On Constructing a Secure and Fast Key Derivation Function Based on Stream Ciphers

被引:0
|
作者
Chuah, Chai Wen [1 ]
Alawatugoda, Janaka [2 ,3 ]
Arbaiy, Nureize [4 ]
机构
[1] Guangdong Univ Sci & Technol, Dongguang, Guangdong, Peoples R China
[2] Rabdan Acad, Res & Innovat Ctr Div, Abu Dhabi, U Arab Emirates
[3] Griffith Univ, Inst Integrated & Intelligent Syst, Nathan, Qld, Australia
[4] Univ Tun Hussein Onn Malaysia, Fac Comp Sci & Informat Technol, Parit Raja, Malaysia
关键词
Key derivation functions; extractors; expanders; stream ciphers; hash functions; symmetric-key cryptography;
D O I
10.14569/IJACSA.2024.01506148
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
In order to protect electronic data, pseudorandom cryptographic keys generated by a standard function known as a key derivation function play an important role. The inputs to the function are known as initial keying materials, such as passwords, shared secret keys, and non-random strings. Existing standard secure functions for the key derivation function are based on stream ciphers, block ciphers, and hash functions. The latest secure and fast design is a stream cipher-based key derivation function ( SCKDF2 ). The security levels for key derivation functions based on stream ciphers, block ciphers, and hash functions are equal. However, the execution time for key derivation functions based on stream ciphers is faster compared to the other two functions. This paper proposes an improved design for a key derivation function based on stream ciphers, namely I-SCKDF2. - SCKDF2 . We simulate instances for the proposed I-SCKDF2 - SCKDF2 using Trivium. As a result, I-SCKDF2 - SCKDF2 has a lower execution time compared to the existing SCKDF2. The results show that the execution time taken by I-SCKDF2 - SCKDF2 to generate an n- bit cryptographic key is almost 50 percent lower than SCKDF2. The security of I-SCKDF2 - SCKDF2 passed all the security tests in the Dieharder test tool. It has been proven that the proposed I-SCKDF2 - SCKDF2 is secure, and the simulation time is faster compared to SCKDF2.
引用
收藏
页码:1486 / 1493
页数:8
相关论文
共 50 条
  • [41] A New Stream Ciphers Based on Hyperchaotic Map
    Lin Jinqiu
    Si Xicai
    2009 2ND IEEE INTERNATIONAL CONFERENCE ON COMPUTER SCIENCE AND INFORMATION TECHNOLOGY, VOL 1, 2009, : 366 - 369
  • [42] Deep Learning based Cryptanalysis of Stream Ciphers
    Mishra, Girish
    Gupta, Indivar
    Murthy, S. V. S. S. N. V. G. Krishna
    Pal, S. K.
    DEFENCE SCIENCE JOURNAL, 2021, 71 (04) : 499 - 506
  • [43] Chosen IV statistical analysis for key recovery attacks on stream ciphers
    Fischer, Simon
    Khazaei, Shahrarn
    Meier, Willi
    PROGRESS IN CRYPTOLOGY - AFRICACRYPT 2008, 2008, 5023 : 236 - +
  • [44] Improved fast correlation attacks on stream ciphers via convolutional codes
    Johansson, T
    Jönsson, F
    ADVANCES IN CRYPTOLOGY - EUROCRYPT'99, 1999, 1592 : 347 - 362
  • [45] Algebraic attacks on a class of stream ciphers with unknown output function
    N. Rajesh Pillai
    S. S. Bedi
    Designs, Codes and Cryptography, 2013, 69 : 317 - 330
  • [46] Fast correlation attacks against stream ciphers and related open problems
    Canteaut, A
    2005 IEEE INFORMATION THEORY WORKSHOP ON THEORY AND PRACTICE IN INFORMATION-THEORETIC SECURITY, 2005, : 49 - 54
  • [47] Algebraic attacks on a class of stream ciphers with unknown output function
    Pillai, N. Rajesh
    Bedi, S. S.
    DESIGNS CODES AND CRYPTOGRAPHY, 2013, 69 (03) : 317 - 330
  • [48] Using Spritz as a Password-Based Key Derivation Function
    Alvarez, Rafael
    Zamora, Antonio
    INTERNATIONAL JOINT CONFERENCE SOCO'16- CISIS'16-ICEUTE'16, 2017, 527 : 518 - 525
  • [49] Algebraic cryptanalysis of stream ciphers using decomposition of Boolean function
    Roy, Dibyendu
    Datta, Pratish
    Mukhopadhyay, Sourav
    JOURNAL OF APPLIED MATHEMATICS AND COMPUTING, 2015, 49 (1-2) : 397 - 417
  • [50] Walks on Algebraic Small World Graphs of Large Girth and New Secure Stream Ciphers
    Ustimenko, Vasyl
    Chojecki, Tymoteusz
    INTELLIGENT SYSTEMS AND APPLICATIONS, VOL 3, INTELLISYS 2024, 2024, 1067 : 525 - 538