNs,” in Proc. IEEE MILCOM, 2007, pp. 1–7
    6. M. Kallahalla, E. Riedel, R. Swaminathan, Q. Wang, and K. Fu, “Plutus: Scalable secure file sharing on untrusted storage,” in Proc. Conf. File Storage Technol., 2003, pp. 29–42.
    7. L. Ibraimi, M. Petkovic, S. Nikova, P. Hartel, and W. Jonker, “Mediated ciphertext-policy attribute-based encryption and its application,” in Proc. WISA, 2009, LNCS 5932, pp. 309–323
    8. N. Chen, M. Gerla, D. Huang, and X. Hong, “Secure, selective group broadcast in vehicular networks using dynamic attribute based encryption,” in Proc. Ad Hoc Netw. Workshop, 2010, pp. 1–8.
    9. D. Huang and M. Verma, “ASPE: Attributebased secure policy enforcement in vehicular ad hoc networks,” Ad Hoc Netw., vol. 7, no. 8, pp. 1526– 1535, 2009
    10. A. Lewko and B. Waters, “Decentralizing attribute-based encryption,” Cryptology ePrint Archive: Rep. 2010/351, 2010.
    11. A. Sahai and B. Waters, “Fuzzy identity-based encryption,” in Proc. Eurocrypt, 2005, pp. 457–473.
    12. V. Goyal, O. Pandey, A. Sahai, and B. Waters, “Attribute-based encryption for fine-grained access control of encrypted data,” in Proc. ACM Conf. Comput. Commun. Security, 2006, pp. 89–98.
    13. J. Bethencourt, A. Sahai, and B. Waters, “Ciphertext-policy attributebased encryption,” in Proc. IEEE Symp. Security Privacy, 2007, pp. 321– 334. 38
    14. R. Ostrovsky, A. Sahai, and B. Waters, “Attribute-based encryption with non-monotonic access structures,” in Proc. ACM Conf. Comput. Commun. Security, 2007, pp. 195–203.
    15. S. Yu, C. Wang, K. Ren, and W. Lou, “Attribute based data sharing with attribute revocation,” in Proc. ASIACCS, 2010, pp. 261–270

    1. R.N. Rodrigues, L.L. Ling, and V. Govindaraju, “Robustness of Multimodal Biometric Fusion Methods against Spoof Attacks,” J. Visual Languages and Computing, vol. 20, no. 3, pp. 169- 179, 2009.
    2. P. Johnson, B. Tan, and S. Schuckers, “Multimodal Fusion Vulnerability to Non-Zero Effort (Spoof) Imposters,” Proc. IEEE Int’l Workshop Information Forensics and Security, pp. 1-5, 2010
    3. P. Fogla, M. Sharif, R. Perdisci, O. Kolesnikov, and W. Lee, “Polymorphic Blending Attacks,” Proc. 15th Conf. USENIX Security Symp., 2006. [4] G.L. Wittel and S.F. Wu, “On Attacking Statistical Spam Filters,” Proc. First Conf. Email and Anti-Spam, 2004
    4. D. Lowd and C. Meek, “Good Word Attacks on Statistical Spam Filters,” Proc. Second Conf. Email and Anti-Spam, 2005.
    5. A. Kolcz and C.H. Teo, “Feature Weighting for Improved Classifier Robustness,” Proc. Sixth Conf. Email and Anti-Spam, 2009.
    6. D.B. Skillicorn, “Adversarial Knowledge Discovery,” IEEE Intelligent Systems, vol. 24, no. 6, Nov./Dec. 2009.
    7. D. Fetterly, “Adversarial Information Retrieval: The Manipulation of Web Content,” ACM Computing Rev., 2007.
    8. R.O. Duda, P.E. Hart, and D.G. Stork, Pattern Classification. Wiley-Interscience Publication, 2000.
    9. N. Dalvi, P. Domingos, Mausam, S. Sanghai, and D. Verma, “Adversarial Classification,” Proc. 10th ACM SIGKDD Int’l Conf. Knowledge Discovery and Data Mining, pp. 99-108, 2004.

Recent Article