Open Server Research Articles

Method of automated search of unauthorized cryptocurrency mining in server operating system containers

It is known that with the growing popularity of blockchain and cryptocurrency technology, many people want to make money on it. As a result, hackers who use other people's resources for easy profit are becoming more active. There are many different tools available today to protect user’s personal computers from cryptojacking, but effective protection for server operating systems are still actual.This paper investigates the possibility of searching for unauthorized cryptocurrency mining processes by three parameters: search for suspicious processes by name, by binary signature and by connection to the mining pool.Based on the study, a method of automated search for unauthorized cryptocurrency mining in server OS containers was proposed, which consists of 5 main stages:1. Search for unauthorized cryptocurrency generation processes by process name.2. Search by binary signature.3. Search for a connection to a mining pool4. Detection of the process of unauthorized mining and stopping the container in which the mining process was detected.5. Notification of the system administrator about the detection of unauthorized cryptocurrency generation processes.It is worth noting that, unlike existing tools, the developed method searches for containers from the host virtual machine, so that there is no need to run a search in each of the containers, as it can be a large number of them and as a result reduce the load on the system.The block diagram of the application for the implementation of the proposed method was also described, as well as examples of stopping the container in which an unauthorized mining process was found and the corresponding message to the system administrator.In addition, a study of the speed of the proposed method was conducted. The results of the test showed a time of 2,585 seconds, which reflects the fast operation and the absence of additional overload on the system.

Fast Identity Online-Based Facial Authentication System Development in Mobile

Recently, research on methods to improve upon the security vulnerability of password based authentication is being actively conducted. Research on how to use real-time biometric recognition is also actively underway. The system development of Public Key Infrastructure (PKI) key pairs and uses a method that safely stores the produced keys in secure zones, and encryption key data is composed so that access can only be made in Fast Identity Online (FIDO) Authenticator zones. Face certification data extracted from the face recognition engine is created, data can be accessed and saved through encryption. With the Fast Identity Online (FIDO) Authenticator, a method was developed that compares and face certification data. The system in this thesis developed a Fast Identity Online (FIDO) based face certification system that uses biometric authentication to supplement the weaknesses of password based systems which were used for user certification in the past because they cost little and are convenient. System development in this thesis was conducted by applying a Fast Identity Online (FIDO) based certification system to an Active Shape Model (ASM) style face recognition algorithm. After taking a photo of the face with the user’s cellular phone and saving it, certification is carried out through comparisons made of the photo and real-time input images. Once certification is made using Fast Identity Online (FIDO) protocols, tests of face detection speed and matching speed are conducted to measure accuracy and speed. A total of 30 tests were conducted and test results showed that detection speed was an average of 30.35 f/s and matching speed was 14.16 ms. In this paper, biometric authentication security and convenience are provided by using security functions provided by user devices and supplementing them with a server operation method.

Design of Reliable Disaster Recovery System through Integrated Server Redundancy

Even before the September 11 terrorist attacks in the United States in 2001, information systems prepared against disasters in Korea were extremely weak. However, as various domestic and foreign accident cases have occurred, it is recognized that preparations for this are necessary. Accordingly, at present, each institution has prepared and implemented various backup policies to protect the institution's information and data in case of disaster. Therefore, in this paper, we conducted a study to design a more stable and efficient disaster recovery system by building redundancy for server operating in integrated data center. To do this, we analyzed the redundancy design for the integrated disaster recovery server and designed the overall system configuration. Also, the design results were analyzed by testing web server redundancy and switch redundancy. In this paper, the proposed design method for stabilization and efficiency of disaster recovery system is the redundant construction of integrated server and switch. In other words, the disaster recovery system was composed of active storage and standby storage, and data stabilization was promoted through real-time replication of each other. In the existing disaster recovery system, there is a problem in stabilizing replication because there is no monitoring system for internal replication between storage arrays. To solve this problem, we designed a system that replicates all data in active storage to standby storage in real time and monitors the replication status. Therefore, introducing service conversion automation from the main system, which is the method designed in this paper, to the disaster recovery system, improves the stability and reliability of the service of the local governments, so that it is possible to operate a more efficient and advanced disaster recovery system.

Pазработка картографического веб-сервиса природного парка «Кондинские озера»

Currently, many protected natural areas (PNA) implement geographic information systems (GIS) and technologies for structuring and managing collected spatial data to support of monitoring and scientific research. GIS of protected areas may be developed based on various software products and characterized by different level of functionality. Also, online web map services on this topic are being developed, which provide access to data not for employees only, but also for users. This paper focuses on the development of a web-GIS of the Kondinsky Lakes natural park located in the Tyumen region of Russian Federation and ensuring the preservation of unique river systems, landscapes, cultural and historical natural monuments. The web service includes cartographic layers and attribute data to characterize the main activities of the natural park. GIS layers are divided into thematic groups and contain information about flora and fauna, forest fires, logged areas, resting places and objects of the oil and gas mining in the park. The project is implemented using Leaflet, a popular open source web application development library. The code was written using the markup language HTML 5, CSS 3 and JavaScript. Data management is implemented using PostgreSQL DBMS. The publication is created based on the open GIS server Geoserver. The data structure and functionality of the developed web service is also presented. The developed web service can be used by both employees of the natural park (to develop the content of the databases) and its visitors, as well as organizations working in the field of environmental education and tourism.

Nonintrusive Load Management Based on Distributed Edge and Secure Key Agreement

With the advancement of national policies and the rise of Internet of things (IoT) technology, smart meters, smart home appliances, and other energy monitoring systems continue to appear, but due to the fixed application scenarios, it is difficult to apply to different equipment monitoring. At the same time, the limited computing resources of sensing devices make it difficult to guarantee the security in the transmission process. In order to help users better understand the energy consumption of different devices in different scenarios, we designed a nonintrusive load management based on distributed edge and secure key agreement, which uses narrowband Internet of things (NB‐IoT) for transmission and uses edge devices to forward node data to provide real‐time power monitoring for users. At the same time, we measured the changes of server power under different behaviors to prepare for further analysis of the relationship between server operating state and energy consumption.

A Method to Prevent SQL Injection Attack using an Improved Parameterized Stored Procedure

Structured Query Language (SQL) injection is one of the critical threats to database security. The effects of SQL injection attacks cause the data contained in the database to be at risk of being exploited by irresponsible parties, compromising data integrity, disrupting server operations and in return affecting the organization's image. Although SQL injection is an attack performed at the application level, SQL injection prevention requires security controls at all levels, namely application level, database level and network level. The absence of SQL injection prevention measures at the application level makes the database vulnerable to attack. Reviews indicate that the current approaches still not sufficient in addressing these three issues, which are i) improper use of dynamic SQL, ii) lack of input validation process and iii) inconsistent error handling. Currently, program and database code security is based solely on basic security measures that are focused at the network level such as network firewalls, database access control and web server request filtering. Unfortunately, these measures are still inadequate and not sufficient to safe guard the program code and databases from the attack. To overcome this shortcoming as addressed by these three issues, a new comprehensive method is proposed using an improved parameterized stored procedure to enhance database security. Experimental results prove that the proposed method is able to prevent SQL injection from occurring and able to shorten the processing time when compared with existing methods, hence able to improve database security.

An Effective Fault‐Tolerant Intrusion Detection System under Distributed Environment

Traditional intrusion detection system is limited to a single network or several hosts, which has been seriously unable to fulfill the growing information security problems. This paper uses the distributed technology to design and implement an intrusion detection system (IDS) based on the hybrid of Hadoop with some effective open‐source technologies. On the one hand, it can efficiently realize the data acquisition and analysis under distributed environment. On the other hand, it can solve the problems of single‐point fault‐tolerant and the insufficient data processing capacity of the traditional intrusion detection system. In this IDS, RabbitMQ, Flume, and MongoDB are utilized to act as the middleware of this system to build the system environment which includes the collector, analyzer, and data storage. By detecting the CPU and memory usage of hosts, TCP connections, network bandwidth, web server operation logs, and the logs of user behavior, the proposed IDS especially focuses on monitoring the first four parts, which can better detect external distributed denial of service attacks and intrusions and send automatically alarm service information to the administrators.

Automated Server Operation Model to Improve the Efficiency of Domain Services

While using the internet services, users tend to frequently experience the inconvenience in service due to buffering caused by overloads in the domain service server. If there are some margins for availabilities for the service server, the above issue does not occur, so it is possible to remove the inconvenience. In each time period of the domain that provides the service, the peak traffic data is collected to configure the data set, and the peak traffic data in each time period within the configured data set is summed up. After that, in this newly proposed model, the cumulative hourly peak traffic data is checked in terms of whether it exceeds the availability threshold set by an operator, and if it does, it is transferred to other pool group (pool N). The test results for the proposed model indicates that in the past, it normally took 2 hours to analyze the domain traffic data and 10 to 20 minutes to apply the analysis results, but in the newly proposed model, it takes only less than 5 minutes to analyze and apply results. System load frequency is reduced from 13 times a month to 1 time per month, and also the number of times to use the reserved server is reduced from 18 times to 2 times. The CPU margin rate is increased from 27% to 71%, which indicates that the usage rate is decreased. Overall, the operator’s resource is reduced, and thus it is possible to achieve server stability as well.

Password-Authenticated Decentralized Identities

Password-authenticated identities, where users establish username-password pairs with individual servers and use them later on for authentication, is the most widespread user authentication method over the Internet. Although they are simple, user-friendly, and broadly adopted, they offer insecure authentication and position server operators as trusted parties, giving them full control over users’ identities. To mitigate these limitations, many identity systems have embraced public-key cryptography and the concept of decentralization. All these systems; however, require users to create and manage public-private keypairs. Unfortunately, users usually do not have the required knowledge and resources to properly handle cryptographic secrets, which arguably contributed to the failures of many end-user public-key infrastructures (PKIs). In fact, as of today, no end-user PKI, able to authenticate users to web servers, has a significant adoption rate. In this paper, we propose Password-authenticated Decentralized Identities (PDIDs), an identity and authentication framework where users can register their self-sovereign username-password pairs and use them as universal credentials. Our system provides a global namespace, human-meaningful usernames, and resilience against username collision attacks. A user’s identity can be used to authenticate the user to any server without revealing that server anything about the password, such that no offline dictionary attacks are possible against the password. We analyze PDIDs and implement it using existing infrastructures and tools. We report on our implementation and evaluation.

PERANCANGAN PIRANTI LUNAK RESPONSIVE UNTUK MONITORING RUANGAN SERVER MENGUNAKAN NODEMCU ESP8266 BERBASIS INTERNET OF THINGS

The role of the server is very important as a data service provider and control for an office that has a very large data usage and control system. This can also affect the temperature in the server room which has computer devices and other control systems because of its continuous use. The impact of temperature that is outside of its tolerance value due to the dead air conditioner without being noticed by the officer or server operator can result in damage to the hardware devices in the server room. Monitoring and measuring server room temperature is not possible to be done directly and accurately in all conditions due to several inhibiting factors in obtaining temperature information. With these problems, a temperature monitoring prototype was built using node MCU ESP 2866 and DHT 21 sensor with responsive web-based software so that it can be easily seen on various PC and smartphone monitors. This software can be used in server rooms to provide room temperature information to operators or server officers. The long-term objective of this research is expected to provide information Real-time temperature conditions in a responsive web-based server room.

Analysis of Host Resources Utilization by OpenStack in Ubuntu Environment

Cloud computing is one of the frontier technologies, which over the last decade has gained a widespread commercial and educational user base. OpenStack is one of the popular open source cloud management platforms for establishing a private or public Infrastructure-as-a-Service (IAAS) cloud. Although OpenStack started with very few core modules, it now houses nearly 38 modules and is quite complex. Such a complex software bundle is bound to have an impact on the underlying hardware utilization of the host system. The objective is to monitor the usage of system resources by OpenStack on commodity hardware. This paper analyzes the effect of OpenStack on the host machine's hardware. An extensive empirical evaluation has been done on different types of hardware, at different virtualization levels and with different flavours of operating systems comparing the CPU utilization, memory consumption, disk I/O, network, and I/O requests. OpenStack was deployed using Devstack on a single node. The novel aspect of this work is monitoring the resource usage by OpenStack without creating virtual machines on commodity hardware. From the analysis of data, it is observed that standalone machine with Ubuntu server operating system is the least effected by OpenStack and thereby has more available resources for computation of user workloads. Doi: 10.28991/esj-2020-01246 Full Text: PDF

Development of an Algorithm for Bus Routing and Tracking for an Educational Institution: A Case Study

The demand for an institution bus service varies every year, and it affects the efficiency if the service remains static. This necessitates the need to develop a procedure to identify optimum bus stops and routes to incorporate the annual variation in demand. This study was aimed to develop an algorithm for the reallocation of bus stops and routes for an institutional bus service considering the annual demand variation. The algorithm developed in the study identifies the optimum bus stops and routes to cater to the demand in a Geographic Information System (GIS) platform. The students are assigned to the nearest bus stop and the optimum routes are developed by ensuring equity. The location data of buses in real time will aid the traveller to reduce their waiting time. The developed algorithm was validated and tested with field data and results provided routing with better level of service and equity. A WebGIS based user interface was also created in the study for providing the real time location details of the requested bus to the user. The open servers like GeoServer and PostgreSQL were used for the creation of layers in the user interface, and the webpage was created with Java script and PHP language.

Fault-Tolerant Covering Problems in Metric Spaces

In this article, we study some fault-tolerant covering problems in metric spaces. In the metric multi-cover problem (MMC), we are given two point sets Y (servers) and X (clients) in an arbitrary metric space $$(X \cup Y, d)$$ , a positive integer k that represents the coverage demand of each client, and a constant $$\alpha \ge 1$$ . Each server can host a single ball of arbitrary radius centered on it. Each client $$x \in X$$ needs to be covered by at least k such balls centered on servers. The objective function that we wish to minimize is the sum of the $$\alpha $$ -th powers of the radii of the balls. We also study some non-trivial generalizations of the MMC, such as (a) the non-uniform MMC, where we allow client-specific demands, and (b) the t-MMC, where we require the number of open servers to be at most some given integer t. We present the first constant approximations for these fault-tolerant covering problems. Our algorithms are based on the following paradigm: for each of the three problems, we present an efficient algorithm that reduces the problem to several instances of the corresponding 1-covering problem, where the coverage demand of each client is 1. The reductions preserve optimality up to a multiplicative constant factor. Applying known constant factor approximation algorithms for 1-covering, we obtain our results for the MMC and these generalizations.

A Hybrid Dynamic Encryption Scheme for Multi-Factor Verification: A Novel Paradigm for Remote Authentication.

A significant percentage of security research that is conducted suffers from common issues that prevent wide-scale adoption. Common snags of such proposed methods tend to include (i) introduction of additional nodes within the communication architecture, breaking the simplicity of the typical client–server model, or fundamental restructuring of the Internet ecosystem; (ii) significant inflation of responsibilities or duties for the user and/or server operator; and (iii) adding increased risks surrounding sensitive data during the authentication process. Many schemes seek to prevent brute-forcing attacks; they often ignore either partially or holistically the dangers of other cyber-attacks such as MiTM or replay attacks. Therefore, there is no incentive to implement such proposals, and it has become the norm instead to inflate current username/password authentication systems. These have remained standard within client–server authentication paradigms, despite insecurities stemming from poor user and server operator practices, and vulnerabilities to interception and masquerades. Besides these vulnerabilities, systems which revolve around secure authentication typically present exploits of two categories; either pitfalls which allow MiTM or replay attacks due to transmitting data for authentication constantly, or the storage of sensitive information leading to highly specific methods of data storage or facilitation, increasing chances of human error. This paper proposes a more secure method of authentication that retains the current structure of accepted paradigms, but minimizes vulnerabilities which result from the process, and does not inflate responsibilities for users or server operators. The proposed scheme uses a hybrid, layered encryption technique alongside a two-part verification process, and provides dynamic protection against interception-based cyber-attacks such as replay or MiTM attacks, without creating additional vulnerabilities for other attacks such as bruteforcing. Results show the proposed mechanism outperforms not only standardized methods, but also other schemes in terms of deployability, exploit resilience, and speed.

Virtual CPU Scaling for Efficient Server Power Consumption in Cloud Data Center

Cloud computing is a fast-growing technology used by major corporations these days because of the flexibility framework it provides to consumers. Cloud technology requires large data centers consisting of multiple IT equipment and servers. One main problem with these data centers is the vast amount of power consumed during servers operation. This reduces financial benefit and increases the need to produce more energy to cover the needs of operating the cloud infrastructure. This paper proposes an approach for managing the virtual central processing unit (vCPU) of a virtual machine to improve server power efficiency. A framework is used to study the proposed approach while processing different types of workloads widely found in most general-purpose cloud computing applications. Results indicate an improvement in server power saving.

The Method of Logic Cyber Attack Detection of Abuse Functionality Type on Nginx Http-Server and Apache on the Basis of Fuzzy Logic

The article presents a method of abuse detection functionality of the most common open source http-servers Nginx and Apache, which currently implement a full web stack and serve more than 60% of traffic on the Internet. The proposed method is based on the application of the mathematical apparatus of fuzzy set theory and fuzzy inference to the selected analysis parameters corresponding to the properties of a logical cyber attack that realizes the vulnerability of web server data. To obtain the most accurate results of fuzzy inference the direction of adaptation of membership functions to the conditions of server operation (changes on the server and analysis of client behavior) based on the application of the mathematical apparatus of genetic algorithms is determined.

A Development of Medical Records Management System to Health Care Decision Makers using Cloud Technologies

Electronic Health Record systems continue to be incorporated into health care facilities to reduce the problems and limits of paper-based methodology but their deployment has been slow due to high investment and storage costs. The Enterprise Electronic Cloud-based Health Record System is planned, created and checked for recording, recovering, chronicling and surveying patients and other clinical records. Cloud Data fills in as a coordinates information bank over every single authoritative emergency clinic, middleware gives a typical stage to all electronic health record frameworks between remote medical clinics while a security approval server gives access to approves clients and denies unapproved clients access to records or assets in the system. In this model, complex mixes are redistributed to open cloud servers, leaving nearly the whole intricate of private key generator, sender and beneficiary. In addition, PKG communication costs with users have been optimized. In addition, we are building a comprehensive library called libabe compatible with mobile devices, and the access control mechanism is distributed in a logical environment, including public cloud servers, a laptop and an inexpensive mobile device with interactive resources.

A Multiserver Tandem Queue with a Specialist Server Operating with a Vacation Strategy

In the considered queueing system, the service is provided at two stations, station 1 and station 2 operating in tandem. Station 1 is a multi-server station with c identical servers working in parallel, and station 2 is equipped with a single server called the specialist server. The service times of each of the servers at station 1 follow an exponential distribution. The specialist server has phase-type distributed service times. Customers arrive at station 1 according to a Markovian arrival process. An arriving customer enters directly into service at station 1 if at least one of the servers is idle, otherwise joins an infinite queue. After receiving service at station 1, customers either proceed to station 2 or can exit the system. There is a finite buffer between two stations. When the buffer is not full, a customer coming out of the station 1 joins the buffer with a probability p or leaves the system with the complementary probability 1 − p. If the buffer is full, then all the customers coming out of station 1 are lost forever. The server at the station 2 will be turned on only if the number of customers in the buffer reaches a threshold. Once the server is turned on, the service will be rendered until the buffer is emptied. A stability condition for this system is established and the stationary distribution is obtained using matrix analytic methods. Various performance measures are also calculated. Our model is motivated by a hospital situation where station 1 represents the causalty clinic and the specialist server represents an expert giving a consultation upon the request of a threshold number of patients.

Research and Application of Server Health State Prediction Model Based on BP Neural Network

As the core equipment of the data center, the importance of the operation and maintenance of the server is self-evident. In order to improve the operation and maintenance of data center server, this paper selected the feature quantity using the analysis method of grey correlation and established server operation parameters and health state prediction model using BP neural network algorithm in machine learning. The model can predict server health status and made fault early warning which provide decision support for operation and maintenance. This can reserve the responding time for problems and realize “active” operation and maintenance of data center servers.

Research on Server Health State Prediction Model Based on Support Vector Machine

With the development of artificial intelligence, machine learning methods have been widely applied to predictive modelling in various fields. Support vector machine is a linear classifier with the largest interval defined on the feature space. In order to improve the current status of server operation and maintenance, and improve the accuracy and efficiency of server health prediction, this paper studies the feature quantity selection based on grey relational analysis, studies the support vector machine applied to data generalization and classification, and establishes a health prediction model. The simulation training of historical data shows that the method has fast learning, high prediction speed, high efficiency, high accuracy and wide application prospects.