Asian Science Citation Index is committed to provide an authoritative, trusted and significant information by the coverage of the most important and influential journals to meet the needs of the global scientific community.  
ASCI Database
308-Lasani Town,
Sargodha Road,
Faisalabad, Pakistan
Fax: +92-41-8815544
Contact Via Web
Suggest a Journal
 
Articles by Faudziah Ahmad
Total Records ( 3 ) for Faudziah Ahmad
  Ashwak Alabaichi , Ramlan Mahmod and Faudziah Ahmad
  The Blowfish Algorithm (BA) is a symmetric block cipher that iterates simple encryption and decryption functions by using Feistel networks. BA keys vary from 32-448 bits to ensure a high level of security. However, the BA requires a high memory percentage and it has a problem regarding randomness of output with text and image files having large strings of identical bytes. One solution to the seissues is to design a new Cryptography algorithm based on the BA that incorporates an F-function into a Cylindrical Coordinate System (CCS). The resulting F-function is known as a CCS with a Dynamic Permutation Table (DPT) or CCSDPT whereas the new algorithm is called the New BA (NBA). The objectives of the CCSDPT are to reduce memory requirements, enhance the randomness of the output and increase resistance to attacks through byte relocation and transformation in the right cylinder. NBA is evaluated by investigates the output of the algorithm by using statistical tests from the National Institute of Standard and Technology (NIST) with five types of data and compared with the BA. The findings of the NIST tests show that the NBA is suitable for any data stream, even those with long strings of identical bytes. The combination of a DPT with a dynamic 3D S-box strengthens the resistance of the NBA against attacks and increases the randomness of the output. C++ is used in the implementation of both algorithms. The NIST tests are implemented under Linux.
  Ashwak Mahmood Alabaichi , Ramlan Mahmood , Faudziah Ahmad and Mohammed S. Mechee
  Randomness of the output is one of the significant factors in measuring the security of any cryptographic algorithm. Non-random block cipher is vulnerable to any type of attack. This paper presents the National Institute of Standard and Technology (NIST) statistical tests of the Blowfish algorithm to investigate its randomness. Blowfish algorithm with Electronic Codebook (ECB) and Cipher Block Chaining (CBC) modes were conducted for these tests. In addition, comparisons between them were introduced. The analysis showed that Blowfish algorithm with ECB mode was inappropriate with data such as text and image files which have large strings of identical bytes. This inconsistency is due to the majority of the 188 statistical tests of NIST statistical tests failing in all rounds.
  Ruziana Mohamad Rasli , Mime Azrina Jaafar , Faudziah Ahmad and Siti Sakira Kamaruddin
  The purpose of this study is to explain on the process of data selection and collection for Quranic knowledge. The data used in this research is from the Holy Al-Quran and Hadiths. Basically, there are five sources used which is the Holy Al-Quran, Hadith Sahih Bukhari, Hadith Sahih Muslim, Hadith Sunan Abu Dawud and Hadith Sunan Ibn Majah. In order to minimize the resources, only Zakat topics is extracted. From all the data collection and selection processes, it is concluded that the total of 339 sentences are extracted from 72 Surah in the Holy Al-Quran and a total of 589 sentences are extracted from four Hadiths (Hadith Sahih Bukhari, Hadith Sahih Muslim, Hadith Sunan Abu Dawud and Hadith Sunan Ibn Majah). The total of sentences extracted from these two sources are 928 sentences. These two processes took 8 month to be completed. Most of the times are allocated in the process of proof reading the documents after OCR conversion. The output of this paper is 928 sentences from the Al-Quran and Hadiths that are focuses to Zakat topic. These ayats will be used for the next phase which is data processing and TF-IDF calculation.
 
 
 
Copyright   |   Desclaimer   |    Privacy Policy   |   Browsers   |   Accessibility