New Anomaly Network Intrusion Detection System in Cloud Environment Based on Optimized Back Propagation Neural Network Using Improved Genetic Algorithm

Cloud computing is distributed architecture, providing computing facilities and storage resource as a service over an open environment (Internet), this lead to different matters related to the security and privacy in cloud computing. Thus, defending network accessible Cloud resources and services from various threats and attacks is of great concern. To address this issue, it is essential to create an efficient and effective Network Intrusion System (NIDS) to detect both outsider and insider intruders with high detection precision in the cloud environment. NIDS has become popular as an important component of the network security infrastructure, which detects malicious activities by monitoring network traffic. In this work, we propose to optimize a very popular soft computing tool widely used for intrusion detection namely, Back Propagation Neural Network (BPNN) using an Improved Genetic Algorithm (IGA). Genetic Algorithm (GA) is improved through optimization strategies, namely Parallel Processing and Fitness Value Hashing, which reduce execution time, convergence time and save processing power. Since,  Learning rate and Momentum term are among the most relevant parameters that impact the performance of BPNN classifier, we have employed IGA to find the optimal or near-optimal values of these two parameters which ensure high detection rate, high accuracy and low false alarm rate. The CloudSim simulator 4.0 and DARPA’s KDD cup datasets 1999 are used for simulation. From the detailed performance analysis, it is clear that the proposed system called “ANIDS BPNN-IGA” (Anomaly NIDS based on BPNN and IGA) outperforms several state-of-art methods and it is more suitable for network anomaly detection

Memory system for a relational database processor

An associative memory for a relational database management system, with content addressing capability, is studied and analyzed. The system utilizes one level of indexing and the database is clustered. The logic-per-track approach is used for parallel processing of the data in a cylinder. The attributes and the tuples are allowed to have an arbitrary length and no encoding algorithm is used. The performance of the system is analyzed and it is demonstrated to have superior performance in comparison to software-based systems. The cost effectiveness of the system is also shown

Insuring Smiles: Predicting routine dental coverage using Spark ML

Finding suitable health insurance coverage can be challenging for individuals and small enterprises in the USA. The Health Insurance Exchange Public Use Files (Exchange PUFs) dataset provided by CMS offers valuable information on health and dental policies [1]. In this paper, we leverage machine learning algorithms to predict if a health insurance plan covers routine dental services for adults. By analyzing plan type, region, deductibles, out-of-pocket maximums, and copayments, we employ Logistic Regression, Decision Tree, Random Forest, Gradient Boost, Factorization Model and Support Vector Machine algorithms. Our goal is to provide a clinical strategy for individuals and families to select the most suitable insurance plan based on income and expenses.Comment: 4 pages, 13 figures, 5 table

Guest Editors' Introduction: Special Section on Computer Arithmetic

International audienceCOMPUTER arithmetic is the mother of all computer research and application topics, like mathematics (as the title of a famous book by E.T. Bell) is the queen and servant of sciences and arithmetic the queen of mathematics. The etymology itself of the word computer is intrinsically related to the concept of arithmetic and mathematics. Interesting to note is that the origin of the word computer comes from the Latin word computare, which is defined as count, evaluate, calculate the result. In all cases, the connection between computers and computer arithmetic goes beyond simple etymology reasons. Computers are designed either to perform a specific calculation or to have extensive programmability for many changing tasks. In either case, at a certain level this translates into doing computations and arithmetic evaluations

A Parallel Computational Approach for String Matching- A Novel Structure with Omega Model

In r e cent day2019;s parallel string matching problem catch the attention of so many researchers because of the importance in different applications like IRS, Genome sequence, data cleaning etc.,. While it is very easily stated and many of the simple algorithms perform very well in practice, numerous works have been published on the subject and research is still very active. In this paper we propose a omega parallel computing model for parallel string matching. The algorithm is designed to work on omega model pa rallel architecture where text is divided for parallel processing and special searching at division point is required for consistent and complete searching. This algorithm reduces the number of comparisons and parallelization improves the time efficiency. Experimental results show that, on a multi - processor system, the omega model implementation of the proposed parallel string matching algorithm can reduce string matching time

The role of computer algebra systems in mathematics teaching at upper secondary school

Computer algebra systems are programs that manipulate both symbols and numbers and so can reduce the tedium of algebra in the same way calculators can reduce the time and work involved in arithmetic. Some systems combine a wide ranqe of mathematical functions with graphing capabilities. As such they have the potential to reduce the time students spend calculating algorithms, allowing more time for concept development, which is enhanced by the ability of the program to concurrently represent mathematical functions graphically. Originally computer algebra systems were only developed for mainframe computers, but in recent years several systems have become available for microcomputers. These systems are being introduced to mathematics teaching at tertiary level. This study considered some aspects of their introduction at upper secondary level in Western Australia. Two systems were identified as suitable for use in schools and one of these, Derive, was considered in some detail. It was found that the utilities available within the program were applicable to most areas of the new upper school mathematics curricula due for introduction in 1991. A small group of mathematics teachers was administered a demonstration and given hands-on exercises with Derive, then their views sought via a questionnaire on the introduction of such programs. Their response was generally positive. They believed the programs had the potential to improve mathematics for both students and teachers, if applied sensibly. The introduction of the program would have to be supported by extra computing resources and training for some teachers. The way the programs were applied would be critical; they must stimulate students\u27 mathematical thinking, not merely do the work for them