Back-end Database Research Articles

Mutual Authentication Protocol for Role-Based Access Control Using Mobile RFID

The Internet has become the main transmission media in modern information systems due to the popularization of information technology and the rapid development of network technology. To use the Internet, we need complete security mechanisms which include requirements such as integrity, security and privacy to ensure the legal user can login to a remote server to get the service and resources they need. The radio frequency identification (RFID) is a very convenient technology with the property of non-contact reading. It uses the tag embedded in the object to identify the information quickly. Now, more and more devices are equipped with the RFID reader. Hence, the user can use the RFID reader embedded in the mobile device through a wireless network to read the information on the tag and then use the service which is called Mobile RFID. Compared to traditional RFID, the characteristic of mobility makes the reading more flexible. It can deal with the events in real-time and undertake the process faster and more efficiently. The major security problem of Mobile RFID is privacy, which is also a consideration when constructing a Mobile RFID Mechanism. In this paper, we propose a secure authentication mechanism which uses the authenticated delegating mechanism in Mobile RFID to enable the reader to get the specific role authority through a back-end database server. The reader has to undertake mutual authentication with the back-end database server and the tag. Then, it can protect the information and limit the access times of the reader to achieve privacy.

Investigating students’ use of lecture videos: Learning analytics vs. self-evaluation surveys

This presentation examines students’ use of lecture videos through two approaches -- (1) students’ real usages of lecture videos as collected from Blackboard, a learning management system which can track students’ activities and store every click in its backend database or in the web server log file, and (2) a self-evaluation of students’ study strategies in the course survey at the end of the semester. This study was conducted in a fully online psychology course taught in Fall 2014, Summer 2015, and Fall 2015. The course included 76 streaming lecture videos ranging from 3.5 to 30 minutes. A comparison between these two sets of data was examined and discussed in this presentation.The preliminary analysis revealed that most students’ study strategies reported on the survey were consistent with their real usages on the Blackboard course site. However, survey data could not explain which lecture videos students had watched and how frequently students watched videos. Learning analytics can support instructors in understanding how students used videos, when they watched, and which videos were watched most. The data also implied that students’ final grades and learning satisfaction associated with their usage of lecture videos. As compared to survey data, the evidence indicated that learning analytics can give more detailed and accurate descriptions about students’ learning behaviors. This presentation will share the limitations of either method. This presentation will benefit both undergraduate and graduate courses whose instructors plan to use surveys or learning analytics to understand their students’ learning behaviors and study strategies.

Implementing MIMOSA Standard

A common challenge to Prognostic Health Management (PHM) systems is the management of data across different organizations based on a standardized format and meaning. The Open System Architecture for Condition-based Maintenance (OSA-CBM) and the Open System Architecture for Enterprise Application Integration (OSA-EAI) are complementary reference architectures for domain-independent asset and condition data management. In previous papers, we reported on our experiences with implementing a data integration layer based on these two architectures. In this paper, we report on our experience implementing code generators for binary OSA-CBM and OSA-EAI Tech-CDE (Compound Document Exchange), and the utilization of the resulting components within the OMAHA project. OMAHA aims towards an overall management architecture for health analysis, incorporating manufacturers, operators and maintainers of fleets of aircraft.The OSA-CBM standard specifies a message structure but leaves the assembly and disassembly of OSA-CBM data up to the implementor. Our solution is a builder/reader Application Programming Interface (API) for a binary OSA-CBM message codec which we have implemented under the constraints of a real-time computing environment. The required C code is automatically generated from the provided technical documentation for OSA-CBM. We discuss the properties of the resulting codec and point out future improvements for the OSA-CBM binary protocol to improve consistency and to add the capability of streaming. Using the same generative approach we have implemented a code generator for a Tech-CDE-compliant middleware system, consisting ofclient libraries (currently C++ and Java), a network layer, a server portion, and a database backend. Analogously to OSA-CBM, the code generator processes the documentation provided for Tech-CDE, creating both productive and testing code. We discuss the properties of the resulting system, report specific limitations of the Tech-CDE protocol and suggest mitigations. The paper concludes with an experience report from utilizing our work in the OMAHA project. While Tech-CDE was generally found sufficient, we identified areas of improvement, including protocol properties and entity coverage. We were able to make customizations using our generative coding approach and present these as suggestions for future standard extensions.

SQLI-Dagger, a Multilevel Template based Algorithm to Detect and Prevent SQL Injection

injection attacks are often found within the dynamic pages of a web application that exploit the security vulnerability of the database layers of an application. In this attack category a specifically crafted SQL command is entered in the form field of a web application instead of the expected information. SQL injection takes advantages of the design flaws in poorly designed web applications to poison SQL statements and bypass the normal methods of accessing the database content .In these types of Injection attempt the database server execute undesirable SQL Code to steal, manipulate or delete the content of a database. The proposed algorithm is implemented on an application which is placed on a proxy server kept between the Database server and a web server. It is working on multi-level template based approach, which is a model based approach to detect the illegal queries before they are executed on the database server. With the support of the query evaluation engine it can detect and block the injected query. Only the benign query is allowed to get the access to the back end database server. An alert message is generated if there is an Injection.

SQLiGoT: Detecting SQL injection attacks using graph of tokens and SVM

SQL injection attacks have been predominant on web databases since the last 15 years. Exploiting input validation flaws, attackers inject SQL code through the front-end of websites and steal data from the back-end databases. Detection of SQL injection attacks has been a challenging problem due to extreme heterogeneity of the attack vectors. In this paper, we present a novel approach to detect injection attacks by modeling SQL queries as graph of tokens and using the centrality measure of nodes to train a Support Vector Machine (SVM). We explore different methods of creating token graphs and propose alternative designs of the system comprising of single and multiple SVMs. The system is designed to work at the database firewall layer and can protect multiple web applications in a shared hosting scenario. Though we focus primarily on web applications developed with PHP and MySQL, the approach can be easily ported to other platforms. The experimental results demonstrate that this technique can effectively identify malicious SQL queries with negligible performance overhead.

MiTALOS v2: Analyzing Tissue Specific microRNA Function.

MicroRNAs are involved in almost all biological processes and have emerged as regulators of signaling pathways. We show that miRNA target genes and pathway genes are not uniformly expressed across human tissues. To capture tissue specific effects, we developed a novel methodology for tissue specific pathway analysis of miRNAs. We incorporated the most recent and highest quality miRNA targeting data (TargetScan and StarBase), RNA-seq based gene expression data (EBI Expression Atlas) and multiple new pathway data sources to increase the biological relevance of the predicted miRNA-pathway associations. We identified new potential roles of miR-199a-3p, miR-199b-3p and the miR-200 family in hepatocellular carcinoma, involving the regulation of metastasis through MAPK and Wnt signaling. Also, an association of miR-571 and Notch signaling in liver fibrosis was proposed. To facilitate data update and future extensions of our tool, we developed a flexible database backend using the graph database neo4j. The new backend as well as the novel methodology were included in the updated miTALOS v2, a tool that provides insights into tissue specific miRNA regulation of biological pathways. miTALOS v2 is available at http://mips.helmholtz-muenchen.de/mitalos.

A Proposed Architecture for Query Anomaly Detection and Prevention against SQL Injection Attacks

SQL injection is a predominant type of attack which targets web applications and databases. SQL injection bypasses the authentication logic and breaks the confidentiality of the database or manipulates the database. It helps the attacker to obtain unauthorized access into the back end database. Vulnerability exists within a web application when it does not provide a proper validation system for the data entered by the user in the input field. Vulnerability scanners aid in checking vulnerabilities embedded in a web application and has the potential to test invalid forms of input query. However, the limitation lies in the reduction of system availability due to denial of service, especially in case of false positives. In this paper, an approach which focuses on query template based detection of SQL injection attack and reconstruction of queries is proposed. Thus the proposed architecture can mitigate the denial of service and increase the availability by potentially reconstructing malicious queries.

A Novel Method for SQL Injection Detection using Assocation Rule Mining (Sqlid-Arm) and Binary Transformation

SQL injection attacks are predominant on net databases since last fifteen years. Abusing input authentication defects, out breakers protect SQL code complete the front-end of internet sites and exceptional knowledge from the back-end databases. Detection of SQL injection attacks has been a tricky downside for the reason that of extreme no standardization of the attack vectors. Till now, most of the studies on SQLIA outcome have located on the structured query language arrangement at the appliance close. Inappropriately, this method inexorably fails to find those attacks that use previously holds on method and database among the database system. Prevailing SQLIA detectors proposal high uncovering accuracy however could have derelict another focuses on strength and accurateness. Our study has found that in the interior most systems existent numerous hot queries that present SQLIA detectors have repeatedly verified. Such recurrence causes terminated leftover of system resources. During this paper, we have a proposed method to suggest an outline SQLID-ARM at database level by persecution association rule mining, binary classification and SVM classification purposes. The key issue of SQL injection uncovering framework is the way to characterize the inner query tree composed from database log suitable for SVM classification algorithmic rule by means of the spatial relation live of protuberances to coach a Support Vector Machine, so as to accrue shrewd performance in perceiving SQL injections.

Dynamic Strategy Selection based on Evidence Theory. Application on a P2P-VoD system

Peer-to-Peer Video-on-Demand (VoD) systems are rising as a new dominant way to distribute video content over IP networks. While many works addressed the broad area of P2P communications, few work has been focused onto the resource allocation in P2P streaming systems, where the real-time constraint adds another dimension to the problem. Most work on P2P resource allocation solve the problem with static rules strategies are not robust when they are facing to the content demand (popularity) trends. In this paper, we use a dynamic approach, which automatically selects the best strategy on a given time period. With the proposed P2P resource allocation method, a VoD service provider can combine any number of resource allocation strategies and formulate different performance objectives that meet its requirements. As part of our effort to develop algorithms that can be effectively deployed by broadband operators, we developed a full-scale emulator for P2P streaming that can support up to 10,000 peers. The P2P streaming emulator includes a VoD request generators, along with a SuperNode (with backend DataBase) that tracks and allocates network resources. In this paper the goal is to use a low complexity learning approach to enhance the performance of a P2P-VoD system based on evidence theory. The proposed approach is compared to both static and dynamic solutions. The obtained results show that the proposed approach allows to reduce the complexity of selecting resource allocation strategies, while maintaining a low rejection rate.

Design of Electric Power Management System in Jilin Province based on SOA

Aiming at the problem of electric power data integration and sharing in Jilin Province, China, this paper proposed a method based on SOA which has high scalability, flexibility in strong power data and application integration. This approach establishes a web service-oriented system architecture, using SQL Server 2012 as its backend database and using C# as the programming language. And this approach has developed three kinds of terminal applications namely C/S(Client/Server), B/S(Browser /Server) and M/S(Mobile/Server). Client applications send all kinds of request to the electric power cloud computing centre, meanwhile web service components receive the requests and call corresponding functions to compute, and then return the results to the original app through the internet. The results show that system achieved the target we expected and successfully realized electric power information data integration, release and sharing.

A Web-Based Pilot Implementation of the Africanized Land Administration Domain Model for Kenya—A Case Study of Nyeri County

Kenya has amassed a wealth of paper based land information records collected over the duration of more than a century. The National Land Commission (NLC) having the mandate to develop a National Land Information Management System (NLIMS) for Kenya partnered with the Dedan Kimathi University of Technology on a project to develop a pilot LIMS for Nyeri County. A pilot Land Administration System (LAS) has been developed in this work and utilizes an Africanized Land Administration Domain Model (A-LADM) fitted to the Kenyan context. Various processes involved in land administration that required to be automated were identified. Informed by the numbers of applications made for the change of User service, it was picked as the first workflow to be automated. The key outputs of this work were the A-LADM and pilot LAS. The pilot solution uses a webcentric solution, with the data stored and managed centrally from a PostGIS database backend, using the Python Django framework to implement the server side and client side frontend. This solution demonstrates the importance of automating processes and supporting standards based software development. Stakeholder participation is key when implementing systems and 2 workshops are held to capture requirements and validate the developed solution.

Increasing Cross-Referral and Recruitment to Clinical Trials: A New Approach

Background/AimsThe Haematology Clinical Research Network of New South Wales & the Australian Capital Territory (HCRN NSW/ACT) comprises public hospital clinical trial unit managers committed to collaboration in the clinical research endeavour. In June 2013 we launched the ClinTrial Refer Application (App) on iTunes and Google play. This smart-phone and iPAD/Tablet tool provided clinicians, research staff and patients with instant knowledge of currently recruiting local haematology trials. It was associated with an immediate increase in inter-hospital cross referrals of patients to trials. Following this, the HCRN aimed to sustain and measure this increased referral and trials recruitment and to create a not-for-profit 'template App' that could be transferrable to other clinical trial portfolios.MethodsPatient cross-referral patterns, recruitment and staffing data were obtained from each of the 18 contributing hospitals in the HCRN from June 2013 to June 2015 and compared with prior to June 2013. Google analytics for the App were downloaded. We worked with research staff of other cancer networks to create modified versions of the App, establishing search functions unique to each network's geography and/or tumour stream. Newly derived Apps had to conform to the specifications of ClinTrial Refer, namely being publically available and free to download, simple to use and hosting only publically listed data of currently recruiting trials.ResultsWithin the HCRN there has been a sustained increase in cross referrals for clinical trials (median 1/month (range 0-6) to 9/month (0-18)) (Figure 1) and a state-wide >50% increase in recruitment from 300 to 460 from 2012 to 2014 and a 20% increase in unit staffing from 2013 to 2014. Google analytics usage metrics identify 3362 App users, over 24,703 sessions lasting an average 56 seconds. 19,907 of these sessions are in NSW where 91% of users are repeat users.Ten other state and national haematology or other tumour stream ClinTrial Refer Apps have been derived from the original App, from Sept 2013 to July 2015 (Figure 2). While maintaining the basic structure of an easy-to-navigate listing of currently recruiting trials, each new App has been re-designed to ensure relevance for the needs of each network. This ranged from a simple re-configuration of the logo, splash screen and recruiting locations for other Australian haematology Apps, to providing mutational status options for melanoma trials or age criteria for paediatric and adolescent- young adult Networks. The back-end database of listed trials, selection criteria and recruiting sites can be rapidly easily updated by local trial unit managers ensuring currency of trial information (est. 30 minutes/month in total). The "early adopters" within other cancer research networks have reported a similar upswing in trials recruitment and Google analytics for these newer Apps are similarly impressive. Recognising ClinTrial Refer as an effective tool for patients to identify recruiting trials close to home, cancer consumer groups have posted the Apps on their websites.ConclusionsAn instantly accessible, simple smartphone Application has provided better knowledge management of local clinical trials across the spectrum of rare haematologic malignancies. A tool to facilitate collaboration in clinical research, it has significantly enhanced cross-referral and recruitment rates, increasing patient access to emerging therapies and supporting the viability of haematology clinical trial units across Australia. ClinTrial Refer has been rapidly adapted to suit the trials portfolios of other clinical trial networks, both within and beyond cancer. [Display omitted] [Display omitted] DisclosuresNo relevant conflicts of interest to declare.

RFID mutual-authentication protocol with synchronous updated-keys based on Hash function

With the wide application of radio frequency identification (RFID) technology, its security privacy issues are becoming more and more prominent. A RFID mutual-authentication protocol with synchronous updated-keys based on Hash function is proposed to tackle those problems in this paper. An updated mechanism of the dynamic tag keys is introduced and a self-synchronized scheme is designed in the protocol, which has achieved the second verification for the tags. The security of the protocol is verified and analyzed by the Burrows-Abadi-Needham (BAN) logic and the attack models, moreover it has been compared with the existing schemes of security properties and its storage and computational performance. The results show that the proposed protocol has the ability to considerably reduce the amount of computation between tags and back-end database, and enhance the search efficiency of the whole system without the additional cost of the tags. It can satisfy safe requirements of RFID system effectively, also improve the authentication efficiency. The proposed protocol is more suitable for the low cost RFID system.

Evolution of the architecture of the ATLAS Metadata Interface (AMI)

The ATLAS Metadata Interface (AMI) is now a mature application. Over the years, the number of users and the number of provided functions has dramatically increased. It is necessary to adapt the hardware infrastructure in a seamless way so that the quality of service re - mains high. We describe the AMI evolution since its beginning being served by a single MySQL backend database server to the current state having a cluster of virtual machines at French Tier1, an Oracle database at Lyon with complementary replication to the Oracle DB at CERN and AMI back-up server.

R-memcached: A reliable in-memory cache for big key-value stores

Large-scale key-value stores are widely used in many Web-based systems to store huge amount of data as (key, value) pairs. In order to reduce the latency of accessing such (key, value) pairs, an in-memory cache system is usually deployed between the front-end Web system and the back-end database system. In practice, a cache system may consist of a number of server nodes, and fault tolerance is a critical feature to maintain the latency Service-Level Agreements (SLAs). In this paper, we present the design, implementation, analysis, and evaluation of R-Memcached, a reliable in-memory key-value cache system that is built on top of the popular Memcached software. R-Memcached exploits coding techniques to achieve reliability, and can tolerate up to two node failures. Our experimental results show that R-Memcached can maintain very good latency and throughput performance even during the period of node failures.

The ATLAS Software Installation System v2: a highly available system to install and validate Grid and Cloud sites via Panda

The ATLAS Installation System v2 is the evolution of the original system, used since 2003. The original tool has been completely re-designed in terms of database backend and components, adding support for submission to multiple backends, including the original Workload Management Service (WMS) and the new PanDA modules. The database engine has been changed from plain MySQL to Galera/Percona and the table structure has been optimized to allow a full High-Availability (HA) solution over Wide Area Network. The servlets, running on each frontend, have been also decoupled from local settings, to allow an easy scalability of the system, including the possibility of an HA system with multiple sites. The clients can also be run in multiple copies and in different geographical locations, and take care of sending the installation and validation jobs to the target Grid or Cloud sites. Moreover, the Installation Database is used as source of parameters by the automatic agents running in CVMFS, in order to install the software and distribute it to the sites. The system is in production for ATLAS since 2013, having as main sites in HA the INFN Roma Tier 2 and the CERN Agile Infrastructure. The Light Job Submission Framework for Installation (LJSFi) v2 engine is directly interfacing with PanDA for the Job Management, the Atlas Grid Information System (AGIS) for the site parameter configurations, and CVMFS for both core components and the installation of the software itself. LJSFi2 is also able to use other plugins, and is essentially Virtual Organization (VO) agnostic, so can be directly used and extended to cope with the requirements of any Grid or Cloud enabled VO. In this work we will present the architecture, performance, status and possible evolutions to the system for the LHC Run2 and beyond.

Re-engineering SAM or Changing the Engine in the Train While it is Running

In the last few years at Fermilab we re-architect-ed our SAM1[1] family of data catalog and file transfer tools - including major changes - while continuing to transfer over 1 Pb/month of data to multiple existing experiments and bring new experiments on board. This work was done with less than 3 FTE-years of effort, and the changes made include major ones, such as changing interprocess communication protocols, migrating database back-ends, removing and replacing major components, and supporting new file delivery methods. This paper will summarize the approaches we have used to do this, including using design patterns like the Facade, Adapter, and Command patterns, and assisting experiments one at a time with client migration. This process has allowed us to modernize our infrastructure with reasonable costs in both calendar time and developer effort, while continuing to provide the operating service to our customers with minimal interruptions.

Monte Carlo Production Management at CMS

The analysis of the LHC data at the Compact Muon Solenoid (CMS) experiment requires the production of a large number of simulated events. During the RunI of LHC (20102012), CMS has produced over 12 Billion simulated events, organized in approximately sixty different campaigns each emulating specific detector conditions and LHC running conditions (pile up). In order to aggregate the information needed for the configuration and prioritization of the events production, assure the book-keeping of all the processing requests placed by the physics analysis groups, and to interface with the CMS production infrastructure, the web- based service Monte Carlo Management (McM) has been developed and put in production in 2013. McM is based on recent server infrastructure technology (CherryPy + AngularJS) and relies on a CouchDB database back-end. This contribution covers the one and half year of operational experience managing samples of simulated events for CMS, the evolution of its functionalities and the extension of its capability to monitor the status and advancement of the events production.

Towards Monitoring-as-a-service for Scientific Computing Cloud applications using the ElasticSearch ecosystem

The INFN computing centre in Torino hosts a private Cloud, which is managed with the OpenNebula cloud controller. The infrastructure offers Infrastructure-as-a-Service (IaaS) and Platform-as-a-Service (PaaS) services to different scientific computing applications. The main stakeholders of the facility are a grid Tier-2 site for the ALICE collaboration at LHC, an interactive analysis facility for the same experiment and a grid Tier-2 site for the BESIII collaboration, plus an increasing number of other small tenants. The dynamic allocation of resources to tenants is partially automated. This feature requires detailed monitoring and accounting of the resource usage. We set up a monitoring framework to inspect the site activities both in terms of IaaS and applications running on the hosted virtual instances. For this purpose we used the ElasticSearch, Logstash and Kibana (ELK) stack. The infrastructure relies on a MySQL database back-end for data preservation and to ensure flexibility to choose a different monitoring solution if needed. The heterogeneous accounting information is transferred from the database to the ElasticSearch engine via a custom Logstash plugin. Each use-case is indexed separately in ElasticSearch and we setup a set of Kibana dashboards with pre-defined queries in order to monitor the relevant information in each case. For the IaaS metering, we developed sensors for the OpenNebula API. The IaaS level information gathered through the API is sent to the MySQL database through an ad-hoc developed RESTful web service. Moreover, we have developed a billing system for our private Cloud, which relies on the RabbitMQ message queue for asynchronous communication to the database and on the ELK stack for its graphical interface. The Italian Grid accounting framework is also migrating to a similar set-up. Concerning the application level, we used the Root plugin TProofMonSenderSQL to collect accounting data from the interactive analysis facility. The BESIII virtual instances used to be monitored with Zabbix, as a proof of concept we also retrieve the information contained in the Zabbix database. In this way we have achieved a uniform monitoring interface for both the IaaS and the scientific applications, mostly leveraging off-the-shelf tools. At present, we are working to define a model for monitoring-as-a-service, based on the tools described above, which the Cloud tenants can easily configure to suit their specific needs.

A methodology for modeling and monitoring of centrifugal casting process

Purpose – The purpose of this paper is to build a monitoring scheme in order to detect and subsequently eliminate abnormal behavior of the concerned casting process so as to produce worm wheels with good quality characteristics. Design/methodology/approach – In this a study, a process monitoring strategy has been devised for a centrifugal casting process using data-based multivariate statistical technique, namely, partial least squares regression (PLSR). Findings – Based on a case study, the PLSR model constructed for this study seems to mimic the actual process quite well which is evident from the various performance criteria (predicted and analysis of variance results). Practical implications – The practical implication of the study involves development of a software application with a back-end database which would be interfaced with a computer program based on PLSR algorithm for estimation of model parameters and the control limit for the monitoring chart. It would help in easy and real-time detection of faults. Originality/value – This study concerns the application of a PLSR-based monitoring strategy to a centrifugal casting process engaged in the production of worm wheel.