Journal of Al-Qadisiyah for Computer Science and Mathematics

The aim of this work to define the fuzzy base and fuzzy local base in fuzzy bitopological space and so to compare them with fuzzy base and fuzzy local base in fuzzy topological space.

With the increasing needs in security systems, palm vein authentication is one of the important and reliable solutions for identity security for biometrics based authentication systems. Palm vein, as a biological characteristic of an individual, has been increasingly utilized for personal authentication in advanced security applications. Palm vein patterns are a unique attribute of everyone and can therefore be used as a biometric characteristic. The human palm vein pattern is extremely complex and it shows a huge number of vessels. The biometric information is located inside the human body, and therefore it is protected against forgery and manipulation. In the proposed method, the Multilevel Gaussian-Second-Derivative (MGSD) is proposed for enhancement the palm vein images. Secondly, a new feature extraction method based on Steerable filter and Locality Sensitive Discriminant Analysis is proposed called Steerable - Locality Sensitive Discriminant Analysis (SLSDA). Finally, the Correlation Distance method is proposed for verify the tested palm vein. The EER to the proposed authentication system is 0.1087%.

In this paper a new approach has been designed for Intrusion Detection System (IDS). The detection will be for misuse and anomalies for training and testing data detecting the normal users or attacks users.
The method used in this research is a hybrid method from supervised learning and text recognition field for (IDS). Random Forest algorithm used as a supervised learning method to choose the features and k-Nearest Neighbours is a text recognition algorithm used to detect and classify of the legitimate and illegitimate attack types.
The experimental results have shown that the most accurate results is that obtained by using the proposed method and proved that the proposed method can classify the unknown attacks. The results obtained by using benchmark dataset which are: KDD Cup 1999 dataset.

Personal Health Records (PHRs) is service for health information interchange. Patients can create, control, and exchange their health information. PHRs are outsourced to be stored in the cloud. However, there have been serious privacy concerns about cloud service as it may expose user’s data like PHRs to those cloud service providers or unauthorized users. To overcome these challenges, a cloud based PHRs for exchange PHRs among multiple users is proposed. In the proposed system, patients can encrypt their PHRs and store them on the cloud. Furthermore, patients can maintain control over access to their PHRs by assigning fine grained access control. To achieve fine grained access, the proposed PHRs are divided into the personal domain (PSDs) and public domain (PUDs). To ensure security in a cloud based PHRs, Multi-authority based weighted attribute encryption model and Attributed-based access control for the Multi authority model are implemented in the PSDs and PUDs, respectively. The proposed model based on PHRs improves the efficiency of the system in terms of encryption, decryption. Also, the proposed system has proven to be collusion resistant and enhancing the security of PHRs users in a multi owner environment.

The digital audio became very popular and important in a computer user experience. The increasing amounts of audio data requires improvement, new methods and algorithms for processing this information. In this paper, our approach proposed the GA-KNN approach (Genetic Algorithm with K-Nearest Neighbor as fitness function) for content-based audio retrieval. The input is an audio file (query) and the output is a list of audio files ranked by their similarity. The system first extracts the features from an audio database and audio query. The query pattern is considered as a boundary for comparison. Then, the initial population in a genetic algorithm is constructed from a database containing all audio features. To improve the results, this paper uses Cosine measure in the genetic algorithm, and an improved selection method selection method to prevent the fittest chromosomes from being wasted in the new population by adding an Elitism feature, using 4% Elitism count. Furthermore, we proposed a new crossover method (Close Up-Feature Crossover) to create a new offspring by comparison between two audio patterns to query pattern. Finally, we evaluated our approach using a well-known audio database, which contains 409 sound samples of 16 classes to give 0.71475 as a precision of the audio retrieval.