In this paper, Advanced Encryption Standard was modified to address the low diffusion rate at the early rounds by adding additional primitive operations such as exclusive OR and modulo arithmetic in the cipher round. Furthermore, byte substitution and round constant addition were appended to the key schedule algorithm. The modified AES was tested against the standard AES by means of avalanche effect and frequency test to measure the diffusion and confusion characteristics respectively. The results of the avalanche effect evaluation show that there was an average increase in diffusion of 61.98% in round 1, 14.79% in round 2 and 13.87% in round 3. Consequently, the results of the frequency test demonstrated an improvement in the randomness of the ciphertext since the average difference between the number of ones to zeros is reduced from 11.6 to 6.4 along with better-computed p-values. The results clearly show that the modified AES has improved diffusion and confusion properties and the ciphertext can still be successfully decrypted and recover back the original plaintext.

The continuing advancement of technology had provided security issues in protecting the confidentiality of information. The need to protect unauthorized access of a third party is warranted.  In this paper, the reduced-round modified AES with revised round keys and key schedule is proposed to ensure file confidentiality.  The modifications to the AES cipher round was the reduction of the round iterations from 10 to 6, and additional key permutations were added in between states; while in the key schedule, additional byte substitution process was appended.  Time and throughput were utilized to measure the performance of the application's encryption/decryption process; while the avalanche effect and randomness tests were used to measure the security of the modified AES algorithm.  The results of evaluations have shown that the encryption and decryption time have improved by 1.27% and 1.21% respectively while the throughput has similarly improved by 1.29% and 3.19% for both encryption and decryption respectively.  Whereas the avalanche effect of the modified AES was 50.06% which was more than the ideal value of 50% and it was also better than the standard AES which was 49.94% using the sample dataset.  Finally, all the ciphertext outputs of the modified AES passed the randomness tests.

In this paper, Advanced Encryption Standard was modified to address the low diffusion rate at the early rounds by adding additional primitive operations such as exclusive OR and modulo arithmetic in the cipher round. Furthermore, byte substitution and round constant addition were appended to the key schedule algorithm. The modified AES was tested against the standard AES by means of avalanche effect and frequency test to measure the diffusion and confusion characteristics respectively. The results of the avalanche effect evaluation show that there was an average increase in diffusion of 61.98% in round 1, 14.79% in round 2 and 13.87% in round 3. Consequently, the results of the frequency test demonstrated an improvement in the randomness of the ciphertext since the average difference between the number of ones to zeros is reduced from 11.6 to 6.4 along with better-computed p-values. The results clearly show that the modified AES has improved diffusion and confusion properties and the ciphertext can still be successfully decrypted and recover back the original plaintext.

Improved multi-cluster overlapping k-means extension (IMCOKE) uses median absolute deviation (MAD) in detecting outliers in datasets makes the algorithm more effective with regards to overlapping clustering. Nevertheless, analysis of the applied MAD positioning was not considered. In this paper, the incorporation of MAD used to detect outliers in the datasets was analyzed to determine the appropriate position in identifying the outlier before applying it in the clustering application. And the assumption of the study was the size of the cluster and cluster that are close to each other can led to a higher runtime performance in terms of overlapping clusters. Therefore, additional parameters such as radius of clusters and distance between clusters are added measurements in the algorithm procedures. Evaluation was done through experimentations using synthetic and real datasets. The performance of the eHMCOKE was evaluated via F1-measure criterion, speed and percentage of improvement. Evaluation results revealed that the eHMCOKE takes less time to discover overlap clusters with an improvement rate of 22% and achieved the best performance of 91.5% accuracy rate via F1-measure in identifying overlapping clusters over the IMCOKE algorithm. These results proved that the eHMCOKE significantly outruns the IMCOKE algorithm on mosts of the test conducted.

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