Challenges and Security Vulnerabilities to Impact on Database Systems

Abstract A lot of institutions depends at present on the systems database operations and their daily activities, thus providing a means for the maintenance of permanent data can refer to it at any time, as well as to search and to modify the data easily. in this paper to determine the security challenges in the databases, and requirements necessary to address those challenges in the data value to provide security base, and to determine the security rules and know the weaknesses that can be exploited any information in a manner not allowed, when he must protect the database to make sure of the following purposes: confidentiality, integrity and continuity. One of the solutions used in this research to protect databases, and encryption of sensitive data, and adjust the system databases, and updates the database systems and we review some of the ways to address these challenges in the security databases

Optimized Generation and Maintenance of Materialized View using Adaptive Mechanism

Data Warehouse is storage of enormous amount of data gathered from multiple data sources, which is mainly used by managers for analysis purpose. Hence to make this data available in less amount of time is essential. Using Materialize view we can have result of query in less amount of time compared to access the same from base tables. To materialize all of the views is not possible since it requires storage space and maintenance cost. So it is required to select materialized view which minimizes response time of query and cost of maintenance. In this paper, effective approach is suggested for selection and maintenance of materialize view. DOI: 10.17762/ijritcc2321-8169.15050

Clustering-Based Materialized View Selection in Data Warehouses

Materialized view selection is a non-trivial task. Hence, its complexity must be reduced. A judicious choice of views must be cost-driven and influenced by the workload experienced by the system. In this paper, we propose a framework for materialized view selection that exploits a data mining technique (clustering), in order to determine clusters of similar queries. We also propose a view merging algorithm that builds a set of candidate views, as well as a greedy process for selecting a set of views to materialize. This selection is based on cost models that evaluate the cost of accessing data using views and the cost of storing these views. To validate our strategy, we executed a workload of decision-support queries on a test data warehouse, with and without using our strategy. Our experimental results demonstrate its efficiency, even when storage space is limited

Processing Over Encrypted Query Data In Internet of Things (IoTs) : CryptDBs, MONOMI and SDB

Internet of Things (IoT) is the developing technologies that would be the biggest agents to modify the current world. Machine-to-machine communications perform with virtual, mobile and instantaneous connections. In IoT system, it consists of data-gathering sensors various other household devices. Intended for protecting IoT system, the end-to-end secure communication is a necessary measure to protect against unauthorized entities (e.g., modification attacks and eavesdropping,) and the data unprotected on the Cloud. The most important concern hereby is how to preserve the insightful information and to provide the privacy of user data. In IoT, the encrypted data computing is based on techniques appear to be promising approaches. In this paper, we discuss about the recent secure database systems, which are capable to execute SQL queries over encrypted data

Holistic Indexing: Offline, Online and Adaptive Indexing in the Same Kernel

Proper physical design is a momentous issue for the performance of modern database systems and applications. Nowadays, a growing amount of applications require the execution of dynamic and exploratory workloads with unpredictable characteristics that change over time, e.g., social networks, scientific databases and multime