Security Monitoring and Management for the Network Services in the Orchestration of SDN-NFV Environment Using Machine Learning Techniques

Software Defined Network(SDN)and Network Function Virtualization(NFV)technology promote several benefits to network operators,including reduced maintenance costs,increased network operational performance,simplified network lifecycle,and policies management.Network vulnerabilities try to modify services provided by Network Function Virtualization MANagement and Orchestration(NFV MANO),and malicious attacks in different scenarios disrupt the NFV Orchestrator(NFVO)and Virtualized Infrastructure Manager(VIM)lifecycle management related to network services or individual Virtualized Network Function(VNF).This paper proposes an anomaly detection mechanism that monitors threats in NFV MANO and manages promptly and adaptively to implement and handle security functions in order to enhance the quality of experience for end users.An anomaly detector investigates these identified risks and provides secure network services.It enables virtual network security functions and identifies anomalies in Kubernetes(a cloud-based platform).For training and testing purpose of the proposed approach,an intrusion-containing dataset is used that hold multiple malicious activities like a Smurf,Neptune,Teardrop,Pod,Land,IPsweep,etc.,categorized as Probing(Prob),Denial of Service(DoS),User to Root(U2R),and Remote to User(R2L)attacks.An anomaly detector is anticipated with the capabilities of a Machine Learning(ML)technique,making use of supervised learning techniques like Logistic Regression(LR),Support Vector Machine(SVM),Random Forest(RF),Naïve Bayes(NB),and Extreme Gradient Boosting(XGBoost).The proposed framework has been evaluated by deploying the identified ML algorithm on a Jupyter notebook in Kubeflow to simulate Kubernetes for validation purposes.RF classifier has shown better outcomes(99.90%accuracy)than other classifiers in detecting anomalies/intrusions in the containerized environment.

A Survey on Event Mining for ICT Network Infrastructure Management

1 IntroductionNowadays in China, there are more than six hundred million netizens [1]. On April 11, 2015, the nmnbet of simultaneous online users of the Chinese instant message application QQ reached two hundred million [2]. The fast growth ol the lnternet pusnes me rapid development of information technology （IT） and communication technology （CT）. Many traditional IT service and CT equipment providers are facing the fusion of IT and CT in the age of digital transformation, and heading toward ICT enterprises. Large global ICT enterprises, such as Apple, Google, Microsoft, Amazon, Verizon, and AT＆T, have been contributing to the performance improvement of IT service and CT equipment.

A Cache Considering Role-Based Access Control and Trust in Privilege Management Infrastructure

PMI （privilege management infrastructure） is used to perform access control to resource in an E-commerce or E-government system. With the ever-increasing need for secure transaction, the need for systems that offer a wide variety of QoS （quality-of-service） features is also growing. In order to improve the QoS of PMI system, a cache based on RBAC （Role-based Access control） and trust is proposed. Our system is realized based on Web service. How to design the cache based on RBAC and trust in the access control model is deseribed in detail. The algorithm to query role permission in cache and to add records in cache is dealt with. The policy to update cache is introduced also.

The Role of Knowledge Management Infrastructure in Enhancing Job Satisfaction at Aqaba Five Star Hotels in Jordan

The aim of this research is to explore the role of Knowledge Management (KM) infrastructure (organizational culture, organizational structure and information technology) in enhancing job satisfaction at Aqaba five star hotels located in Jordan. A total of 216 questionnaires containing 33 items were used to collect information from the respondents. Multiple regression analysis was conducted to test the research hypotheses. Results of the current study revealed that there is a significant positive impact of KM infrastructure on job satisfaction and these results are in line with the results of the previous studies mentioned in the literature, and also revealed that the dimensions of KM infrastructure that has the highest effect on job satisfaction are organizational culture followed by information technology;whereas the variable of organizational structure has not significant impact on it. Results of T-test showed that there is no significant difference in the impact of KM infrastructure towards job satisfaction in favor of gender. In addition, results of ANOVA test found that there are significant differences in the impact of KM infrastructure on job satisfaction that can be attributed to age, educational level, and personal income.

Sustainable water management for green infrastructure

The water is the most important component in the ecosystems responsible for energy flow and mass transport. The water also plays an important role for human existence. However, the constructed infrastructures such as roads, buildings, railways, drainage systems, etc. give negative impacts to the ecosystem such as deteriorating the water quality and changing the natural water circulation system.

Considering deterioration propagation in transportation infrastructure maintenance planning

Civil infrastructure system maintenance planning is to determine which facility should be repaired,when and how maintenance should be carried out,and what treatment should be used under budget and other resource constraints.In the existing literature,various simulation and optimization models have been developed to help select the optimal maintenance plan.However,the developed models overlooked the deterioration propagation between adjacent connected facilities of the network infrastructure system.For instance,a facility receiving zero maintenance or having a failure of maintenance treatment affects not only the condition of itself,but also the deterioration rate of its neighboring facilities.This raises the call for taking the deterioration propagation into consideration when developing optimization models and capture to which extent it can affect the optimal maintenance plan.Therefore,in this paper,an infrastructure maintenance planning model considering the deterioration propagation between facilities is formulated as a mixed integer linear programming problem.A heuristic algorithm was proposed to solve the problem efficiently.Example networks were tested for the performance comparison between CPLEX and the heuristic algorithm.The proposed model performs better than models without the deterioration propagation.