Data Acquisition Network Research Articles

Fault Diagnosis in the Field of Additive Manufacturing (3D Printing) Using Bayesian Networks

In this work, a new approach for fault diagnosis in the field of additive manufacturing (3d printing) using artificial intelligence will be given. This approach is based on the marriage of the Bayesian Networks theory and data acquisition techniques. Bayesian Networks are well known for their ability to infer probabilities and to give decisional support under uncertainty. In order to do so, these probability engines must be constructed and maintained by a big amount of data and information using learning algorithms. This work provides a methodology that uses sensors based data acquisition and processing to construct such networks. Some of these sensors are already available in most of the 3d printers available in the market, while other sensors were additionally embedded in a studied 3d printer in order to enrich the number of observational variables to gain a high level of fault diagnosis accuracy and support.

A coverage-aware and energy-efficient protocol for the distributed wireless sensor networks

Wireless sensor network (WSNs) are composed of a large number of battery-powered wireless sensors, which acquire and monitor physical data from their surroundings through self-organization. The sensors are deployed randomly in a target area where maintenance and battery replacement are difficult or even impossible. To achieve better coverage and prolong network lifetime, networks typically adopt clustering protocols with hierarchical inter-cluster topology for network management and data acquisition in WSNs. However, typical solutions require cluster re-configuration due to early death of cluster heads (CHs) and cause energy inefficiency. This paper proposes a coverage- and energy-aware protocol with intra- and inter-cluster methods called CEMST that considers the sensor node density and coverage overlapping. In addition, to adapt network dynamics while improving energy efficiency, self-stabilizing algorithm and Borůvka algorithm are applied to construct the minimum spanning trees (MST) for intra- and inter-cluster routes, respectively. Simulation results indicate that CEMST produces the balanced clustering structures and provides better coverage and longer network lifetime than previous methods.

A Fuzzy AHP Approach for Security Risk Assessment in SCADA Networks

In this paper we propose a new method for security risk assessment in Supervisory Control and Data Acquisition (SCADA) networks. The method consists of the three phases, namely the obj ...

A Comprehensive Security Analysis of a SCADA Protocol: From OSINT to Mitigation

It is an established fact that the security of Industrial Automation and Control Systems (IACS) strongly depends on the robustness of the underlying supervisory control and data acquisition (SCADA) network protocols (among other factors). This becomes especially evident when considering the extent to which certain protocols, designed with poor or nonexistent security mechanisms, have led to a considerable number of past incident reports affecting critical infrastructures and essential services. Considering the current situation, it is rather obvious why the proper auditing and analysis of SCADA protocols are considered as key when it comes to design and/or protect IACS infrastructures. However, while the security of some protocols, such as Modbus or DNP3, has already been extensively analyzed, the same cannot be said for other protocols and technologies being used in the same domain that have not received the same amount of attention. In this paper, we provide a comprehensive security analysis of the PCOM SCADA protocol, including a dissection of PCOM, a demonstration of several attacks scenarios on PCOM-based systems, and also an analysis of possible mitigation strategies against these potential attacks. Moreover, this paper also describes a number of open-source tools that we developed for further analysis and research of PCOM security aspects, including a PCOM Wireshark dissector, a Nmap NSE PCOM scan, multiple Metasploit PCOM modules, a set of Snort PCOM rules, and several network traffic datasets containing multiple samples of different types of PCOM operations.

Study of the performance of prototypes of straw tube tracker by measuring cosmic rays

Straw tube detector developed for the PANDA experiment in [1], will be used for tracking and identifcation of charged particles in the Forward Tracker (FT). The detector read-out will be incorporated in PANDA DAQ running in trigger-less mode by means of Synchronization Of Data Acquisition Network (SODAnet). SODAnet is the protocol used to synchronize individual detector subsystems by providing a common clock signal and timestamps. The reconstruction of events out of many fragments is done with the Burst Building Network. The first tests of such system have been performed with prototypes of FT and ElectroMagnetic Calorimeter modules (EMC) in [1] measuring cosmic rays. Those tests allow to evaluate the detectors as well as the synchronization and processing systems. The reconstruction of particle tracks has been developed and evaluated. The results on the track reconstruction, spatial resolution and energy loss via Time over Threshold (TOT) method is described together with the DAQ performance.

A Reliability Comparison Method for OSINT Validity Analysis

Cyber-threat intelligence (CTI) is a knowledge-based threat management system that addresses increasing cyber threats. The CTI system creates reputation information for network resources such as IP, URL, and file hash-based on security data collected from security information and event management (SIEM) systems. This information can be applied extensively in industrial infrastructures to provide an effective response process for cyber attacks. This information can also be applied to the security systems of internal IT and OT infrastructures such as Internet objects (IoT) and Surveillance Control and Data Acquisition (SCADA) networks. However, because the performance of infrastructure security using CTI depends on the accuracy of the data on which the system is based, careful consideration of the accuracy of the data is required. In this paper, we propose a new model that can analyze the reliability and validity of data by using comparative analysis between CTI data and present a criterion for evaluating the reliability of feed providing CTI data. The experiment uses approximately 40 000 datasets to provide data accuracy results for four CTI feeds. These results can serve as a basis for substantive validation to use CTI data.

Development of a Non-Invasive On-Chip Interconnect Health Sensing Method Based on Bit Error Rates.

Electronic products and systems are widely used in industrial network systems, control devices, and data acquisition devices across many industry sectors. Failures of such electronic systems might lead to unexpected downtime, loss of productivity, additional work for repairs, and delay in product and service development. Thus, developing an appropriate sensing technique is necessary, because it is the first step in system fault diagnosis and prognosis. Many sensing techniques often require external and additional sensing devices, which might disturb system operation and consequently increase operating costs. In this study, we present an on-chip health sensing method for non-destructive and non-invasive interconnect degradation detection. Bit error rate (BER), which represents data integrity during digital signal transmission, was selected to sense interconnect health without connecting external sensing devices. To verify the health sensing performance, corrosion tests were conducted with in situ monitoring of the BER and direct current (DC) resistance. The eye size, extracted from the BER measurement, showed the highest separation between the intact and failed interconnect, as well as a gradual transition, compared with abrupt changes in the DC resistance, during interconnect degradation. These experimental results demonstrate the potential of the proposed sensing method for on-chip interconnect health monitoring applications without disturbing system operation.

Red de sensores inteligentes para adquisición de datos de una planta de desalinización de agua

Una red de sensores inalámbricos (en inglés Wireless Sensor Network, WSN) es un conjunto de nodos sensores y actuadores desplegados sobre la región de actuación. Los sistemas SCADA (Supervisión, Control y Adquisición de Datos) se aplican a la administración de la recolección de información de los procesos de controles industriales, tales como las redes eléctricas, redes de distribución de agua, transporte, etc. Los sistemas Multi-Agente (en inglés Multi-Agent System, MAS) aparecieron como un nuevo enfoque arquitectónico en aplicaciones de ingeniería complejas y altamente dinámicas. Además, los MAS pueden incluir agentes reactivos como Arduinos y agentes inteligentes tales como Redes Neuronales Artificiales, o Lógica Difusa. En este trabajo, se propone construir un sistema tipo SCADAflexible e interoperable, basado en la integración de protocolos de arquitecturas MAS. El sistema propuesto será implementado para administrar un sistema de adquisición de datos y control de operación de tipo SCADA, flexible e interoperable, basado en la integración delos protocolos de procesos MAS y Arduino para la adquisición de datos de una planta de desalinización de agua de mar, de tipo humidificación/des-humidificación, con capacidad de producir 0,1-0,5 m³/h de agua dulce. Particularmente en este trabajo se discute la red de sensores para adquisición de datos y detalles de implementación del mismo.

A multi-scale analysis of 27,000 urban street networks: Every US city, town, urbanized area, and Zillow neighborhood

OpenStreetMap offers a valuable source of worldwide geospatial data useful to urban researchers. This study uses the OSMnx software to automatically download and analyze 27,000 US street networks from OpenStreetMap at metropolitan, municipal, and neighborhood scales—namely, every US city and town, census urbanized area, and Zillow-defined neighborhood. It presents empirical findings on US urban form and street network characteristics, emphasizing measures relevant to graph theory, transportation, urban design, and morphology such as structure, connectedness, density, centrality, and resilience. In the past, street network data acquisition and processing have been challenging and ad hoc. This study illustrates the use of OSMnx and OpenStreetMap to consistently conduct street network analysis with extremely large sample sizes, with clearly defined network definitions and extents for reproducibility, and using nonplanar, directed graphs. These street networks and measures data have been shared in a public repository for other researchers to use.

Diurnal and Seasonal Variation of Surface Refractivity in Minna and Lapai, North Central Nigeria

Spatial and temporal variations of surface refractivity, Ns, in the troposphere are important parameters in designing terrestrial communication links. This research work examines the effect of variations of meteorological parameters on surface radio refractivity during dry and wet seasons in Minna and Lapai (2011-2013). The data on surface temperature, humidity and pressure collected from the Tropospheric Data Acquisition Network (TRODAN) weather stations installed at the Federal University of Technology, Minna, and at Ibrahim Badamasi Babangida University, Lapai, were used for the computation of radio refractivity. The hourly and monthly averages of radio refractivity during dry and wet seasons were calculated. The results showed that surface refractivity varied diurnally and seasonally in both stations. Refractivity values were high during the early morning and night hours and decreased rapidly during the afternoon hours. Values of refractivity were also generally low during the dry season months and high during the wet season months. It was also observed that refractivity values were higher at Lapai than Minna in dry season months. The result also shows that diurnal refractivity variation is attributed to atmospheric phenomena while seasonal variation is caused by the climatic conditions of the regions. Maximum values of 350 N-units in August in 2011, 343 N-units in July in 2012 and 347 N-units in August in 2013, while the minimum values of 275 N-units in January in 2011, 278 N-units in March in 2012 and 273 N-units were recorded in February for Minna. Surface refractivity has maximum values of 350 N-Units in August (2011), 347 N-Units in August (2012) and 349 N-Units in September (2013), while minimum values of 289 N-Units, 290 N-Units and 297 N-Units occurred in January in 2011, 2012 and 2013 respectively for Lapai.

Securing the operations in SCADA-IoT platform based industrial control system using ensemble of deep belief networks

Internet of Things (IoTs) platform is increasingly being used in modern industries. Billions of devices with smart sensing capabilities, PLCs, actuators, intelligent electronic devices (IEDs) of industrial control systems (ICS) and supervisory control and data acquisition (SCADA) network are connected over IoT platform. IoT platform has facilitated modern industries an efficient monitoring and controlling of physical systems (various hardware and machineries) resulting in an intelligent data acquisition, processing and highly productive and profitable management of business. Initially, these devices have been deployed without any security concern considering these will run in isolated networks. With the new IoT platform scenario, SCADA based ICS networks are integrated with the corporate networks over the internet. Therefore, the devices of a SCADA network are facing significant threat of malicious attacks either through the vulnerabilities of the corporate network or the devices used in the SCADA. Traditional IT security software products are not enough for ICS as these software products consider only operating system related calls and application program interface (API) behaviour of applications, which are only focused on corporate business solutions and related technologies. In this paper, we propose a secure architecture for ICS network that proposes a detection model based on SCADA network traffic. The proposed architecture develops two ensembles based detection algorithms using deep belief network (DBN) and standard classifier, including support vector machines (SVM). The novelty of the proposed architecture is that it uses network traffic feature and payload feature for detection model instead of conventional signature based or API based malware detection technique. In addition, ensemble-DBN of the proposed architecture can overcome many limitations of standard techniques, including the complexity and big size of the training data.The proposed architecture for ICS has been verified using a real SCADA network data. Experimental results show that our ensemble based detection system outperforms over existing attack detection engines.

Erroneous message discovery with data acquisition and secret communication in cellular networks

Cellular networks are susceptible to different varieties of security barrages, inclusive of erroneous message inoculation, message falsification and monitoring. Sensitivity knots can be adjudicate by invaders and the adjudicate knots can misinterpret message integrity by inoculating erroneous message. Erroneous message can be inoculated by adjudicate sensitivity knots in different measures, Inclusive of data acquisition and broadcasting. In a System the erroneous message exposure methods contemplate the erroneous message inoculations during the message promoting only. In an (SEP) symmetric en-route purifying schemes facilitates broadcasting knots and central terminal will expose erroneous message with a assertive possibility. In an interlaced step-by-step validation pattern Sensitivity knots are not granted to execute the data acquisition during message promoting. The Capricious Cipher based En-route purifying scheme (CCEP) nips erroneous message en-route without balanced key distribution. Message confidentiality means message to be enciphered at the origin knot and deciphered at the terminal. However, message acquisition methods usually need any enciphered sensitivity message to be deciphered at data acquisition. The essential idea at the rear of the erroneous message exposure algorithm is to make team of sensitivity knots in which one team operates a message authentication code (MAC) of promoting message and the alternate team afterwards checks the message using the MAC. Data acquisition is equipped in cellular sensitivity network in order to remove message repetition, minimize message communication, and increase message efficiency.

A Hierarchical IoT Federation Architecture Based on Local Cloud, Platform and Middleware for Massive Context Data Acquisition in Multiple Sensor Networks

A Hierarchical IoT Federation Architecture Based on Local Cloud, Platform and Middleware for Massive Context Data Acquisition in Multiple Sensor Networks

Research on data fusion algorithm and anti-collision algorithm based on internet of things

Internet of Things is involved in all aspects of human life, work, health and social areas, which will have a significant impact on the future development of the global economic society. Perception and recognition technology is the basis of the Internet of things, and data fusion and anti-collision technology are the sensor network and radio frequency identification research focus. This paper focuses on the key technology of the sensing layer of the internet of things, that is, the data fusion of the sensor network and the multi-label anti-collision technology of the radio frequency identification system, which mainly includes the following work. This paper introduces the hierarchical architecture of the internet of things and its key technologies, and introduces the sensing and recognition technology of the internet of things, and expatiates the data fusion model and routing algorithm of the sensor network and the working principle and anti-collision problem of the RFID system. The improved clustering routing protocol Leach based on distributed data fusion effectively prolongs the lifetime of the sensor network. A data fusion algorithm based on Gauss membership function has introduced, and the fusion technology and routing technology have combined to process the data, which improves the efficiency and accuracy of data acquisition in Sensor Networks. An efficient binary search anti-collision algorithm called AEBS, with unknown tag number estimation, which has proposed to recognize unknown tags in the range of reader’s function. Theoretical analysis and experimental simulation results show that the AEBS algorithm improves the efficiency and stability of the system identification and reduces the recognition time of the whole system.

Moving Target Defense for Securing SCADA Communications

In this paper, we introduce a framework for building a secure and private peer to peer communication used in supervisory control and data acquisition networks with a novel Mobile IPv6-based moving target defense strategy. Our approach aids in combating remote cyber-attacks against peer hosts by thwarting any potential attacks at their reconnaissance stage. The IP address of each host is randomly changed at a certain interval creating a moving target to make it difficult for an attacker to find the host. At the same time, the peer host is updated through the use of the binding update procedure (standard Mobile IPv6 protocol). Compared with existing results that can incur significant packet-loss during address rotations, the proposed solution is loss-less. Improving privacy and anonymity for communicating hosts by removing permanent IP addresses from all packets is also one of the major contributions of this paper. Another contribution is preventing black hole attacks and bandwidth depletion DDoS attacks through the use of extra paths between the peer hosts. Recovering the communication after rebooting a host is also a new contribution of this paper. Lab-based simulation results are presented to demonstrate the performance of the method in action, including its overheads. The testbed experiments show zero packet-loss rate during handoff delay.

Design of Data Acquisition System Based on Zigbee for Wireless Sensor Networks

With the continuous development of modern network technology, sensor technology and wireless communication technologies, the emergence and development of wireless sensor networks has been promoted. Among many wireless communication technologies, wireless communication technology featuring low power consumption, close proximity and low cost for ZigBee has attracted the research interest of researchers. Based on the current status of communication systems, based on the review and system analysis of wireless sensor networks, this paper proposes a ZigBee-based wireless sensor network data acquisition system, which avoids the reliability and installation of traditional wired sensor network data acquisition systems and shortcomings such as high maintenance costs and large wiring.

Neural Models for Imputation of Missing Ozone Data in Air-Quality Datasets

Ozone is one of the pollutants with most negative effects on human health and in general on the biosphere. Many data-acquisition networks collect data about ozone values in both urban and background areas. Usually, these data are incomplete or corrupt and the imputation of the missing values is a priority in order to obtain complete datasets, solving the uncertainty and vagueness of existing problems to manage complexity. In the present paper, multiple-regression techniques and Artificial Neural Network models are applied to approximate the absent ozone values from five explanatory variables containing air-quality information. To compare the different imputation methods, real-life data from six data-acquisition stations from the region of Castilla y León (Spain) are gathered in different ways and then analyzed. The results obtained in the estimation of the missing values by applying these techniques and models are compared, analyzing the possible causes of the given response.

Research on Crowdsourcing Emergency Information Extraction of Based on Events' Frame

At present, the common information extraction method cannot extract the structured emergency event information accurately; the general information retrieval tool cannot completely identify the emergency geographic information; these ways also do not have an accurate assessment of these results of distilling. So, this paper proposes an emergency information collection technology based on event framework. This technique is to solve the problem of emergency information picking. It mainly includes emergency information extraction model (EIEM), complete address recognition method (CARM) and the accuracy evaluation model of emergency information (AEMEI). EIEM can be structured to extract emergency information and complements the lack of network data acquisition in emergency mapping. CARM uses a hierarchical model and the shortest path algorithm and allows the toponomy pieces to be joined as a full address. AEMEI analyzes the results of the emergency event and summarizes the advantages and disadvantages of the event framework. Experiments show that event frame technology can solve the problem of emergency information drawing and provides reference cases for other applications. When the emergency disaster is about to occur, the relevant departments query emergency's data that has occurred in the past. They can make arrangements ahead of schedule which defense and reducing disaster. The technology decreases the number of casualties and property damage in the country and world. This is of great significance to the state and society.

RapidIO as a multi-purpose interconnect

RapidIO (http://rapidio.org/) technology is a packet-switched high-performance fabric, which has been under active development since 1997. Originally meant to be a front side bus, it developed into a system level interconnect which is today used in all 4G/LTE base stations world wide. RapidIO is often used in embedded systems that require high reliability, low latency and scalability in a heterogeneous environment - features that are highly interesting for several use cases, such as data analytics and data acquisition (DAQ) networks. We will present the results of evaluating RapidIO in a data analytics environment, from setup to benchmark. Specifically, we will share the experience of running ROOT and Hadoop on top of RapidIO. To demonstrate the multi-purpose characteristics of RapidIO, we will also present the results of investigating RapidIO as a technology for high-speed DAQ networks using a generic multi-protocol event-building emulation tool. In addition we will present lessons learned from implementing native ports of CERN applications to RapidIO.

Exploring RapidIO Technology Within a DAQ System Event Building Network

RapidIO ( http://rapidio.org/ ) technology is a packet-switched high-performance fabric, which has been under active development since 1997. The technology is used in all 4G/LTE base stations worldwide. RapidIO is also used in embedded systems that require high reliability, low latency, and deterministic operations in a heterogeneous environment. RapidIO has several offloading features in hardware, therefore relieving the CPUs from time- and power-consuming work. Most importantly, it allows for remote direct memory access and thus zero-copy data transfer. In addition, it lends itself readily to integration with field-programmable gate arrays. In this paper, we investigate RapidIO as a technology for high-speed data acquisition (DAQ) networks, in particular the DAQ system of an LHC experiment. We present measurements using a generic multiprotocol event-building emulation tool that was developed for the LHCb experiment. Event building using a local area network, such as the one foreseen for the future LHCb DAQ, puts heavy requirements on the underlying network as all data sources from the collider will want to send to the same destinations at the same time. This may lead to an instantaneous overcommitment of the output buffers of the switches. We will present results from implementing an event building cluster based on RapidIO interconnect, focusing on the bandwidth capabilities of the technology as well as its scalability.