A Knowledge Mining Approach for Effective Customer Relationship Management

The problem of existing customer relationship management (CRM) system is not lack of information but the ability to differentiate useful information from chatter or even disinformation and also maximize the richness of these heterogeneous information sources. This paper describes an improved text mining approach for automatically extracting association rules from collections of textual documents. It discovers association rules from keyword features extracted from the documents. The main contributions of the technique are that, in selecting the most discriminative keywords for use in association rules generation, the system combines syntactic and semantic relevance into its Information Retrieval Scheme which is integrated with XML technology. Experiments carried out revealed that the extracted association rules contain important features which form a worthy platform for making effective decisions as regards customer relationship management. The performance of the improved text mining approach is compared with existing system that uses the GARW algorithm to reveal a significant reduction in the large itemsets, leading to reduction in rules generated to more interesting ones due to the semantic analysis component being introduced. Also, it has brought about reduction of the execution time, compared to the GARW algorithm.</p

Mobile Ad-Hoc Networks

Being infrastructure-less and without central administration control, wireless ad-hoc networking is playing a more and more important role in extending the coverage of traditional wireless infrastructure (cellular networks, wireless LAN, etc). This book includes state-of the-art techniques and solutions for wireless ad-hoc networks. It focuses on the following topics in ad-hoc networks: vehicular ad-hoc networks, security and caching, TCP in ad-hoc networks and emerging applications. It is targeted to provide network engineers and researchers with design guidelines for large scale wireless ad hoc networks

Secure information sharing on Decentralized Social Networks.

Decentralized Social Networks (DSNs) are web-based platforms built on distributed systems (federations) composed of multiple providers (pods) that run the same social networking service. DSNs have been presented as a valid alternative to Online Social Networks (OSNs), replacing the centralized paradigm of OSNs with a decentralized distribution of the features o\u21b5ered by the social networking platform. Similarly to commercial OSNs, DSNs o\u21b5er to their subscribed users a number of distinctive features, such as the possibility to share resources with other subscribed users or the possibility to establish virtual relationships with other DSN users. On the other hand, each DSN user takes part in the service, choosing to store personal data on his/her own trusted provider inside the federation or to deploy his/her own provider on a private machine. This, thus, gives each DSN user direct control of his/hers data and prevents the social network provider from performing data mining analysis over these information. Unfortunately, the deployment of a personal DSN pod is not as simple as it sounds. Indeed, each pod\u2019s owner has to maintain the security, integrity, and reliability of all the data stored in that provider. Furthermore, given the amount of data produced each day in a social network service, it is reasonable to assume that the majority of users cannot a\u21b5ord the upkeep of an hardware capable of handling such amount of information. As a result, it has been shown that most of DSN users prefer to subscribe to an existing provider despite setting up a new one, bringing to an indirect centralization of data that leads DSNs to su\u21b5er of the same issues as centralized social network services. In order to overcome this issue in this thesis we have investigated the possibility for DSN providers to lean on modern cloud-based storage services so as to o\u21b5er a cloudbased information sharing service. This has required to deal with many challenges. As such, we have investigated the definition of cryptographic protocols enabling DSN users to securely store their resources in the public cloud, along with the definition of communication protocols ensuring that decryption keys are distributed only to authorized users, that is users that satisfy at least one of the access control policies specified by data owner according to Relationship-based access control model (RelBAC) [20, 34]. In addition, it has emerged that even DSN users have the same difficulties as OSN users in defining RelBAC rules that properly express their attitude towards their own privacy. Indeed, it is nowadays well accepted that the definition of access control policies is an error-prone task. Then, since misconfigured RelBAC policies may lead to harmful data release and may expose the privacy of others as well, we believe that DSN users should be assisted in the RelBAC policy definition process. At this purpose, we have designed a RelBAC policy recommendation system such that it can learn from DSN users their own attitude towards privacy, and exploits all the learned data to assist DSN users in the definition of RelBAC policies by suggesting customized privacy rules. Nevertheless, despite the presence of the above mentioned policy recommender, it is reasonable to assume that misconfigured RelBAC rules may appear in the system. However, rather than considering all misconfigured policies as leading to potentially harmful situations, we have considered that they might even lead to an exacerbated data restriction that brings to a loss of utility to DSN users. As an example, assuming that a low resolution and an high resolution version of the same picture are uploaded in the network, we believe that the low-res version should be granted to all those users who are granted to access the hi-res version, even though, due to a misconfiurated system, no policy explicitly authorizes them on the low-res picture. As such, we have designed a technique capable of exploiting all the existing data dependencies (i.e., any correlation between data) as a mean for increasing the system utility, that is, the number of queries that can be safely answered. Then, we have defined a query rewriting technique capable of extending defined access control policy authorizations by exploiting data dependencies, in order to authorize unauthorized but inferable data. In this thesis we present a complete description of the above mentioned proposals, along with the experimental results of the tests that have been carried out so as to verify the feasibility of the presented techniques

Secure information sharing on Decentralized Social Networks.

Decentralized Social Networks (DSNs) are web-based platforms built on distributed systems (federations) composed of multiple providers (pods) that run the same social networking service. DSNs have been presented as a valid alternative to Online Social Networks (OSNs), replacing the centralized paradigm of OSNs with a decentralized distribution of the features o↵ered by the social networking platform. Similarly to commercial OSNs, DSNs o↵er to their subscribed users a number of distinctive features, such as the possibility to share resources with other subscribed users or the possibility to establish virtual relationships with other DSN users. On the other hand, each DSN user takes part in the service, choosing to store personal data on his/her own trusted provider inside the federation or to deploy his/her own provider on a private machine. This, thus, gives each DSN user direct control of his/hers data and prevents the social network provider from performing data mining analysis over these information. Unfortunately, the deployment of a personal DSN pod is not as simple as it sounds. Indeed, each pod’s owner has to maintain the security, integrity, and reliability of all the data stored in that provider. Furthermore, given the amount of data produced each day in a social network service, it is reasonable to assume that the majority of users cannot a↵ord the upkeep of an hardware capable of handling such amount of information. As a result, it has been shown that most of DSN users prefer to subscribe to an existing provider despite setting up a new one, bringing to an indirect centralization of data that leads DSNs to su↵er of the same issues as centralized social network services. In order to overcome this issue in this thesis we have investigated the possibility for DSN providers to lean on modern cloud-based storage services so as to o↵er a cloudbased information sharing service. This has required to deal with many challenges. As such, we have investigated the definition of cryptographic protocols enabling DSN users to securely store their resources in the public cloud, along with the definition of communication protocols ensuring that decryption keys are distributed only to authorized users, that is users that satisfy at least one of the access control policies specified by data owner according to Relationship-based access control model (RelBAC) [20, 34]. In addition, it has emerged that even DSN users have the same difficulties as OSN users in defining RelBAC rules that properly express their attitude towards their own privacy. Indeed, it is nowadays well accepted that the definition of access control policies is an error-prone task. Then, since misconfigured RelBAC policies may lead to harmful data release and may expose the privacy of others as well, we believe that DSN users should be assisted in the RelBAC policy definition process. At this purpose, we have designed a RelBAC policy recommendation system such that it can learn from DSN users their own attitude towards privacy, and exploits all the learned data to assist DSN users in the definition of RelBAC policies by suggesting customized privacy rules. Nevertheless, despite the presence of the above mentioned policy recommender, it is reasonable to assume that misconfigured RelBAC rules may appear in the system. However, rather than considering all misconfigured policies as leading to potentially harmful situations, we have considered that they might even lead to an exacerbated data restriction that brings to a loss of utility to DSN users. As an example, assuming that a low resolution and an high resolution version of the same picture are uploaded in the network, we believe that the low-res version should be granted to all those users who are granted to access the hi-res version, even though, due to a misconfiurated system, no policy explicitly authorizes them on the low-res picture. As such, we have designed a technique capable of exploiting all the existing data dependencies (i.e., any correlation between data) as a mean for increasing the system utility, that is, the number of queries that can be safely answered. Then, we have defined a query rewriting technique capable of extending defined access control policy authorizations by exploiting data dependencies, in order to authorize unauthorized but inferable data. In this thesis we present a complete description of the above mentioned proposals, along with the experimental results of the tests that have been carried out so as to verify the feasibility of the presented techniques

Internet of Things Applications - From Research and Innovation to Market Deployment

The book aims to provide a broad overview of various topics of Internet of Things from the research, innovation and development priorities to enabling technologies, nanoelectronics, cyber physical systems, architecture, interoperability and industrial applications. It is intended to be a standalone book in a series that covers the Internet of Things activities of the IERC – Internet of Things European Research Cluster from technology to international cooperation and the global "state of play".The book builds on the ideas put forward by the European research Cluster on the Internet of Things Strategic Research Agenda and presents global views and state of the art results on the challenges facing the research, development and deployment of IoT at the global level. Internet of Things is creating a revolutionary new paradigm, with opportunities in every industry from Health Care, Pharmaceuticals, Food and Beverage, Agriculture, Computer, Electronics Telecommunications, Automotive, Aeronautics, Transportation Energy and Retail to apply the massive potential of the IoT to achieving real-world solutions. The beneficiaries will include as well semiconductor companies, device and product companies, infrastructure software companies, application software companies, consulting companies, telecommunication and cloud service providers. IoT will create new revenues annually for these stakeholders, and potentially create substantial market share shakeups due to increased technology competition. The IoT will fuel technology innovation by creating the means for machines to communicate many different types of information with one another while contributing in the increased value of information created by the number of interconnections among things and the transformation of the processed information into knowledge shared into the Internet of Everything. The success of IoT depends strongly on enabling technology development, market acceptance and standardization, which provides interoperability, compatibility, reliability, and effective operations on a global scale. The connected devices are part of ecosystems connecting people, processes, data, and things which are communicating in the cloud using the increased storage and computing power and pushing for standardization of communication and metadata. In this context security, privacy, safety, trust have to be address by the product manufacturers through the life cycle of their products from design to the support processes. The IoT developments address the whole IoT spectrum - from devices at the edge to cloud and datacentres on the backend and everything in between, through ecosystems are created by industry, research and application stakeholders that enable real-world use cases to accelerate the Internet of Things and establish open interoperability standards and common architectures for IoT solutions. Enabling technologies such as nanoelectronics, sensors/actuators, cyber-physical systems, intelligent device management, smart gateways, telematics, smart network infrastructure, cloud computing and software technologies will create new products, new services, new interfaces by creating smart environments and smart spaces with applications ranging from Smart Cities, smart transport, buildings, energy, grid, to smart health and life. Technical topics discussed in the book include: • Introduction• Internet of Things Strategic Research and Innovation Agenda• Internet of Things in the industrial context: Time for deployment.• Integration of heterogeneous smart objects, applications and services• Evolution from device to semantic and business interoperability• Software define and virtualization of network resources• Innovation through interoperability and standardisation when everything is connected anytime at anyplace• Dynamic context-aware scalable and trust-based IoT Security, Privacy framework• Federated Cloud service management and the Internet of Things• Internet of Things Application

Privacidade em comunicações de dados para ambientes contextualizados

Doutoramento em InformáticaInternet users consume online targeted advertising based on information collected about them and voluntarily share personal information in social networks. Sensor information and data from smart-phones is collected and used by applications, sometimes in unclear ways. As it happens today with smartphones, in the near future sensors will be shipped in all types of connected devices, enabling ubiquitous information gathering from the physical environment, enabling the vision of Ambient Intelligence. The value of gathered data, if not obvious, can be harnessed through data mining techniques and put to use by enabling personalized and tailored services as well as business intelligence practices, fueling the digital economy. However, the ever-expanding information gathering and use undermines the privacy conceptions of the past. Natural social practices of managing privacy in daily relations are overridden by socially-awkward communication tools, service providers struggle with security issues resulting in harmful data leaks, governments use mass surveillance techniques, the incentives of the digital economy threaten consumer privacy, and the advancement of consumergrade data-gathering technology enables new inter-personal abuses. A wide range of fields attempts to address technology-related privacy problems, however they vary immensely in terms of assumptions, scope and approach. Privacy of future use cases is typically handled vertically, instead of building upon previous work that can be re-contextualized, while current privacy problems are typically addressed per type in a more focused way. Because significant effort was required to make sense of the relations and structure of privacy-related work, this thesis attempts to transmit a structured view of it. It is multi-disciplinary - from cryptography to economics, including distributed systems and information theory - and addresses privacy issues of different natures. As existing work is framed and discussed, the contributions to the state-of-theart done in the scope of this thesis are presented. The contributions add to five distinct areas: 1) identity in distributed systems; 2) future context-aware services; 3) event-based context management; 4) low-latency information flow control; 5) high-dimensional dataset anonymity. Finally, having laid out such landscape of the privacy-preserving work, the current and future privacy challenges are discussed, considering not only technical but also socio-economic perspectives.Quem usa a Internet vê publicidade direccionada com base nos seus hábitos de navegação, e provavelmente partilha voluntariamente informação pessoal em redes sociais. A informação disponível nos novos telemóveis é amplamente acedida e utilizada por aplicações móveis, por vezes sem razões claras para isso. Tal como acontece hoje com os telemóveis, no futuro muitos tipos de dispositivos elecónicos incluirão sensores que permitirão captar dados do ambiente, possibilitando o surgimento de ambientes inteligentes. O valor dos dados captados, se não for óbvio, pode ser derivado através de técnicas de análise de dados e usado para fornecer serviços personalizados e definir estratégias de negócio, fomentando a economia digital. No entanto estas práticas de recolha de informação criam novas questões de privacidade. As práticas naturais de relações inter-pessoais são dificultadas por novos meios de comunicação que não as contemplam, os problemas de segurança de informação sucedem-se, os estados vigiam os seus cidadãos, a economia digital leva á monitorização dos consumidores, e as capacidades de captação e gravação dos novos dispositivos eletrónicos podem ser usadas abusivamente pelos próprios utilizadores contra outras pessoas. Um grande número de áreas científicas focam problemas de privacidade relacionados com tecnologia, no entanto fazem-no de maneiras diferentes e assumindo pontos de partida distintos. A privacidade de novos cenários é tipicamente tratada verticalmente, em vez de re-contextualizar trabalho existente, enquanto os problemas actuais são tratados de uma forma mais focada. Devido a este fraccionamento no trabalho existente, um exercício muito relevante foi a sua estruturação no âmbito desta tese. O trabalho identificado é multi-disciplinar - da criptografia à economia, incluindo sistemas distribuídos e teoria da informação - e trata de problemas de privacidade de naturezas diferentes. À medida que o trabalho existente é apresentado, as contribuições feitas por esta tese são discutidas. Estas enquadram-se em cinco áreas distintas: 1) identidade em sistemas distribuídos; 2) serviços contextualizados; 3) gestão orientada a eventos de informação de contexto; 4) controlo de fluxo de informação com latência baixa; 5) bases de dados de recomendação anónimas. Tendo descrito o trabalho existente em privacidade, os desafios actuais e futuros da privacidade são discutidos considerando também perspectivas socio-económicas

Combining SOA and BPM Technologies for Cross-System Process Automation

This paper summarizes the results of an industry case study that introduced a cross-system business process automation solution based on a combination of SOA and BPM standard technologies (i.e., BPMN, BPEL, WSDL). Besides discussing major weaknesses of the existing, custom-built, solution and comparing them against experiences with the developed prototype, the paper presents a course of action for transforming the current solution into the proposed solution. This includes a general approach, consisting of four distinct steps, as well as specific action items that are to be performed for every step. The discussion also covers language and tool support and challenges arising from the transformation

An RFM Model Customizable to Product Catalogues and Marketing Criteria Using Fuzzy Linguistic Models: Case Study of a Retail Business

In the field of strategic marketing, the recency, frequency and monetary (RFM) variables model has been applied for years to determine how solid a database is in terms of spending and customer activity. Retailers almost never obtain data related to their customers beyond their purchase history, and if they do, the information is often out of date. This work presents a new method, based on the fuzzy linguistic 2-tuple model and the definition of product hierarchies, which provides a linguistic interpretability giving business meaning and improving the precision of conventional models. The fuzzy linguistic 2-tuple RFM model, adapted by the product hierarchy thanks to the analytical hierarchical process (AHP), is revealed to be a useful tool for including business criteria, product catalogues and customer insights in the definition of commercial strategies. The result of our method is a complete customer segmentation that enriches the clusters obtained with the traditional fuzzy linguistic 2-tuple RFM model and offers a clear view of customers’ preferences and possible actions to define cross- and up-selling strategies. A real case study based on a worldwide leader in home decoration was developed to guide, step by step, other researchers and marketers. The model was built using the only information that retailers always have: customers’ purchase ticket details

The User Attribution Problem and the Challenge of Persistent Surveillance of User Activity in Complex Networks

In the context of telecommunication networks, the user attribution problem refers to the challenge faced in recognizing communication traffic as belonging to a given user when information needed to identify the user is missing. This is analogous to trying to recognize a nameless face in a crowd. This problem worsens as users move across many mobile networks (complex networks) owned and operated by different providers. The traditional approach of using the source IP address, which indicates where a packet comes from, does not work when used to identify mobile users. Recent efforts to address this problem by exclusively relying on web browsing behavior to identify users were limited to a small number of users (28 and 100 users). This was due to the inability of solutions to link up multiple user sessions together when they rely exclusively on the web sites visited by the user. This study has tackled this problem by utilizing behavior based identification while accounting for time and the sequential order of web visits by a user. Hierarchical Temporal Memories (HTM) were used to classify historical navigational patterns for different users. Each layer of an HTM contains variable order Markov chains of connected nodes which represent clusters of web sites visited in time order by the user (user sessions). HTM layers enable inference generalization by linking Markov chains within and across layers and thus allow matching longer sequences of visited web sites (multiple user sessions). This approach enables linking multiple user sessions together without the need for a tracking identifier such as the source IP address. Results are promising. HTMs can provide high levels of accuracy using synthetic data with 99% recall accuracy for up to 500 users and good levels of recall accuracy of 95 % and 87% for 5 and 10 users respectively when using cellular network data. This research confirmed that the presence of long tail web sites (rarely visited) among many repeated destinations can create unique differentiation. What was not anticipated prior to this research was the very high degree of repetitiveness of some web destinations found in real network data