A Detailed Study on Aggregation Methods used in Natural Language Interface to Databases (NLIDB)

Historically, databases have been the most crucial issue in the study of information systems, and they constitute an essential part of all information management systems. Since, it complicated due to restricting the number of potential users, particularly non-expert database users who must comprehend the database structure to submit such queries. Natural language interface (NLI), the simplest method to retrieve information, is one possibility for interacting with the database. The transformation of a natural language query into a Structured Query (SQL) in a database is known as a "Natural Language Interface to Database" (NLIDB). This study uses NLIDB to handle the works performed under various aggregations with aggregation functions, a grouping phrase, and a possessing clause. This study carefully examines the numerous systematic aggregation approaches utilized in the NLIDB. This review provides extensive information about the many methods, including query-based, pattern-based, general, keyword-based NLIDB, and grammar-based systems, to extract data for a dissertation from a generic module for use in such systems that support query execution utilizing aggregations

Secure and Privacy-Preserving Data Aggregation Protocols for Wireless Sensor Networks

This chapter discusses the need of security and privacy protection mechanisms in aggregation protocols used in wireless sensor networks (WSN). It presents a comprehensive state of the art discussion on the various privacy protection mechanisms used in WSNs and particularly focuses on the CPDA protocols proposed by He et al. (INFOCOM 2007). It identifies a security vulnerability in the CPDA protocol and proposes a mechanism to plug that vulnerability. To demonstrate the need of security in aggregation process, the chapter further presents various threats in WSN aggregation mechanisms. A large number of existing protocols for secure aggregation in WSN are discussed briefly and a protocol is proposed for secure aggregation which can detect false data injected by malicious nodes in a WSN. The performance of the protocol is also presented. The chapter concludes while highlighting some future directions of research in secure data aggregation in WSNs.Comment: 32 pages, 7 figures, 3 table

Secure Data Aggregation in Wireless Sensor Networks. Homomorphism versus Watermarking Approach

International audienceWireless sensor networks are now in widespread use to monitor regions, detect events and acquire information. Since the deployed nodes are separated, they need to cooperatively communicate sensed data to the base station. Hence, transmissions are a very energy consuming operation. To reduce the amount of sending data, an aggregation approach can be applied along the path from sensors to the sink. However, usually the carried information contains confidential data. Therefore, an end-to-end secure aggregation approach is required to ensure a healthy data reception. End-to-end encryption schemes that support operations over cypher-text have been proved important for private party sensor network implementations. These schemes offer two main advantages: end-to-end concealment of data and ability to operate on cipher text, then no more decryption is required for aggregation. Unfortunately, nowadays these methods are very complex and not suitable for sensor nodes having limited resources. In this paper, we propose a secure end-to-end encrypted-data aggregation scheme. It is based on elliptic curve cryptography that exploits a smaller key size. Additionally, it allows the use of higher number of operations on cypher-texts and prevents the distinction between two identical texts from their cryptograms. These properties permit to our approach to achieve higher security levels than existing cryptosystems in sensor networks. Our experiments show that our proposed secure aggregation method significantly reduces computation and communication overhead and can be practically implemented in on-the-shelf sensor platforms. By using homomorphic encryption on elliptic curves, we thus have realized an efficient and secure data aggregation in sensor networks. Lastly, to enlarge the aggregation functions that can be used in a secure wireless sensor network, a watermarking-based authentication scheme is finally proposed

Security protocols suite for machine-to-machine systems

Nowadays, the great diffusion of advanced devices, such as smart-phones, has shown that there is a growing trend to rely on new technologies to generate and/or support progress; the society is clearly ready to trust on next-generation communication systems to face today’s concerns on economic and social fields. The reason for this sociological change is represented by the fact that the technologies have been open to all users, even if the latter do not necessarily have a specific knowledge in this field, and therefore the introduction of new user-friendly applications has now appeared as a business opportunity and a key factor to increase the general cohesion among all citizens. Within the actors of this technological evolution, wireless machine-to-machine (M2M) networks are becoming of great importance. These wireless networks are made up of interconnected low-power devices that are able to provide a great variety of services with little or even no user intervention. Examples of these services can be fleet management, fire detection, utilities consumption (water and energy distribution, etc.) or patients monitoring. However, since any arising technology goes together with its security threats, which have to be faced, further studies are necessary to secure wireless M2M technology. In this context, main threats are those related to attacks to the services availability and to the privacy of both the subscribers’ and the services providers’ data. Taking into account the often limited resources of the M2M devices at the hardware level, ensuring the availability and privacy requirements in the range of M2M applications while minimizing the waste of valuable resources is even more challenging. Based on the above facts, this Ph. D. thesis is aimed at providing efficient security solutions for wireless M2M networks that effectively reduce energy consumption of the network while not affecting the overall security services of the system. With this goal, we first propose a coherent taxonomy of M2M network that allows us to identify which security topics deserve special attention and which entities or specific services are particularly threatened. Second, we define an efficient, secure-data aggregation scheme that is able to increase the network lifetime by optimizing the energy consumption of the devices. Third, we propose a novel physical authenticator or frame checker that minimizes the communication costs in wireless channels and that successfully faces exhaustion attacks. Fourth, we study specific aspects of typical key management schemes to provide a novel protocol which ensures the distribution of secret keys for all the cryptographic methods used in this system. Fifth, we describe the collaboration with the WAVE2M community in order to define a proper frame format actually able to support the necessary security services, including the ones that we have already proposed; WAVE2M was funded to promote the global use of an emerging wireless communication technology for ultra-low and long-range services. And finally sixth, we provide with an accurate analysis of privacy solutions that actually fit M2M-networks services’ requirements. All the analyses along this thesis are corroborated by simulations that confirm significant improvements in terms of efficiency while supporting the necessary security requirements for M2M networks

Algorithms for Energy Efficiency in Wireless Sensor Networks

The recent advances in microsensor and semiconductor technology have opened a new field within computer science: the networking of small-sized sensors which are capable of sensing, processing, and communicating. Such wireless sensor networks offer new applications in the areas of habitat and environment monitoring, disaster control and operation, military and intelligence control, object tracking, video surveillance, traffic control, as well as in health care and home automation. It is likely that the deployed sensors will be battery-powered, which will limit the energy capacity significantly. Thus, energy efficiency becomes one of the main challenges that need to be taken into account, and the design of energy-efficient algorithms is a major contribution of this thesis. As the wireless communication in the network is one of the main energy consumers, we first consider in detail the characteristics of wireless communication. By using the embedded sensor board (ESB) platform recently developed by the Free University of Berlin, we analyze the means of forward error correction and propose an appropriate resync mechanism, which improves the communication between two ESB nodes substantially. Afterwards, we focus on the forwarding of data packets through the network. We present the algorithms energy-efficient forwarding (EEF), lifetime-efficient forwarding (LEF), and energy-efficient aggregation forwarding (EEAF). While EEF is designed to maximize the number of data bytes delivered per energy unit, LEF additionally takes into account the residual energy of forwarding nodes. In so doing, LEF further prolongs the lifetime of the network. Energy savings due to data aggregation and in-network processing are exploited by EEAF. Besides single-link forwarding, in which data packets are sent to only one forwarding node, we also study the impact of multi-link forwarding, which exploits the broadcast characteristics of the wireless medium by sending packets to several (potential) forwarding nodes. By actively selecting a forwarder among all nodes that received a packet successfully, retransmissions can often be avoided. In the majority of cases, multi-link forwarding is thus more efficient and able to save energy. In the last part of this thesis, we present a topology and energy control algorithm (TECA) to turn off the nodes' radio transceivers completely in order to avoid idle listening. By means of TECA, a connected backbone of active nodes is established, while all other nodes may sleep and save energy by turning off their radios. All algorithms presented in this thesis have been fully analyzed, simulated, and implemented on the ESB platform. They are suitable for several applications scenarios and can easily be adapted even to other wireless sensor platforms

Distributed heterogeneous web data sources integration DeXIN approach

Zsfassung in dt. SpracheIn modernen Wirtschaftsunternehmen wird häufig eine integrierte Anwendung entwickelt, um einheitlichen Zugriff auf mehrere bestehende Informationssysteme zu bieten, die innerhalb oder außerhalb des Unternehmens laufen. Datenintegration ist eine tiefgreifende Herausforderung dieser Anwendungen, da Abfragen über mehrere autonome und heterogene Datenquellen reichen.Die Integration solch unterschiedlicher Informationssysteme ist eine anspruchsvolle Aufgabe, insbesondere wenn verschiedene Anwendungen unterschiedliche Datenformate und Abfragesprachen verwenden, die nicht untereinander kompatibel sind.Mit der wachsenden Popularität von Web 2.0-Technologien und der Verfügbarkeit riesiger Mengen an Daten im Web, haben sich die Anforderungen für die Datenintegration, im Vergleich zu traditionellen Ansätzen der Datenbankintegration, geändert. Der große Umfang an Web-Datenquellen hat nicht nur zu einem hohen Maß an Verteilung, Heterogenität, sowie unterschiedlichen Datenformaten und Abfragesprachen geführt, sondern darüber hinaus sind die Daten auch mit zusätzlichen Dateneigenschaften verbunden, wie zum Beispiel Datenschutz, Lizenzierung, Kosten, Qualität der Daten, etc. Daher müssen die Datenintegration-Tools nicht nur einen optimalen Weg zur Verfügung stellen, um die Heterogenität der Datenformate und Abfragesprachen zu reduzieren, sondern darüber hinaus sollten auch die verschiedenen zusätzlichen Dateneigenschaften beibehalten werden, wenn die Daten veröffentlicht oder genutzt werden.Weiters sollte die Auswahl der Datendienste und die Selektion der Daten diese Dateneigenschaften berücksichtigen.Das Ziel dieser Dissertation ist es, bessere Mittel bereitzustellen zur einfachen und dynamischen Integration von verteilten heterogenen Web-Datenquellen (insbesondere XML und RDFDatenquellen), in einer Weise, die es dem Benutzer vereinfachen, Datenintegrationsapplikationen zu erstellen, während gleichzeitig alle Dateneigenschaften mit den damit verbundenen Daten sichergestellt werden.Das Hauptthema dieser Arbeit ist der verteilten heterogenen Datenintegration für Web- Datenquellen gewidmet. Um die Herausforderung der XML und RDF-Datenintegration zu bewältigen, schlagen wir "DeXIN (Distributed extended XQuery for heterogeneous Data Integration)", ein erweiterbares Framework für die verteilte Verarbeitung von Abfragen über heterogene, verteilte und autonome Datenquellen vor. DeXIN verwendet ein Datenformat als Grundlage (das sogenannte "aggregation model") und erweitert die entsprechende Abfragesprache, um Abfragen über heterogene Datenquellen in ihren jeweiligen Abfragesprachen durchzuführen. Wir stellen eine Erweiterung von XQuery vor, welche die volle SPARQL Sprache abdeckt und die dezentrale Ausführung von XQuery als auch SPARQL in einer einzigen Abfrage unterstützt.Für die Sicherstellung der Dateneigenschaften, die mit den veröffentlichten Daten im Web verbunden sind, führen wir ein "Data Concerns Aware Query System" ein.Dieses System vereinigt mehrere Dateneigenschaften in eine Abfragesprache, wodurch es DatenserviceIntegrationssystemen erlaubt wird, Dateneigenschaften, die mit den Datendiensten verbunden sind, zu behandeln.Unser "Data Concerns Aware Query System" erweitert die XQuery-Sprache, um Dateneigenschaften zu berücksichten. Dafür werden spezielle Schlüsselwörter eingeführt, um Dateneigenschaften innerhalb der Abfrage auszudrücken.Im letzten Teil dieser Arbeit entwerfen wir ein Mashup-Tool, welches auf DeXIN aufbaut.Wir präsentieren eine Abfrage-basierte Aggregation von mehreren heterogenen Datenquellen durch die Kombination von vielseitigen Abfrage-Features von XQuery und SPARQL mit einer intuitiven Benutzerschnittstelle eines Mashup-Tools für Datenquellen in XML und RDF. Unser Mashup-Editor ermöglicht die automatische Generierung von Mashups mit einer einfach zu bedienenden visuellen Schnittstelle. Wir nutzen das Konzept der Daten-Mashups, um dynamisch heterogene Web-Datenquellen zu integrieren, indem wir die in DeXIN vorgeschlagene Erweiterung von XQuery benutzen.In modern business enterprises, it is frequent to develop an integrated application to provide uniform access to multiple existing information systems running internally or externally of the enterprise.Data integration is a pervasive challenge faced in these applications that need to query across multiple autonomous and heterogeneous data sources. Integrating such diverse information systems becomes a challenging task particularly when different applications use different data formats and query languages which are not compatible with each other.With the growing popularity of web technologies and availability of the huge amount of data on the web, the requirements for data integration has changed from the traditional database integration approaches. The large scale of web data sources has not only led to high levels of distribution, heterogeneity, different data formats and query languages.Additionally, the data is also associated with data concerns like privacy, licensing, pricing, quality of data, etc. Hence, the data integration tools not only have to provide the optimal solution to mitigate the heterogeneity in data formats and query languages. In addition, also the various data concerns should be preserved when data is published and utilized. Moreover, data service selection and data selection should be based on these data concerns.The goal of this thesis is to provide better means to easily and dynamically integrate distributed heterogeneous web data sources (particularly XML and RDF data sources) in such a way that the user can easily build data integration applications while assuring all the data concerns associated with the data.The main topic of this work is devoted to the distributed heterogeneous data integration for web data sources. In order to deal with the challenge of XML and RDF data integration, we propose "DeXIN (Distributed extended XQuery for heterogeneous data INtegration)", an extensible framework for distributed query processing over heterogeneous, distributed and autonomous data sources. DeXIN considers one data format as the basis (the so-called "aggregation model") and extends the corresponding query language to executing queries over heterogeneous data sources in their respective query languages. We come up with an extension of XQuery which covers the full SPARQL language and supports the decentralized execution of both XQuery and SPARQL in a single query.For the assurance of the data concerns associated with the published data over the web, we introduce a "Data Concerns Aware Querying System".A data concerns aware querying system incorporates several data concerns into a query language, thus enabling data services integration systems to handle data concerns associated with the data services. Our concerns aware querying system extends the XQuery language to make it concerns aware, with the introduction of special keywords for mentioning data concerns within the query.In the last part of this thesis, we design a mashup tool on top of DeXIN. We propose a query based aggregation of multiple heterogeneous data sources by combining powerful querying features of XQuery and SPARQL with an easy interface of a mashup tool for data sources in XML and RDF. Our mashup editor allows for automatic generation of mashups with an easy to use visual interface. For the dynamic integration of heterogeneous web data sources we utilize the concept of data mashups, which uses the extension of XQuery proposed in DeXIN.10