An Assessment of Practical Hands-On Lab Activities in Network Security Management

With the advancement in technology over the past decades, networks have become increasingly large and complex. In the meantime, cyberattacks have become highly sophisticated making them difficult to detect. These changes make securing a network more challenging than ever before. Hence, it is critical to prepare a comprehensive guide of network security management for students assist them in becoming network security professionals. The objective of this paper is to introduce a variety of techniques related to network security management, such as Simple Network Management Protocol (SNMP), event management, security policy management, risk management, access control, and remote monitoring. With the usage of these techniques, malicious activities from outsiders and misuse by insiders can be effectively monitored and managed. A network learning environment is proposed for students to practice network security management experiments. In addition, hands-on lab exercises are suggested. These activities will help students become familiar with the operations of network security management and allow them to further apply practical skills to protect networks

Fuzzy special logic functions and applications

In this thesis, four special logic functions (threshold functions, monotone increasing functions, monotone decreasing functions, and unate functions) are extended to more general functions which allows the activities of these special functions to be a fuzzy rather than a 1-or-O process. These special logic functions are called as fuzzy special logic functions and are based on the concepts and techniques developed in fuzzy logic and fuzzy languages. The algorithms of determining C(n), Cmax(n) and generating the most dissimilar fuzzy special logic functions as well as important properties and results are investigated. Examples are given to illustrated these special logic functions. In addition, their applications -- function representation, data compression, error correction, and monotone flash analog to digital converter, their relationships, and fuzzy classification are also presented. It is obviously shown that fuzzy logic theory can be used successfully on these four special logic functions in order to normalize the grade of membership function μ in the interval [0 1]. As a result, the techniques described in this thesis may be of use in the study of other special logic functions and much fertile field work is great worth researching and developing

The Impact of Hands-On Simulation Laboratories on Teaching of Wireless Communications

Aim/Purpose: To prepare students with both theoretical knowledge and practical skills in the field of wireless communications. Background: Teaching wireless communications and networking is not an easy task because it involves broad subjects and abstract content. Methodology: A pedagogical method that combined lectures, labs, assignments, exams, and readings was applied in a course of wireless communications. Contribution: Five wireless networking labs, related to wireless local networks, wireless security, and wireless sensor networks, were developed for students to complete all of the required hands-on lab activities. Findings: Both development and implementation of the labs achieved a successful outcome and provided students with a very effective learning experience. Students expressed that they had a better understanding of different wireless network technologies after finishing the labs. Recommendations for Practitioners: Detailed instructional lab manuals should be developed so that students can carry out hands-on activities in a step-by-step fashion. Recommendation for Researchers: Hands-on lab exercises can not only help students understand the abstract technical terms in a meaningful way, but also provide them with hands-on learning experience in terms of wireless network configuration, implementation, and evaluation. Impact on Society: With the help of a wireless network simulator, students have successfully enhanced their practical skills and it would benefit them should they decide to pursue a career in wireless network design or implementation. Future Research: Continuous revision of the labs will be made according to the feedback from students. Based on the experience, more wireless networking labs and network issues could be studied in the future

Scripting an Automated Score and Message Board; Cyber Security Competitive Labs as a Service (CLaaS),

There is a growing skills gap in the cybersecurity industry, to compound the skills gap, there is also a growing manpower gap. Every year the need for skilled cybersecurity professionals grows and every year the skills deemed important change. This has created a dire situation for academic and organizational training. The situation has sparked a wealth of research and development in Serious Cyber Security games-based learning systems. However, significant research of design in game-based learning systems is independent of actual curriculum or does not set a standard for which systems and designs should follow. The Cybersecurity CLaaS learning system provides participants with a competitive environment to apply hands on knowledge and skills gained in related courses. Participants defend their system while also attacking others, creating a fun and competitive experience. Developed using primary open source technology’s, such as Linux and VirtualBox, the CLaaS platform is deployable with minimal configuration and little to no cost. Utilizing embedded virtualization, and current cloud technology, the platforms lab pods can be made accessible over the internet or restricted to participants on a secure local network. Materials and instruction are presented on a graphical user interface (GUI) via a web browser. The GUI also contains a Score and Message Board, that updates participants’ scores in to real time. The CLaaS learning system is designed to allow for customization of both the GUI and the environment itself. Changing, adding or removing learning objectives are as easy as spinning up new Virtual Machines.ECU Research and Creative Achievement Wee

Urinary levels of organophosphate flame retardants metabolites in a young population from Southern Taiwan and potential health effects

BackgroundOrganophosphate flame retardants (OPFRs) are widely distributed in the environment and their metabolites are observed in urine, but little is known regarding OPFRs in a broad-spectrum young population from newborns to those aged 18 years.ObjectivesInvestigate urinary levels of OPFRs and OPFR metabolites in Taiwanese infants, young children, schoolchildren, and adolescents within the general population.MethodsDifferent age groups of subjects (n=136) were recruited from southern Taiwan to detect 10 OPFR metabolites in urine samples. Associations between urinary OPFRs and their corresponding metabolites and potential health status were also examined.ResultsThe mean level of urinary Σ10 OPFR in this broad-spectrum young population is 2.25 μg/L (standard deviation (SD) of 1.91 μg/L). Σ10 OPFR metabolites in urine are 3.25 ± 2.84, 3.06 ± 2.21, 1.75 ± 1.10, and 2.32 ± 2.29 μg/L in the age groups comprising of newborns, 1-5 year-olds, 6-10 year-olds, and 11-18 year-olds, respectively, and borderline significant differences were found in the different age groups (p=0.125). The OPFR metabolites of TCEP, BCEP, DPHP, TBEP, DBEP, and BDCPP predominate in urine and comprise more than 90% of the total. TBEP was highly correlated with DBEP in this population (r=0.845, p<0.001). The estimated daily intake (EDI) of Σ5OPFRs (TDCPP, TCEP, TBEP, TNBP, and TPHP) was 2,230, 461, 130, and 184 ng/kg bw/day for newborns, 1-5 yr children, 6-10 yr children, and 11-17 yr adolescents, respectively. The EDI of Σ5OPFRs for newborns was 4.83-17.2 times higher than the other age groups. Urinary OPFR metabolites are significantly correlated with birth length and chest circumference in newborns.ConclusionTo our knowledge, this is the first investigation of urinary OPFR metabolite levels in a broad-spectrum young population. There tended to be higher exposure rates in both newborns and pre-schoolers, though little is known about their exposure levels or factors leading to exposure in the young population. Further studies should clarify the exposure levels and factor relationships

Ensemble fuzzy belief intrusion detection design

With the rapid growth of the Internet, computer attacks are increasing at a fast pace and can easily cause millions of dollar in damage to an organization. Detecting these attacks is an important issue of computer security. There are many types of attacks and they fall into four main categories, Denial of Service (DoS) attacks, Probe, User to Root (U2R) attacks, and Remote to Local (R2L) attacks. Within these categories, DoS and Probe attacks continuously show up with greater frequency in a short period of time when they attack systems. They are different from the normal traffic data and can be easily separated from normal activities. On the contrary, U2R and R2L attacks are embedded in the data portions of the packets and normally involve only a single connection. It becomes difficult to achieve satisfactory detection accuracy for detecting these two attacks. Therefore, we focus on studying the ambiguity problem between normal activities and U2R/R2L attacks. The goal is to build a detection system that can accurately and quickly detect these two attacks. In this dissertation, we design a two-phase intrusion detection approach. In the first phase, a correlation-based feature selection algorithm is proposed to advance the speed of detection. Features with poor prediction ability for the signatures of attacks and features inter-correlated with one or more other features are considered redundant. Such features are removed and only indispensable information about the original feature space remains. In the second phase, we develop an ensemble intrusion detection system to achieve accurate detection performance. The proposed method includes multiple feature selecting intrusion detectors and a data mining intrusion detector. The former ones consist of a set of detectors, and each of them uses a fuzzy clustering technique and belief theory to solve the ambiguity problem. The latter one applies data mining technique to automatically extract computer users’ normal behavior from training network traffic data. The final decision is a combination of the outputs of feature selecting and data mining detectors. The experimental results indicate that our ensemble approach not only significantly reduces the detection time but also effectively detect U2R and R2L attacks that contain degrees of ambiguous information

Scripting an Automated Score and Message Board; Cyber Security Competitive Labs as a Service (CLaaS) ,

There is a growing skills gap in the cybersecurity industry , to compound the skills gap , there is also a growing manpower gap. Every year the need for skilled cybersecurity professionals grows and every year the skills deemed important change. This has created a dire situation for academic and organizational training. The situation has sparked a wealth of research and development in Serious Cyber Security games-based learning systems. However , significant research of design in game-based learning systems is independent of actual curriculum or does not set a standard for which systems and designs should follow. The Cybersecurity CLaaS learning system provides participants with a competitive environment to apply hands on knowledge and skills gained in related courses. Participants defend their system while also attacking others , creating a fun and competitive experience. Developed using primary open source technology's , such as Linux and VirtualBox , the CLaaS platform is deployable with minimal configuration and little to no cost. Utilizing embedded virtualization , and current cloud technology , the platforms lab pods can be made accessible over the internet or restricted to participants on a secure local network. Materials and instruction are presented on a graphical user interface (GUI) via a web browser. The GUI also contains a Score and Message Board , that updates participants' scores in to real time. The CLaaS learning system is designed to allow for customization of both the GUI and the environment itself. Changing , adding or removing learning objectives are as easy as spinning up new Virtual Machines