Graphical web based tool for generating query from star schema

This paper presents the development of a graphical SQL query tool that allows novice and non-technical users to navigate through database tables and generate their own queries.The tool enables the query output to be presented in graphical and tabular forms, which can help users, especially top management in better understanding and interpreting query results.The algorithms to construct complex SQL query from star schema in databases is also presented

A Statistical Approach Towards Worm Detection Using Cross-Relation Technique

Computer networks have become an important dimension of modern organizations. Thus, ensuring that networks run at peak performance (network utilization and speed running normal without any faults) is considered a crucial step for these organizations. To achieve this goal, networks must be secure because security is one of the essential issues for reaching a good performance level (no faults in the network such as high rate of connection failure). However, this task is next to impossible especially when there are other issues that need to be addressed. This thesis focuses on detecting the presence of network worms in network, which is one of the most challenging problems in network security. By detecting the presence of network worms in the network, resources and services can be further protected by patching or installing security measures, such as firewalls, intrusion detection systems, or alternative computer systems

A Preliminary Performance Evaluation of K-means, KNN and EM Unsupervised Machine Learning Methods for Network Flow Classification

Unsupervised leaning is a popular method for classify unlabeled dataset i.e. without prior knowledge about data class. Many of unsupervised learning are used to inspect and classify network flow. This paper presents in-deep study for three unsupervised classifiers, namely: K-means, K-nearest neighbor and Expectation maximization. The methodologies and how it’s employed to classify network flow are elaborated in details. The three classifiers are evaluated using three significant metrics, which are classification accuracy, classification speed and memory consuming. The K-nearest neighbor introduce better results for accuracy and memory; while K-means announce lowest processing time

Earlier stage for straggler detection and handling using combined CPU test and LATE methodology

Using MapReduce in Hadoop helps in lowering the execution time and power consumption for large scale data. However, there can be a delay in job processing in circumstances where tasks are assigned to bad or congested machines called "straggler tasks"; which increases the time, power consumptions and therefore increasing the costs and leading to a poor performance of computing systems. This research proposes a hybrid MapReduce framework referred to as the combinatory late-machine (CLM) framework. Implementation of this framework will facilitate early and timely detection and identification of stragglers thereby facilitating prompt appropriate and effective actions

Review of Prevention Schemes for Man-In-The-Middle (MITM) Attack in Vehicular Ad hoc Networks

Vehicular Ad-Hoc Network (VANET) is an indispensable part of the Intelligent Transportation System (ITS) due to its abilities to enhance traffic management and safety. Many researchers have been focused on specific areas involving management and storage data, protocols standardization, network fragmentation, monitoring, and quality of service.  The benchmarks of security of VANET are studied and figured out in this paper. VANET provides the driver and passenger with the safety application as well as entertainment service. However, the communication between nodes in VANET is susceptible to security threats in both communication modes, which indicates the main hazard. In this paper, we identified different Man-In-The-Middle (MITM) attacks with various behaviors such as message tampering, message delaying, and message dropping, according to the literature. In this study, the essential background of VANET from architectural point of view and communication types are discussed. Then, the overview of MITM attack in VANET is presented. In addition, this paper thoroughly reviews the existing prevention schemes for MITM attack in VANET. This review paper reveals that there is still a need for a better and more efficient preventive scheme to address the MITM attack in VANET. This review paper could serve as evidence and reference in the development of any new security schemes for VANETs

Review of Prevention Schemes for Modification Attack in Vehicular Ad hoc Networks

Vehicular Ad-hoc Network (VANET) technology is the basis of Intelligent Transportation System (ITS) connectivity that enables the delivery of useful information to and fro between vehicles in vehicle-to-vehicle communication mode; or between vehicle and infrastructure in vehicle-to-infrastructure mode for safety and comfort. However, due to the openness of the wireless medium used by VANET, the technology is vulnerable to security threats in both communication modes. In this study, the essential background of VANET from architectural point of view and communication types are discussed. Then, the overview of modification attack in VANET is presented. In addition, this paper thoroughly reviews the existing prevention schemes for modification attack in VANET. This review paper reveals that there is still a need for a better and more efficient preventive scheme to address the modification attack in VANET

Straggler handling approaches in mapreduce framework: a comparative study

The proliferation of information technology produces a huge amount of data called big data that cannot be processed by traditional database systems. These Various types of data come from different sources. However, stragglers are a major bottleneck in big data processing, and hence the early detection and accurate identification of stragglers can have important impacts on the performance of big data processing. This work aims to assess five stragglers identification methods: Hadoop native scheduler, LATE Scheduler, Mantri, MonTool, and Dolly. The performance of these techniques was evaluated based on three benchmarked methods: Sort, Grep and WordCount. The results show that the LATE Scheduler performs the best and it would be efficient to obtain better results for stragglers identification

Detection and Defense Mechanisms on Duplicate Address Detection Process in IPv6 Link-Local Network: A Survey on Limitations and Requirements

The deployment of Internet Protocol Version 6 (IPv6) has progressed at a rapid pace. IPv6 has introduced new features and capabilities that is not available in IPv4. However, new security risks and challenges emerge with any new technology. Similarly, Duplicate Address Detection (DAD), part of Neighbor Discovery Protocol in IPv6 protocol, is subject to security threats such as denial-of-service attacks. This paper presents a comprehensive review on detection and defense mechanisms for DAD on fixed network. The strengths and weaknesses of each mechanism to Secure-DAD process are discussed from the perspective of implementation and processing time. Finally, challenges and future directions are presented along with feature requirements for the new security mechanism to secure DAD procedure in an IPv6 link-local network

A Machine Learning Approach to Detect Router Advertisement Flooding Attacks in Next-Generation IPv6 Networks

Router advertisement (RA) flooding attack aims to exhaust all node resources, such as CPU and memory, attached to routers on the same link. A biologically inspired machine learning-based approach is proposed in this study to detect RA flooding attacks. The proposed technique exploits information gain ratio (IGR) and principal component analysis (PCA) for feature selection and a support vector machine (SVM)-based predictor model, which can also detect input traffic anomaly. A real benchmark dataset obtained from National Advanced IPv6 Center of Excellence laboratory is used to evaluate the proposed technique. The evaluation process is conducted with two experiments. The first experiment investigates the effect of IGR and PCA feature selection methods to identify the most contributed features for the SVM training model. The second experiment evaluates the capability of SVM to detect RA flooding attacks. The results show that the proposed technique demonstrates excellent detection accuracy and is thus an effective choice for detecting RA flooding attacks. The main contribution of this study is identification of a set of new features that are related to RA flooding attack by utilizing IGR and PCA algorithms. The proposed technique in this paper can effectively detect the presence of RA flooding attack in IPv6 network

Is carotid artery atherosclerosis associated with poor cognitive function assessed using the Mini-Mental State Examination? A systematic review and meta-analysis

OBJECTIVES: To determine associations between carotid atherosclerosis assessed by ultrasound and the Mini-Mental State Examination (MMSE), a measure of global cognitive function. DESIGN: Systematic review and meta-analysis. METHODS: MEDLINE and EMBASE databases were searched up to 1 May 2020 to identify studies assessed the associations between asymptomatic carotid atherosclerosis and the MMSE. Studies reporting OR for associations between carotid plaque or intima-media thickness (cIMT) and dichotomised MMSE were meta-analysed. Publication bias of included studies was assessed. RESULTS: A total of 31 of 378 reviewed articles met the inclusion criteria; together they included 27 738 participants (age 35-95 years). Fifteen studies reported some evidence of a positive association between measures of atherosclerosis and poorer cognitive performance in either cross-sectional or longitudinal studies. The remaining 16 studies found no evidence of an association. Seven cross-sectional studies provided data suitable for meta-analysis. Meta-analysis of three studies that assessed carotid plaque (n=3549) showed an association between the presence of plaque and impaired MMSE with pooled estimate for the OR (95% CI) being 2.72 (0.85 to 4.59). An association between cIMT and impaired MMSE was reported in six studies (n=4443) with a pooled estimate for the OR (95% CI) being 1.13 (1.04 to 1.22). Heterogeneity across studies was moderate to small (carotid plaque with MMSE, I2=40.9%; cIMT with MMSE, I2=4.9%). There was evidence of publication bias for carotid plaque studies (p=0.02), but not cIMT studies (p=0.2). CONCLUSIONS: There is some, limited cross-sectional evidence indicating an association between cIMT and poorer global cognitive function assessed with MMSE. Estimates of the association between plaques and poor cognition are too imprecise to draw firm conclusions and evidence from studies of longitudinal associations between carotid atherosclerosis and MMSE is limited. PROSPERO REGISTRATION NUMBER: CRD42021240077