An empirical recommendation framework to support location-based services

© 2020 by the authors. The rapid growth of Global Positioning System (GPS) and availability of real-time Geo-located data allow the mobile devices to provide information which leads towards the Location Based Services (LBS). The need for providing suggestions to personals about the activities of their interests, the LBS contributing more effectively to this purpose. Recommendation system (RS) is one of the most effective and efficient features that has been initiated by the LBS. Our proposed system is intended to design a recommendation system that will provide suggestions to the user and also find a suitable place for a group of users and it is according to their preferred type of places. In our work, we propose the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm for clustering the check-in spots of the user's and user-based Collaborative Filtering (CF) to find similar users as we are considering constructing an interest profile for each user. We also introduced a grid-based structure to present the Point of Interest (POI) into a map. Finally, similarity calculation is done to make the recommendations. We evaluated our system on real world users and acquired the F-measure score on average 0.962 and 0.964 for a single user and for a group of user respectively. We also observed that our system provides effective recommendations for a single user as well as for a group of users

A Service-Oriented Approach for Sensing in the Internet of Things: Intelligent Transportation Systems and Privacy Use Cases

This paper presents a Sensing-as-a-Service run-time Service Oriented Architecture (SOA), called 3SOA, for the development of Internet of Things (IoT) applications. 3SOA aims to allow interoperability among various IoT platforms and support service-oriented modelling at high levels of abstraction where fundamental SOA theories and techniques are fully integrated into a practical software engineering approach. 3SOA abstracts the dependencies of the middleware programming model from the application logic. This abstraction allows the development efforts to focus on writing the application logic independently from hardware platforms, middleware, and languages in which applications are programmed. To achieve this result, IoT objects are treated as independent entities that may interact with each other using a well-defined message exchange sequence. Each object is defined by the services it provides and the coordination protocol it supports. Objects are then able to coordinate their resources to address the global objectives of the system. To practically validate our proposals, we demonstrate an intelligent transportation system and data privacy functional prototypes as proof of concepts. The use cases show that 3SOA and the presented abstraction language allow the amalgamation of macroprogramming and node-centric programming to develop real-time and efficient applications over IoT

Network Traffic Analysis for Threats Detection in the Internet of Things

As the prevalence of the Internet of Things (IoT) continues to increase, cyber criminals are quick to exploit the security gaps that many devices are inherently designed with. Whilst users can not be expected to tackle this threat alone, many current solutions available for network monitoring are simply not accessible or can be difficult to implement for the average user and is a gap that needs to be addressed. This paper presents an effective signature-based solution to monitor, analyse and detect potentially malicious traffic for IoT ecosystems in the typical home network environment by utilising passive network sniffing techniques and a cloud-application to monitor anomalous activity. The proposed solution focuses on two attack and propagation vectors leveraged by the infamous Mirai botnet, namely DNS and Telnet. Experimental evaluation demonstrates the proposed solution can detect 98.35% of malicious DNS traffic and 99.33% of Telnet traffic respectively; for an overall detection accuracy of 98.84%

Control Plane Optimisation for an SDN-Based WBAN Framework to Support Healthcare Applications

Software-Defined Networking (SDN) offers an abstract view of the network and assists network operators to control the network traffic and the associated network resources more effectively. For the past few years, SDN has shown a lot of merits in diverse fields of applications, an important one being the Wireless Body Area Network (WBAN) for healthcare services. With the amalgamation of SDN with WBAN (SDWBAN), the patient monitoring and management system has gained much more flexibility and scalability compared to the conventional WBAN. However, the performance of the SDWBAN framework largely depends on the controller which is a core element of the control plane. The reason is that an optimal number of controllers assures the satisfactory level of performance and control of the network traffic originating from the underlying data plane devices. This paper proposes a mathematical model to determine the optimal number of controllers for the SDWBAN framework in healthcare applications. To achieve this goal, the proposed mathematical model adopts the convex optimization method and incorporates three critical SDWBAN factors in the design process: number of controllers, latency and number of SDN-enabled switches (SDESW). The proposed analytical model is validated by means of simulations in Castalia 3.2 and the outcomes indicate that the network achieves high level of Packet Delivery Ratio (PDR) and low latency for optimal number of controllers as derived in the mathematical model

Towards developing a framework to analyze the qualities of the university websites

The website of a university is considered to be a virtual gateway to provide primary resources to its stakeholders. It can play an indispensable role in disseminating information about a university to a variety of audience at a time. Thus, the quality of an academic website requires special attention to fulfil the users’ need. This paper presents a multi-method approach of quality assessment of the academic websites, in the context of universities of Bangladesh. We developed an automated web-based tool that can evaluate any academic website based on three criteria, which are as follows: content of information, loading time and overall performance. Content of information contains many sub criteria, such as university vision and mission, faculty information, notice board and so on. This tool can also perform comparative analysis among several academic websites and generate a ranked list of these. To the best of our knowledge, this is the very first initiative to develop an automated tool for accessing academic website quality in context of Bangladesh. Beside this, we have conducted a questionnaire-based statistical evaluation among several universities to obtain the respective users’ feedback about their academic websites. Then, a ranked list is generated based on the survey result that is almost similar to the ranked list got from the University ranking systems. This validates the effectiveness of our developed tool in accessing academic website

An effective hotel recommendation system through processing heterogeneous data

Recommendation systems have recently gained a lot of popularity in various industries such as entertainment and tourism. They can act as filters of information by providing relevant suggestions to the users through processing heterogeneous data from different networks. Many travelers and tourists routinely rely on textual reviews, numerical ratings, and points of interest to select hotels in cities worldwide. To attract more customers, online hotel booking systems typically rank their hotels based on the recommendations from their customers. In this paper, we present a framework that can rank hotels by analyzing hotels’ customer reviews and nearby amenities. In addition, a framework is presented that combines the scores generated from user reviews and surrounding facilities. We perform experiments using datasets from online hotel booking platforms such as TripAdvisor and Booking to evaluate the effectiveness and applicability of the proposed framework. We first store the keywords extracted from reviews and assign weights to each considered unigram and bigram keywords and, then, we give a numerical score to each considered keyword. Finally, our proposed system aggregates the scores generated from the reviews and surrounding environments from different categories of the facilities. Experimental results confirm the effectiveness of the proposed recommendation framework

Accessing Data from Multiple Sources Through Context-Aware Access Control

With the proliferation of cloud-based data and services, accessing data from distributed cloud environments and consequently providing integrated results to the users has become a key challenge, often involving large processing overheads and administrative costs. The traditional, spatial, temporal and other context-sensitive access control models have been applied in different environments in order to access such data and information. Recently, fog-based access control models have also been introduced to overcome the latency and processing issues by moving the execution of application logic from the cloud-level to an intermediary-level through adding computational nodes at the edges of the networks. These existing access control models mostly have been used to access data from centralized sources. However, we have been encountering rapid changes in computing technologies over the last few years, and many organizations need to dynamically control context-sensitive access to cloud data resources from distributed environments. In this article, we propose a new generation of fog-based access control approach, combining the benefits of fog computing and context-sensitive access control solutions. We first formally introduce a general data model and its associated policy and mapping models, in order to access data from distributed cloud sources and to provide integrated results to the users. In particular, we present a unified set of fog-based access control policies with the aim of reducing administrative burdens and processing overheads. We then introduce a unified data ontology together with its reasoning capability by realizing our formal approach. We demonstrate the applicability of our proposal through a prototype testing and several case studies. Experiment results demonstrate the good performance of our approach with respect to our earlier context-sensitive access control approach.Full Tex