Server Administration Research Articles

RANCANG BANGUN MEDIA PEMBELAJARAN BERBASIS ANDROID (SMART APP CREATOR) PADA MATA PELAJARAN SISTEM ADMINISTRASI JARINGAN DI SMK ULIL ALBAB

Student learning outcomes are influenced by two factors, namely internal factors and external factors. Internal factors come from within students and external factors that come from outside students. Internal factors such as students' abilities, interests and motivation to learn, while external factors such as environmental conditions, schools and learning quality. The use of media in learning can help the limitations of educators in conveying information as well as the limitations of class hours. The media serves as a source of information on learning materials and as a source of practice questions. The quality of learning is also influenced by individual differences of students, both differences in learning styles, differences in cognitive abilities, differences in learning speed, and differences in background. This research and development aims to develop learning media for Android-based network server administration on basic network server administration materials, knowing the process of designing learning media developed, and making learning media developed using smart apps creators. There is no android-based learning media in the subject of network server administration. From the results of the preliminary study, it can be illustrated that the learning media used in the learning process still use paper and print media. Student learning outcomes are still far from expectations (KKM). Software development uses the waterfall model development method. In the waterfall there are several main stages that describe software development activities. The reason for using the waterfall method is because the stages in system development in the waterfall model are clearly structured.

Implementasi Openstack untuk Private Cloud pada mata kuliah Administrasi server

Dalam pembelajaran Administrasi Server membutuhkan infrastruktur dan spesifikasi yang lengkap seiring dengan kebutuhan server yang semakin meningkat. Dengan mengatasi kendala kendala infrastruktur, Cloud Computing menawarkan infrastruktur server yang lebih efisien dan fleksibel. Salah satu platform yang menawarkan infrastruktur dan spesifikasi server adalah Openstack. Teknologi komputasi awan dibangun menggunakan sistem operasi Ubuntu Server 18.04 dan versi Victoria dari platform penerapan OpenStack dengan Devstack. Hasil tugas akhir ini diimplementasikan dan digunakan di laboratorium jaringan. Openstack dapat menjalankan 30 pengguna. Pembuatan instance berdasarkan ragam ukuran m1.nano, m1.micro, cirros256, m1.tiny, ds512m, ds1G, dan m1.small. Gambar yang digunakan pada instance adalah cirros-0.5.1-x86_65-disk dan Ubuntu Server 18.04.

Implementation of real-time online mouse tracking on overseas quiz session

Mouse tracking serves as an alternative to eye tracking in measuring the learning process in education because of its affordability. Moreover, mouse tracking does not require extra hardware, as in the case of eye tracking, because it is a feature in personal computers by default. Therefore, it is possible to implement mouse tracking in a massive open scale. However, mouse tracking has only been implemented in a laboratory setting to date, ostensibly because of the associated extremely high running costs. Nonetheless, there is no available data to support the claim of high resource costs, which has resulted in much speculation among implementers. In general, the implementation of mouse tracking in a non-laboratory environment is still rare. Therefore, the authors developed an application to investigate real-time mouse tracking online. It was implemented on the Moodle learning management system and tested on an online quiz session accessed abroad. Additionally, the application can handle tracking on mobile devices. In this work, the main resources that include CPU, network, RAM, and storage costs were measured when mouse tracking was used. These results can serve as a reference for network and server administrators during future implementation of this technique. It was determined that the characteristics of mouse activities were dynamic in that occasional surges and lulls were observed. Additionally, this article also discussed the advantage of real-time and online implementation to regular online implementation and showed that there is a possibility of implementing mouse tracking on a large scale if mouse tracking data are not aggregated and transmitted as a single data package.

Development of evaluation results information system learn based on website

SIP-Eval uses the concept of a decision support system and is developed with a SDLC model by designing using UML. SIP-Eval uses three tests that is assessment testing, usability testing and user accepted testing. Testing do to determine the quality of the item’s product by SIP-Eval and to know the usefulness of the SIP-Eval and to know SIP-Eval can function property. The test results conducted at Vocational High School 7 Jakarta and Vocational High School 26 Jakarta involving 3 Server Administration subject teachers and 27 students of the Computer Network Engineering expertise program show that SIP-Eval has a good ability in assisting users in completing the evaluation of learning outcomes process and can function very well for educators and students in the implementation evaluation of learning outcomes in schools with 73.75% obtained in usability testing and 94.70% in UAT testing. SIP-Eval produces 40 items that are declared valid. Difficulty analysis states that 5 items are too difficult, 34 items are moderate and 1 item is too easy. Differentiating power analysis states that 2 items have a very good, 19 items have well, 7 items are good enough for their power, 3items are not good for their power and 9 items are not very good at their power. Test equipment (assessment) used in the test subjects of server administration class XI even semester has a very high reliability scale with reliability test results obtained at 0.896.

Mystique: A Fine-Grained and Transparent Congestion Control Enforcement Scheme

TCP congestion control is a vital component for the latency of Web services. In practice, a single congestion control mechanism is often used to handle all TCP connections on a Web server, e.g., Cubic for Linux by default. Considering complex and ever-changing networking environment, the default congestion control may not always be the most suitable one. Adjusting congestion control to meet different networking scenarios usually requires modification of TCP stacks on a server. This is difficult, if not impossible, due to various operating system and application configurations on production servers. In this paper, we propose Mystique, a light-weight, flexible, and dynamic congestion control switching scheme that allows network or server administrators to deploy any congestion control schemes transparently without modifying existing TCP stacks on servers. We have implemented Mystique in Open vSwitch (OVS) and conducted extensive test-bed experiments in both public and private cloud environments. Experiment results have demonstrated that Mystique is able to effectively adapt to varying network conditions, and can always employ the most suitable congestion control for each TCP connection. More specifically, Mystique can significantly reduce latency by 18.13% on average when compared with individual congestion controls.

Online learning model development using google classroom on the topic of administration server

This study aims to: (1) generate e-learning-based practice learning model of Server Administration which is valid, useful, exciting, and can be applied to improve the learning outcomes of students in the subject of Administration Server; (2) determine the effectiveness of the implementation of Google Classroom on practice learning Administration Server; (3) monitor the learners in the learning process Server Administration practices inside and outside learning. This study is a Research and Development (R & D) to the conceptual model and using research procedures Borg and Gall. Results obtained eligibility percentage of media experts of 77.5% and 78.5% matter experts with criteria are eligible. Implementation level learning model captured very well at 91.66%. The level of attractiveness of the learners XII TKJ 1 amounted to 83.9% and XII TKJ 2 of 85.1% with very interesting criteria. The results of the analysis of the primary field trials assessing the effectiveness aspect, the value of the students after using the learning model and the overall increase learners or 100% to reach KKM with a limit value of 75, so it can be said to be a beneficial learning model to increase the number of learners.

An Analysis of Spam Email Detection Performance Assessment Using Machine Learning

Spam email is very annoying for email account users to get relevant information. Detection of email spam has actually been applied to email services for the public with various methods. But for the use of a limited number of company's e-mail accounts, not all e-mail servers provide spam e-mail detection features. The server administrator must add a separate or modular spam detection feature so that e-mail accounts can be protected from spam e-mail. This study aims to get the best method in the process of detecting spam emails. Some machine learning methods such as Logistic Regression, Decision Tree, and Random Forest are applied and compared results to get the most efficient method of detecting spam e-mail. Efficiency measurements are obtained from the speed of training and testing processes, as well as the accuracy in detecting spam emails. The results obtained in this study indicate that the Random Forest method has the best performance with a test data speed of 0.19 seconds and an accuracy of 98%. This result can be used as a reference for the development of spam detection using other methods.

Rancang Bangun Pembelajaran Jaringan Server dengan Sistem Server Cloud Virtual (Hypervisor)

Computers now have very high capabilities so they can be used virtualization. With computer capabilities that are high enough computer lab practicum and server administration can already be done on a pc or laptop that has virtualization applications installed. Network practicum and server administration that previously could only be done in the classroom, so with this technology it is expected that it can be practiced on a PC or personal laptop for each student, so that students are able to continue the practical scenario that has been given. Virtualization will use Hyper-V that already exists in Windows 7, Windows 8 and Windows 10. In the Hyper-V application 4 Windows servers will be installed, all of which will be installed and connected via Active Directory. All windows servers will be accessed using a computer and physical network through the Remote Desktop Connection application. So it is expected that with this study student will be able to practice outside the campus lab environment.

Enhancing Cloud Storage Privacy (CSP) Based on Hybrid Cryptographic Techniques

Cloud computing has emerged as a new technology model for providing customized, high quality and reliable services for clients over the Internet. These clients can rent the services as long as they need rather than owning and maintaining large expensive IT infrastructure. One of the most used cloud services is the cloud storage as it provides storage on demand service. Nevertheless, due to the structure of cloud services which may not fully be managed by the cloud clients, the privacy and security of cloud storage become a significant challenge. Most of the previous works on the cloud security trying to solve the security challenges with data encryption techniques. However, these solutions do not protect data from being exposed or read by the server administrator or owner. In this paper, we have proposed a hybrid novel solution referred to as Cloud Storage Privacy (CSP) paradigm to enhance the privacy policies for cloud storage. This framework solution combines three of the superior cryptographic techniques: RSA, AES and Block-Chain. The solution not only secures the asset in the cloud but also protects the asset from unauthorized server access and improving user password protection. We have compared the proposed solution with the best based on our knowledge cloud storage services which are Google Drive and Dropbox in terms of performance and security. The result shows that the proposed solution outperforms existing services.

PERANCANGAN SISTEM PENDETKSI SERANGAN PADA SERVER JARINGAN KOMPUTER MENGGUNAKAN SNORT BERBASIS SMS GETEWAY

Server on a network becomes an important point because its function is to serve all requests required by all clients on a network. For that, maintaining the security of a server is also very important because if the server is experiencing a problem then there is no one the network can serve the request from the client. This makes a server administrator must see traffic to the server at any time. For this reason, it is important to conduct an attack detection system research in order to help the performance of administrators. Detection of attacks directed to the server is an early solution in securing a server from attack. For attack detection systems, SNORT is generally able to detect almost any attack because it has many rules that can be modified. Detection system by configuring and adding the rule first on the server. If there is an incoming attack then SNORT will compare the attack with the existing rule, SNORT will later categorize the attack into 3 types of High, Medium and Low. The design of attack detection system using SNORT and web server is planted on Raspberry Pi. Web server that is planted on Raspberry Pi as information system or container of attack records. In addition, Raspberry Pi also implemented database to store attack log which will be sent via sms gateway. The overall test results of the system built on this final project work well. The admin user can login the web server and do the user creation properly. Among the 6 rule attacks that have been implemented, all rules can read the attack accurately and able to save it into the database. From 75 attacks recorded in the database, only 80% attack detection can be displayed in the web server. And the web server is capable of sending 77.3% of attack notifications to the admin.

Improving Student Assessment of a Server Administration Course Promoting Flexibility and Competitiveness

Contribution: This paper describes a highly flexible design for a master’s-level server administration course that uses updated technologies, addresses the most important course design challenges and extracts useful feedback from student work. The main contribution of this design is eliminating the self-regulation challenge students encounter in similar highly flexible computer-related courses. This is attributed to the introduction of orientation lectures and a competitive element; these may have helped students to achieve their goals on time. Background: The Web server administration course on the master’s of the Web engineering program was intended to inculcate a series of competences, such as common administration techniques, procedures to increase security, efficient website deployment, and an introduction to clusters and infrastructure deployment automation. The course generally failed to transmit these competencies effectively; complaints were made about the difficulty of the course and the low applicability of its contents. Intended Outcomes: The design facilitates students finding assessment activities that better suit their profiles or previous experience, and enables them to customize their assessment, thus encouraging them and giving future value to their work. Application Design: The course design maximizes assessment flexibility by providing students with many optional activities from which to choose. It also promotes a healthy competitive spirit to improve student’s motivation and results. Findings: Complaints about the difficulty or lack of applicability were no longer made. The course is highly valued by the students, achieving a very high pass rate and average score.

Design and development of vulnerability management portal for DMZ admins powered by DBPowder

It is difficult to promote cyber security measures in research institutes, especially in DMZ networks that allow connections from outside network. This difficulty mainly arises from two types of variety. One is the various requirements of servers operated by each research group. The other is the divergent skill level among server administrators. Unified manners rarely fit managing those servers. One of the solutions to overcome the above mentioned difficulties is vulnerability management. To overcome these challenges, There are two possible approaches. One of the options is to offer a simple and powerful vulnerability management service to the administrators of the DMZ hosts (DMZ admins). The other is to facilitate flexibility and efficiency in the development process of the service. To achieve these requirements, we designed and developed a vulnerability management portal site for DMZ admins, named DMZ User’s Portal. This paper describes the design of DMZ User’s Portal and the development process using a development framework, named DBPowder. Using the DMZ User’s Portal, each DMZ admin can perform a vulnerability scan on his/her own servers with ease. In other words, this delegates security vulnerability discovery and responsibility to individual DMZ admins that improve security awareness for them. Then, each DMZ admin can grasp and manage the security by himself/herself. The 13-year result from vulnerability scans show that the status of security in the KEK-DMZ has been kept in good conditions. Also, we are developing DBPowder object-relational mapping (ORM) framework to improve the flexibility and efficiency in the development process of DMZ User’s Portal.

Privacy preserving biometric‐based remote authentication with secure processing unit on untrusted server

Biometric-based authentication systems offer undeniable benefits to users. However, biometric features are vulnerable to attacks, especially those happening over transmission network or at the stored biometric templates. In this work, we propose a novel biometric-based remote authentication framework to deal with malicious attacks over the transmission channel and at the untrusted server. More concretely, the proposed framework is not only resistant against attacks on the network but also protects biometric templates stored in the untrusted server's database, thanks to the combination of fuzzy commitment protocol and non-invertible transformation techniques. The notable feature as compared to previous biometric based remote authentication framework is its ability to defend the sensitive data against different kinds of insider attacks. The server's administrator is incapable of utilizing information saved in its database to impersonate the clients and deceive the whole system because secure computing in the server is guaranteed by employing a secure coprocessor embedded in the server. In addition, the system performance is maintained with the support of random orthonormal project, which reduces computational complexity while preserving its accuracy.

Smart Contract-Based Review System for an IoT Data Marketplace.

Internet of Things (IoT)-based devices, especially those used for home automation, consist of their own sensors and generate many logs during a process. Enterprises producing IoT devices convert these log data into more useful data through secondary processing; thus, they require data from the device users. Recently, a platform for data sharing has been developed because the demand for IoT data increases. Several IoT data marketplaces are based on peer-to-peer (P2P) networks, and in this type of marketplace, it is difficult for an enterprise to trust a data owner or the data they want to trade. Therefore, in this study, we propose a review system that can confirm the reputation of a data owner or the data traded in the P2P data marketplace. The traditional server-client review systems have many drawbacks, such as security vulnerability or server administrator’s malicious behavior. However, the review system developed in this study is based on Ethereum smart contracts; thus, this system is running on the P2P network and is more flexible for the network problem. Moreover, the integrity and immutability of the registered reviews are assured because of the blockchain public ledger. In addition, a certain amount of gas is essential for all functions to be processed by Ethereum transactions. Accordingly, we tested and analyzed the performance of our proposed model in terms of gas required.

Implementation and efficiency analysis of composite DNS-metric for dynamic server selection

User requirements for a high availability and fast response time of network services require placing more than one server for accessing particular network service, often using multiple communication links and locations. Dynamic Server Selection (DSS) is a new DNS method for the optimal server selection of a multiple available network service that allows dynamic selection of a server on the client side based on the information of the server load and its network topological distance from the client. The server selection is based on the calculations of a composite DNS-metric in which servers, whose IP addresses are sent in a DNS response, are ranked from the optimal to the least suitable. Calculation parameters are server response time, which the client measures for each server independently, and the server load, which is specified by the server administrator and is forwarded to the client together with the rules for calculating the composite DNS-metric. The DSS method has the lowest overall network service response time in comparison with the other four observed methods (Geographical, Hops, Random and RTT) which, in measurements done in a real time environment for two servers accessible by two independent internet links each, have a longer response time from 8.5 to 26.8% compared to DSS. Results of the proposed analytical model for calculating the efficiency index of the DSS method are compared with results of the practical measurements confirming the relevance of the analytical model. In measurements, the DSS method achieved a high average efficiency index of 1.23.

DEVELOPMENT OF E-MODULE PROJECT BASED LEARNING MODEL IN SERVER ADMINISTRATION BASICS CLASS XI COMPUTER ENGINEERING AND NETWORKS IN SMK NEGERI 3 SINGARAJA.

ABSTRACTThe purpose of this study (1) In order to implement the results of the E-Module Project Based Learning Model in Server Administration Basics Class XI Computer Engineering and Networks in SMK Negeri 3 Singaraja. (2) To study the response of teachers and students towards the development of E-Module Project Based Learning Model in Server Administration Basics Class XI Computer Engineering and Networks in SMK Negeri 3 Singaraja developed.The type of the research used in this study was Research and Development using ADDIE development model. The subjects of the study were the eleven grade students of Computer Engineering and Networks at SMK Negeri 3 Singaraja in academic year 2017/2018. In order to identify the teachers’ and students’ respond toward the e module of Network Design, questionnaire was used to obtain the data. The results obtained shown that (1) the results of the E-Module Project Based Learning Model in Server Administration Basics Class XI Computer Engineering and Networks in SMK Negeri 3 Singaraja otherwise successfully applied by some of the tests conducted. (2) The results of the analysis show that the teacher response data, obtained an average score of response was 43 when converted into the classification table, the response included in the category of positive. As for the students' response to the development of e-modules obtained an average score of 60.78 response, if converted into a table classifying student responses included in the category of positive. Keywords: E-Module, ADDIE, Server Administration, Project Based Learning

Trusted detection of ransomware in a private cloud using machine learning methods leveraging meta-features from volatile memory

Cloud computing is one of today's most popular and important IT trends. Currently, most organizations use cloud computing services (public or private) as part of their computer infrastructure. Virtualization technology is at the core of cloud computing, and virtual resources, such as virtual servers, are commonly used to provide services to the entire organization. Due to their importance and prevalence, virtual servers in an organizational cloud are constantly targeted by cyber-attackers who try to inject malicious code or malware into the server (e.g., ransomware). Many times, server administrators are not aware that the server has been compromised, despite the presence of detection solutions on the server (e.g., antivirus engine). In other cases, the breach is detected after a long period of time when significant damage has already occurred. Thus, detecting that a virtual server has been compromised is extremely important for organizational security. Existing security solutions that are installed on the server (e.g., antivirus) are considered untrusted, since malware (particularly sophisticated ones) can evade them. Moreover, these tools are largely incapable of detecting new unknown malware. Machine learning (ML) methods have been shown to be effective at detecting malware in various domains. In this paper, we present a novel methodology for trusted detection of ransomware in virtual servers on an organization's private cloud. We conducted trusted analysis of volatile memory dumps taken from a virtual machine (memory forensics), using the Volatility framework, and created general descriptive meta-features. We leveraged these meta-features, using machine learning algorithms, for the detection of unknown ransomware in virtual servers. We evaluated our methodology extensively in five comprehensive experiments of increasing difficulty, on two different popular servers (IIS server and an email server). We used a collection of real-world, professional, and notorious ransomware and a collection of legitimate programs. The results show that our methodology is able to detect anomalous states of a virtual machine, as well as the presence of both known and unknown ransomware, obtaining the following results: TPR = 1, FPR = 0.052, F-measure = 0.976, and AUC = 0.966, using the Random Forest classifier. Finally, we showed that our proposed methodology is also capable of detecting an additional type of malware known as a remote access Trojan (RAT), which is used to attack organizational VMs.

Docker Container Manager: A Simple Toolkit for Isolated Work with Shared Computational, Storage, and Network Resources

We present a simple set of command line interface tools called Docker Container Manager (DCM) that allow users to create and manage Docker containers with preconfigured SSH access while keeping the users isolated from each other and restricting their access to the Docker features that could potentially disrupt the work of the server. Users can access DCM server via SSH and are automatically redirected to DCM interface tool. From there, they can create new containers, stop, restart, pause, unpause, and remove containers and view the status of the existing containers. By default, the containers are also accessible via SSH using the same private key(s) but through different server ports. Additional publicly available ports can be mapped to the respective ports of a container, allowing for some network services to be run within it. The containers are started from read-only filesystem images. Some initial images must be provided by the DCM server administrators, and after containers are configured to meet one’s needs, the changes can be saved as new images. Users can see the available images and remove their own images. DCM server administrators are provided with commands to create and delete users. All commands were implemented as Python scripts. The tools allow to deploy and debug medium-sized distributed systems for simulation in different fields on one or several local computers.

Indico 2.0 – the whole Iceberg

The last two years have been atypical to the Indico community, as the development team undertook an extensive rewrite of the application and deployed no less than 9 major releases of the system. Users at CERN have had the opportunity to experience the results of this ambitious endeavour. They have only seen, however, the “tip of the iceberg“.Indico 2.0 employs a completely new stack, leveraging open source packages in order to provide a web application that is not only more feature-rich but, more importantly, builds on a solid foundation of modern technologies and patterns. But this milestone represents not only a complete change in technology – it is also an important step in terms of user experience and usability that opens the way to many potential improvements in the years to come.In this article, we will describe the technology and all the different dimensions in which Indico 2.0 constitutes an evolution vis-à-vis its predecessor and what it can provide to users and server administrators alike. We will go over all major system features and explain what has changed, the reasoning behind the most significant modifications and the new possibilities that they pave the way for.

Protect the operating environment internet voting systems

In this paper we propose a method of creating a secure operating environment for Internet voting system server, which eliminates the causes of public distrust about the possible falsification of results or disclosure of the secretsof the vote. The method is based on the concept of the security kernel. Portion of memory is allocated in the server, where exclusive access to the data of the vote counting process has previously verified open application. To prevent access to this memory portion of any other processes is used an open operating system, which does not have functions for such access. Furthermore, conditions have been created for the remote monitoring of the integrity of any and all files and processes on the server, as well as all of the personnel server administration from an unlimited number of controllers that can become any person concerned. It is shown that the proposed method in conjunction with known methods of protecting information transmitted via open channels, it makes it possible to identify any and all possible threats to disclose the secrets of the vote counting and distortion of the results of Internet voting systems. The introduction of this method can be useful in many areas for all public and expert remote surveys that require counting accuracy and secrecy of the vote in full confidence to any and all participants in the electoral process.