Recent research has focused on Continuous -Nearest Neighbor (CNN) query over moving objects in road networks. A CNN query is to find among all moving objects the -Nearest Neighbors (NNs) of a moving query point within a given time interval. As the data objects move frequently and arbitrarily in road networks, the frequent updates of object locations make it complicated to process CNN accurately and efficiently. In this paper, according to the relative moving situation between the moving objects and the query point, a Moving State of Object (MSO) model is presented to indicate the relative moving state of the object to the query point. With the help of this model, we propose a novel Object Candidate Processing (OCP) algorithm to highly reduce the repetitive query cost with pruning phase and refining phase. In the pruning phase, the data objects which cannot be the NN query results are excluded within the given time interval. In the refining phase, the time subintervals of the given time interval are determined where the certain NN query results are obtained. Comprehensive experiments are conducted and the results verify the effectiveness of the proposed methods.

TO-DCF, a new backoff scheme for 802.11, has the potential to significantly increase throughput in dense wireless LANs while also opportunistically favouring nodes with heavier traffic loads and/or better channel conditions. In this paper we present an analytical model to investigate the behaviour and performance of the TO-DCF protocol with regards to operating parameters such as the number of nodes, the contention window size and the backoff countdown probabilities. We then compare numerical results from an implementation of our model with simulations. Our model shows a high level of accuracy, even when the model assumptions are relaxed, and provides guidance for network operators to correctly configure the weight functions for nodes running TO-DCF given the network's operating conditions.

App collusion refers to two or more apps working together to achieve a malicious goal that they otherwise would not be able to achieve individually. The permissions based security model of Android does not address this threat as it is rather limited to mitigating risks of individual apps. This paper presents a technique for quantifying the collusion threat, essentially the first step towards assessing the collusion risk. The proposed method is useful in finding the collusion candidate of interest which is critical given the high volume of Android apps available. We present our empirical analysis using a classified corpus of over 29,000 Android apps provided by Intel Security.

In recent times, a phishing attack has become one of the most prominent attacks faced by internet users, governments, and service-providing organizations. In a phishing attack, the attacker(s) collects the client's sensitive data (i.e., user account login details, credit/debit card numbers, etc.) by using spoofed emails or fake websites. Phishing websites are common entry points of online social engineering attacks, including numerous frauds on the websites. In such types of attacks, the attacker(s) create website pages by copying the behavior of legitimate websites and sends URL(s) to the targeted victims through spam messages, texts, or social networking. To provide a thorough understanding of phishing attack(s), this paper provides a literature review of Artificial Intelligence (AI) techniques: Machine Learning, Deep Learning, Hybrid Learning, and Scenario-based techniques for phishing attack detection. This paper also presents the comparison of different studies detecting the phishing attack for each AI technique and examines the qualities and shortcomings of these methodologies. Furthermore, this paper provides a comprehensive set of current challenges of phishing attacks and future research direction in this domain.

Video streaming currently dominates global Internet traffic. Live streaming broadcasts events in real-time, with very different characteristics compared to video-on-demand (VoD), being more sensitive to variations in delay, jitter, and packet loss. The use of adaptive streaming techniques over HTTP is massively deployed on the Internet, adapting the video quality to instantaneous condition of the network. Dynamic Adaptive Streaming over HTTP (DASH) is the most popular adaptive streaming technology. In DASH, the client probes the network quality and adjusts the quality of requested video segment according to the bandwidth fluctuations. Therefore, DASH is an over-the-top application using unmanaged networks to distribute content in the best possible quality. In order to maintain a seamless playback, VoD applications commonly use a large reception buffer. However, in live streaming, the use of large buffers is not allowed because of the induced delay. Active Queue Management (AQM) arises as an alternative to control the congestion in router's queue, pressing the traffic sources to reduce their transmission rate when it detects incipient congestion. In this article, we evaluate the performance of recent AQM strategies for real-time adaptive video streaming. Furthermore, we propose a new AQM algorithm to improve the user-perceived video quality. The results show that the proposed method achieves better performance than competing AQM algorithms and improves the video quality in terms of average peak signal-to-noise ratio while keeping the fairness among concurrent flows.

With rapid advancements in the technology, almost all the devices around are becoming smart and contribute to the Internet of Things (IoT) network. When a new IoT device is added to the network, it is important to verify the authenticity of the device before allowing it to communicate with the network. Hence, access control is a crucial security mechanism that allows only the authenticated node to become the part of the network. An access control mechanism also supports confidentiality, by establishing a session key that accomplishes secure communications in open public channels. Recently, blockchain has been implemented in access control protocols to provide a better security mechanism. The foundation of this survey article is laid on IoT, where a detailed description on IoT, its architecture and applications is provided. Further, various security challenges and issues, security attacks possible in IoT and their countermeasures are also provided. We emphasize on the blockchain technology and its evolution in IoT. A detailed description on existing consensus mechanisms and how blockchain can be used to overpower IoT vulnerabilities is highlighted. Moreover, we provide a comprehensive description on access control protocols. The protocols are classified into certificate-based, certificate-less and blockchain-based access control mechanisms for better understanding. We then elaborate on each use case like smart home, smart grid, health care and smart agriculture while describing access control mechanisms. The detailed description not only explains the implementation of the access mechanism, but also gives a wider vision on IoT applications. Next, a rigorous comparative analysis is performed to showcase the efficiency of all protocols in terms of computation and communication costs. Finally, we discuss open research issues and challenges in a blockchain-envisioned IoT network.

Today's modern enterprises are adjusting to new realities of connectivity. As companies become more distributed and autonomous, emerging applications demand more bandwidth, low latency, more spectrum, and higher reliability. 5G technology can aid many industries or enterprises to make quicker and better business decisions. Private 5G networks, also called 5G Non-Public Networks (5G-NPN), is a 3GPP-based standalone 5G network positioned for a particular enterprise or use case that delivers dedicated network access. It sets to transform industry landscapes with networks capable of rapidly deploying modern use cases and the scalability to meet constantly increasing demands of data capacity and speed. They help generate more revenue for operators who can partner with enterprises to build and manage networks on-premise or in the cloud. The objective of this work is to offer a thorough summary of private 5G networks to assist academicians, researchers, and network developers to quickly grasp their functionalities without needing to go through the standards, specifications, or documentation. This paper discusses various key private 5G network design goals and requirements, examines its deployment scenarios, and explores spectrum considerations and security aspects. The paper presents several enterprise use cases to illuminate how the networks can deliver the demands and services expected by the industries. It also provides an overview of some of the open-source projects considered by various organizations for private network deployment. Finally, several research directions are introduced, emphasizing enterprise challenges to deploying 5G networks.

Recent years have seen an increasing need for higher broadband connections, fueled by novel applications including fifth generation wireless networks (5G). The European Commission is working on achieving specific milestones regarding the development of next generation networks. Many EU countries have opted to adopt a gradual migration path towards the Fiber-to-the-Home (FTTH) technology in view of the high costs of implementation. The Fiber-to-the-Cabinet (FTTC) architecture, combined with very-high-bit-rate digital subscriber line 2 (VDSL2) and vectoring noise cancellation techniques may therefore provide a viable short-term basis solution. Techno-economic modeling and assessment is vital at the initial stages of the development of a telecommunication network investment project involving high capital expenditures for the infrastructure. The present work provides a techno-economic model in order to assess the prospects of such a network upgrade project from a financial perspective, following a three-way migration path. The three stages are: the implementation of the FTTC architecture with VDSL2 vectoring technology, the upgrade to FTTC with G.Fast and finally the migration to FTTH. The analysis is implemented over a suburb of the city of Athens, Greece. Different scenarios are evaluated, predicting profits even from the first years following the investment. The analysis includes the estimation of the degree of market penetration, analytical cost calculations for the implementation and operation of the network and the evaluation of crucial financial indicators, regarding the prospects of the investment in vectoring services. The study can serve as a complete road-map and can be applied in similar upgrade scenarios. The most important outcome of the analysis is that the profits resulted from each upgrade will finance the next step.