International Journal of Scientific & Technology Research 

Abstract: Mobile devices have become popular in our lives since they offer almost the same functionality as personal computers. Among them, Android-based mobile devices had appeared lately and, they were now an ideal target for attackers. Android-based smartphone users can get free applications from Android Application Market. But, these applications were not certified by legitimate organizations and they may contain malware applications that can steal privacy information for users. In this paper, a framework that can detect android malware applications is propos ed to help organizing Android Market. The proposed framework intends to develop a machine learning-based malware detection system on Android to detect malware applications and to enhance security and privacy of smartphone users. This system monitors various permissionbased features and events obtained from the android applications, and analyses these features by using machine learning classifiers to classify whether the application is goodware or malware.

Abstract: Authentic materials are among the most important tools a teacher can and must use in class in order to make his/her teaching go smoothly and be effective in transmitting the necessary knowledge to all students. In this paper, the writers will discuss the Effect of Using Authentic Materials in teaching, because a number of studies point out that the use of authentic materials is regarded a useful means to motivate learners, arouse their interest and expose them to the real language they will face in the real world.

Abstract: In this paper, we have focused to compare a variety of techniques, approaches and different tools and its impact on the healthcare sector. The goal of data mining application is to turn that data are facts, numbers, or text which can be processed by a computer into knowledge or information. The main purpose of data mining application in healthcare systems is to develop an automated tool for identifying and disseminating relevant healthcare information. This paper aims to make a detailed study report of different types of data mining applications in the healthcare sector and to reduce the complexity of the study of the healthcare data transactions. Also presents a comparative study of different data mining applications, techniques and different methodologies applied for extracting knowledge from database generated in the healthcare industry. Finally, the existing data mining techniques with data mining algorithms and its application tools which are more valuable for healthcare services are discussed in detail.

Abstract: Providing security in a distributed system requires more than user authentication with passwords or digital certificates and confidentiality in data transmission. Distributed model of cloud makes it vulnerable and prone to sophisticated distributed intrusion attacks like Distributed Denial of Service (DDOS) and Cross Site Scripting (XSS). To handle large scale network access traffic and administrative control of data and application in cloud, a new multi-threaded distributed cloud IDS model has been proposed. Our proposed cloud IDS handles large flow of data packets, analyze them and generate reports efficiently by integrating knowledge and behavior analysis to detect intrusions. ————————————————————