Search results for: network security techniques

Authors: Amir Farouk Ahmed Ali Hussin

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Social media, such as Facebook, LinkedIn and Ex-Twitter have experienced exponential growth and a remarkable adoption rate in recent years. They give fantastic means of online social interactions and communications with family, friends, and colleagues from around the corner or across the globe, and they have become an important part of daily digital interactions for more than one and a half billion users around the world. The personal information sharing practices that social network providers encourage have led to their success as innovative social interaction platforms. Moreover, these practices have outcome in concerns with respect to privacy and security from different stakeholders. Guiding these privacy and security concerns in social networks is a must for these networks to be sustainable. Real security and privacy tools may not be enough to address existing concerns. Some points should be followed to protect users from the existing risks. In this research, we have checked the various privacy and security issues and concerns pertaining to social media. However, we have classified these privacy and security issues and presented a thorough discussion of the effects of these issues and concerns on the future of the social networks. In addition, we have presented a set of points as precaution measures that users can consider to address these issues.

Keywords: international legal, consultation mix, legal research, small and medium-sized enterprises, strategic International law, strategy alignment, house of laws, deployment, production strategy, legal strategy, business strategy

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Authors: G. M. Hamada, A. A. Al-Gathe, A. M. Al-Khudafi

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Determination of water saturation in sandstone is a vital question to determine the initial oil or gas in place in reservoir rocks. Water saturation determination using electrical measurements is mainly on Archie’s formula. Consequently accuracy of Archie’s formula parameters affects water saturation values rigorously. Determination of Archie’s parameters a, m, and n is proceeded by three conventional techniques, Core Archie-Parameter Estimation (CAPE) and 3-D. This work introduces the hybrid system of parallel self-organizing neural network (PSONN) targeting accepted values of Archie’s parameters and, consequently, reliable water saturation values. This work focuses on Archie’s parameters determination techniques; conventional technique, CAPE technique, and 3-D technique, and then the calculation of water saturation using current. Using the same data, a hybrid parallel self-organizing neural network (PSONN) algorithm is used to estimate Archie’s parameters and predict water saturation. Results have shown that estimated Arche’s parameters m, a, and n are highly accepted with statistical analysis, indicating that the PSONN model has a lower statistical error and higher correlation coefficient. This study was conducted using a high number of measurement points for 144 core plugs from a sandstone reservoir. PSONN algorithm can provide reliable water saturation values, and it can supplement or even replace the conventional techniques to determine Archie’s parameters and thereby calculate water saturation profiles.

Keywords: water saturation, Archie’s parameters, artificial intelligence, PSONN, sandstone reservoir

Procedia PDF Downloads 123

Authors: Wiriranai Brilliant Masara

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The African Peace and Security Architecture is widely celebrated and revered as a paragon of the will to address peace and security challenges in Africa. However, like any other institution, it is embedded with operational and institutional challenges that prevent it from effectively carrying out its mandate and turning goals into achieved results. The article examines the fundamental flaws and weaknesses of the African Peace and Security Architecture by focusing on its institutions, norms, instruments, and its relationship to Africa’s Regional Economic Communities. Therefore, the article reviews the flaws of the five elements of the African Peace and Security Architecture which are the Peace and Security Council, Panel of the Wise, Continental Early Warning System, African Standby Force, and Peace Fund.

Keywords: African Union, African Peace and Security Architecture, peace and security council, continental early warning system, African Standby Force, Panel of the Wise, Peace Fund

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Authors: Mehmet Hakan Karaata

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In this paper, we first coin a new graph theocratic problem with numerous applications. Second, we provide two algorithms for the problem. The first solution is using a brute-force techniques, whereas the second solution is based on an initial identification of the cycles in the given graph. We then provide a correctness proof of the algorithm. The applications of the problem include graph analysis, graph drawing and network structuring.

Keywords: algorithm, cycle, graph algorithm, graph theory, network structuring

Procedia PDF Downloads 378

Authors: Mokrane Selma

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The shift towards decision making (DM) based on artificial intelligence (AI) techniques will change the way in which consumer markets and our societies function. Through AI, predictive analytics is being used by businesses to identify these patterns and major trends with the objective to improve the DM and influence future business outcomes. This paper proposes an Artificial Neural Network (ANN) approach to predict the success of telemarketing calls for selling bank long-term deposits. To validate the proposed model, we uses the bank marketing data of 41188 phone calls. The ANN attains 98.93% of accuracy which outperforms other conventional classifiers and confirms that it is credible and valuable approach for telemarketing campaign managers.

Keywords: bank telemarketing, prediction, decision making, artificial intelligence, artificial neural network

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Authors: Ammarah Irum, Muhammad Ali Tahir

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Document-level sentiment analysis in Urdu is a challenging Natural Language Processing (NLP) task due to the difficulty of working with lengthy texts in a language with constrained resources. Deep learning models, which are complex neural network architectures, are well-suited to text-based applications in addition to data formats like audio, image, and video. To investigate the potential of deep learning for Urdu sentiment analysis, we implemented five different deep learning models, including Bidirectional Long Short Term Memory (BiLSTM), Convolutional Neural Network (CNN), Convolutional Neural Network with Bidirectional Long Short Term Memory (CNN-BiLSTM), and Bidirectional Encoder Representation from Transformer (BERT). In this study, we developed a hybrid deep learning model called BiLSTM-Single Layer Multi Filter Convolutional Neural Network (BiLSTM-SLMFCNN) by fusing BiLSTM and CNN architecture. The proposed and baseline techniques are applied on Urdu Customer Support data set and IMDB Urdu movie review data set by using pre-trained Urdu word embedding that are suitable for sentiment analysis at the document level. Results of these techniques are evaluated and our proposed model outperforms all other deep learning techniques for Urdu sentiment analysis. BiLSTM-SLMFCNN outperformed the baseline deep learning models and achieved 83%, 79%, 83% and 94% accuracy on small, medium and large sized IMDB Urdu movie review data set and Urdu Customer Support data set respectively.

Keywords: urdu sentiment analysis, deep learning, natural language processing, opinion mining, low-resource language

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Authors: Dicky R. Munaf, Ayu Bulan Tisna

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Competitive intelligence (business intelligence) is the process of observing the external environment which often conducted by many organizations to get the relevant information which will be used to create the organization policy, whereas, security intelligence is related to the function of the officers who have the duties to protect the country and its people from every criminal actions that might harm the national and individual security. Therefore, the intelligence dimension of maritime security is associated with all the intelligence activities including the subject and the object that connected to the maritime issues. The concept of intelligence business regarding the maritime security perspective is the efforts to protect the maritime security using the analysis of economic movements as the basic strategic plan. Clearly, a weak maritime security will cause high operational cost to all the economic activities which uses the sea as its media. Thus, it affects the competitiveness of a country compared to the other countries that are able to maintain the maritime law enforcement and secure their marine territory. So, the intelligence business within the security intelligence is important to conduct as the beginning process of the identification against the opponent strategy that might happen in the present or in the future. Thereby, the scenario of the potential impact of all the illegal maritime activities, as well as the strategy in preventing the opponent maneuver can be made.

Keywords: competitive intelligence, maritime security intelligence, intelligent systems, information technology

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Authors: Gabriel A. Orozco

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The purpose of this article is to make an approach to the Security Studies, exposing their theories and concepts to understand the role that have had in the interpretation of the changes and continuities of the world order and their impact on policies or decision-making facing the problems of the 21st century. The aim is to build a bridge between the security studies as a subfield and the meaning that has been given to the world order. The idea of epistemic communities serves as a methodological proposal about the different programs of research in security studies, showing their influence in the realities of States, intergovernmental organizations and transnational forces, moving to implement, perpetuate and project a vision of the world order.

Keywords: security studies, epistemic communities, international, relations

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Authors: Phuong Nguyen, Trung Tran

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Along with the global ongoing energy transition, Vietnam has indicated a strong commitment in the last COP events on the zero-carbon emission target. However, it is a real challenge for the nation to replace fossil-fired power plants by a significant amount of renewable energy sources (RES) while maintaining security of supply. The unpredictability and variability of RES would cause technical issues for supply-demand balancing, network congestions, system balancing, among others. It is crucial to take these into account while planning the future grid infrastructure. This study will address both generation and transmission adequacy and reveal a comprehensive analysis about the impact of ongoing energy transition on the development of Vietnam power system in 2030. This will provide insight for creating an secure, stable, and affordable pathway for the country in upcoming years.

Keywords: generation adequacy, transmission adequacy, security of supply, energy transition

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Authors: Ahmed Jedidi, Mesfer Mohammed Alshamrani, Alwi Mohammad A. Bamhdi

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Optical performance monitoring and optical network management are essential in building a reliable, high-capacity, and service-differentiation enabled all-optical network. One of the serious problems in this network is the fact that optical crosstalk is additive, and thus the aggregate effect of crosstalk over a whole AON may be more nefarious than a single point of crosstalk. As results, we note a huge degradation of the Quality of Service (QoS) in our network. For that, it is necessary to identify and monitor the impairments in whole network. In this way, this paper presents new system to identify and monitor crosstalk in AONs in real-time fashion. particular, it proposes a new technique to manage intra-crosstalk in objective to relax QoS of the network.

Keywords: all-optical networks, optical crosstalk, optical cross-connect, crosstalk, monitoring crosstalk

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Authors: Feng-jie Xie, Jian-hong Yan

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Based on the complex network theory, we construct the air cargo network of the Belt and Road area, analyze its regional distribution and structural characteristics, measure the robustness of the network. The regional distribution results show that Southeast Asia and China have the most prominent development in the air cargo network of the Belt and Road area, Central Asia is the least developed. The structure characteristics found that the air cargo network has obvious small-world characteristics; the degree distribution has single-scale property; it shows a significant rich-club phenomenon simultaneously. The network robustness is measured by two attack strategies of degree and betweenness, but the betweenness of network nodes has a greater impact on network connectivity. And identified 24 key cities that have a large impact on the robustness of the network under the two attack strategies. Based on these results, recommendations are given to maintain the air cargo network connectivity in the Belt and Road area.

Keywords: air cargo, complex network, robustness, structure properties, The Belt and Road

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Authors: Trupti Chavan, Ramachandra Guda, Kameshwar Rao

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The lack of data is a pain problem in medical image analysis using a convolutional neural network (CNN). This work uses various spatial transformation techniques to address the medical image augmentation issue for knee detection and localization using an enhanced single shot detector (SSD) network. The spatial transforms like a negative, histogram equalization, power law, sharpening, averaging, gaussian blurring, etc. help to generate more samples, serve as pre-processing methods, and highlight the features of interest. The experimentation is done on the OpenKnee dataset which is a collection of knee images from the openly available online sources. The CNN called enhanced single shot detector (SSD) is utilized for the detection and localization of the knee joint from a given X-ray image. It is an enhanced version of the famous SSD network and is modified in such a way that it will reduce the number of prediction boxes at the output side. It consists of a classification network (VGGNET) and an auxiliary detection network. The performance is measured in mean average precision (mAP), and 99.96% mAP is achieved using the proposed enhanced SSD with spatial transformations. It is also seen that the localization boundary is comparatively more refined and closer to the ground truth in spatial augmentation and gives better detection and localization of knee joints.

Keywords: data augmentation, enhanced SSD, knee detection and localization, medical image analysis, openKnee, Spatial transformations

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Authors: Po-Jen Chen, Jian-Jiun Ding, Hung-Wei Hsu, Chien-Yao Wang, Jia-Ching Wang

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A more accurate scene classification algorithm using label relations and the hierarchy neural network was developed in this work. In many classification algorithms, it is assumed that the labels are mutually exclusive. This assumption is true in some specific problems, however, for scene classification, the assumption is not reasonable. Because there are a variety of objects with a photo image, it is more practical to assign multiple labels for an image. In this paper, two label relations, which are exclusive relation and hierarchical relation, were adopted in the classification process to achieve more accurate multiple label classification results. Moreover, the hierarchy neural network (hierarchy NN) is applied to classify the image and the directed acyclic graph structure is used for predicting a more reasonable result which obey exclusive and hierarchical relations. Simulations show that, with these techniques, a much more accurate scene classification result can be achieved.

Keywords: convolutional neural network, label relation, hierarchy neural network, scene classification

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Authors: Hossain Samani, Mohammad Ehteram

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In this paper, we consider finite volume method (FVM) in water hammer. We will simulate these techniques on a looped network with complex boundary conditions. After comparing methods, we see the FVM method as the best method. We compare the results of FVM with experimental data. Finite volume using staggered grid is applied for solving water hammer equations.

Keywords: hydraulic transient, water hammer, interpolation, non-liner interpolation

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Authors: Loh Fu Quan, Fong Zi Heng, Burra Venkata Durga Kumar

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Cloud computing has completely transformed the way many businesses operate. Traditionally, confidential data of a business is stored in computers located within the premise of the business. Therefore, a lot of business capital is put towards maintaining computing resources and hiring IT teams to manage them. The advent of cloud computing changes everything. Instead of purchasing and managing their infrastructure, many businesses have started to shift towards working with the cloud with the help of a cloud service provider (CSP), leading to cost savings. However, it also introduces security risks. This research paper focuses on the security risks that arise during data migration and user authentication in cloud computing. To overcome this problem, this paper provides a comprehensive framework that includes Transport Layer Security (TLS), user authentication, security tokens and multi-level data encryption. This framework aims to prevent authorized access to cloud resources and data leakage, ensuring the confidentiality of sensitive information. This framework can be used by cloud service providers to strengthen the security of their cloud and instil confidence in their users.

Keywords: Cloud computing, Cloud security, Cloud security issues, Cloud security framework

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Authors: Jin Xu

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5G network developers need to satisfy the necessary requirements of additional capacity from massive users and spectrally efficient wireless technologies. Therefore, the significant amount of underutilized spectrum in network is motivating operators to combine long-term evolution (LTE) with intelligent spectrum management technology. This new LTE intelligent spectrum management in unlicensed band (LTE-U) has the physical layer topology to access spectrum, specifically the 5-GHz band. We proposed a new intelligent cloud RAN for 5G.

Keywords: cloud radio access network, wireless network, cloud computing, multi-agent

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Authors: Margarita Mayoral-Villa, J. Klapp, L. Di G. Sigalotti, J. E. V. Guzmán

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Automated learning techniques are widely applied in the energy sector to address challenging problems from a practical point of view. To this end, we discuss the implementation of a Message Passing algorithm (MPNN)within a Graph Neural Network(GNN)to leverage the neighborhood of a set of nodes during the aggregation process. This approach enables the characterization of multiphase diffusion processes in the reservoir, such that the flow paths underlying the interconnections between multiple wells may be inferred from previously available data on flow rates and bottomhole pressures. The results thus obtained compare favorably with the predictions produced by the Reduced Order Capacitance-Resistance Models (CRM) and suggest the potential of MPNNs to enhance the robustness of the forecasts while improving the computational efficiency.

Keywords: multiphase diffusion, message passing neural network, well interconnection, interwell connectivity, graph neural network, capacitance-resistance models

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Authors: Kevin Krupski

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Private Military Security Companies have grown to become a major force contributor to nations in military operations. Scholars have debated the implications of this in relation to control and efficiency related to the privatization of violence, but there has been little discussion on how these companies affect the profession of arms. Specifically, this paper seeks to address how the privatization of violence influences the military’s stewardship, whether private military security companies are capable of stewardship of the military profession, and whether there are aspects of stewardship of the military profession that private military security companies are capable of emulating. This paper reviews literature on stewardship, the relationship of the military to the state, and private military security companies in order to identify overlap between uniformed military services and the private sector. Then, it offers a typology for determining under what conditions an organization would act as a steward. Ultimately, there are insufficient reasons for private military security companies to act as stewards of the profession of arms.

Keywords: stewardship, military profession, civil-military, security

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Authors: V. Andal Priyadharshini, Anumalasetty Yashwanth Nath

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Network automation has evolved into a solution that ensures efficiency in all areas. The age-old technique to configure common software-defined networking protocols is inefficient as it requires a box-by-box approach that needs to be repeated often and is prone to manual errors. Network automation assists network administrators in automating and verifying the protocol configuration to ensure consistent configurations. This paper implemented network automation using Python and Ansible to configure different protocols and configurations in the container lab virtual environment. Ansible can help network administrators minimize human mistakes, reduce time consumption, and enable device visibility across the network environment.

Keywords: Python network automation, Ansible configuration, container lab deployment, software-defined networking, networking lab

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Authors: Taha Benarbia

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The advent of automated and connected vehicles has revolutionized the transportation industry, presenting new opportunities for enhancing the efficiency, safety, and sustainability of our transportation networks. This paper explores the integration of automated and connected vehicles into a smart transportation framework, leveraging the power of deep learning techniques to optimize the overall network performance. The first aspect addressed in this paper is the deployment of automated vehicles (AVs) within the transportation system. AVs offer numerous advantages, such as reduced congestion, improved fuel efficiency, and increased safety through advanced sensing and decisionmaking capabilities. The paper delves into the technical aspects of AVs, including their perception, planning, and control systems, highlighting the role of deep learning algorithms in enabling intelligent and reliable AV operations. Furthermore, the paper investigates the potential of connected vehicles (CVs) in creating a seamless communication network between vehicles, infrastructure, and traffic management systems. By harnessing real-time data exchange, CVs enable proactive traffic management, adaptive signal control, and effective route planning. Deep learning techniques play a pivotal role in extracting meaningful insights from the vast amount of data generated by CVs, empowering transportation authorities to make informed decisions for optimizing network performance. The integration of deep learning with automated and connected vehicles paves the way for advanced transportation network optimization. Deep learning algorithms can analyze complex transportation data, including traffic patterns, demand forecasting, and dynamic congestion scenarios, to optimize routing, reduce travel times, and enhance overall system efficiency. The paper presents case studies and simulations demonstrating the effectiveness of deep learning-based approaches in achieving significant improvements in network performance metrics

Keywords: automated vehicles, connected vehicles, deep learning, smart transportation network

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Authors: Arash Heydarian Pashakhanlou

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The security dilemma is one of the key concepts in International Relations (IR), and the numerous engagements with it have created a great deal of confusion regarding its essence. That is why this article seeks to dissect the security dilemma and rebuild it from its foundational core. In doing so, the present study highlights that the security dilemma requires interaction among actors that seek to protect themselves from other's capacity for harm under the condition of uncertainty to operate. In this constellation, actors are confronted with the dilemma of motives, power, and action, which they seek to resolve by acquiring information regarding their opponents. The relationship between the parties is shaped by the harm-uncertainty index (HUI) consisting of geographical distance, MAD, and joint democracy that determines the intensity of the security dilemma. These elements define the unified theory of the security dilemma (UTSD) developed here. UTSD challenges the prevailing view that the security dilemma is a unidimensional paradoxical concept, regulated by the offense-defense balance and differentiation that only occurs in anarchic settings with tragic outcomes and is equivalent to the spiral model.

Keywords: security dilemma, revisionism, status quo, anarchy, uncertainty, tragedy, spiral, deterrence

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Authors: Najm Alotaibi

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Human motion capture has become one of the major area of interest in the field of computer vision. Some of the major application areas that have been rapidly evolving include the advanced human interfaces, virtual reality and security/surveillance systems. This study provides a brief overview of the techniques and applications used for the markerless human motion capture, which deals with analyzing the human motion in the form of mathematical formulations. The major contribution of this research is that it classifies the computer vision based techniques of human motion capture based on the taxonomy, and then breaks its down into four systematically different categories of tracking, initialization, pose estimation and recognition. The detailed descriptions and the relationships descriptions are given for the techniques of tracking and pose estimation. The subcategories of each process are further described. Various hypotheses have been used by the researchers in this domain are surveyed and the evolution of these techniques have been explained. It has been concluded in the survey that most researchers have focused on using the mathematical body models for the markerless motion capture.

Keywords: human motion capture, computer vision, vision-based, tracking

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Authors: Muhammad Mehran Arshad Khan, Chengliang Wang, Zou Minhui, Danyal Badar Soomro

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Security of the smart home in terms of behavior activity pattern recognition is a totally dissimilar and unique issue as compared to the security issues of other scenarios. Sensor devices (low capacity and high capacity) interact and negotiate each other by detecting the daily behavior activity of individuals to execute common tasks. Once a device (e.g., surveillance camera, smart phone and light detection sensor etc.) is compromised, an adversary can then get access to a specific device and can damage daily behavior activity by altering the data and commands. In this scenario, a group of common instruction processes may get involved to generate deadlock. Therefore, an effective suitable security solution is required for smart home architecture. This paper proposes seamless distributed Scheme which fortifies low computational wireless devices for secure communication. Proposed scheme is based on lightweight key-session process to upheld cryptic-link for trajectory by recognizing of individual’s behavior activities pattern. Every device and service provider unit (low capacity sensors (LCS) and high capacity sensors (HCS)) uses an authentication token and originates a secure trajectory connection in network. Analysis of experiments is revealed that proposed scheme strengthens the devices against device seizure attack by recognizing daily behavior activities, minimum utilization memory space of LCS and avoids network from deadlock. Additionally, the results of a comparison with other schemes indicate that scheme manages efficiency in term of computation and communication.

Keywords: authentication, key-session, security, wireless sensors

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Authors: Sara Muslat Alsahali, Nout Mohammed Alqahtani

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Digital technology has changed the world, and with the increasing number of children accessing the Internet, it has now become an integral part of children's lives from their early years. With the rapid development of digital technology, the risks children face on the internet also evolve from cyberbullying to misuse, sexual exploitation, and abuse of their private information over the Internet. Digital technology, with its advantages and disadvantages, is now a fact of our life. Therefore, knowledge of how to reduce its risks and maximize its benefits will help shape the growth and future of a new generation of digital citizens. This paper will discuss access control techniques that help to create secure cyberspace where children can be safe without depriving them of their rights and freedom to use the internet and preventing them from its benefits. Also, it sheds light on its challenges and problems by classifying the methods of parental controlling into two possibilities asynchronous and synchronous techniques and choosing YouTube as a case study of access control techniques.

Keywords: access control, cyber security, kids, parental monitoring

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Authors: Naveed Ghani

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With the arrival of higher speed communication links and mature application running over the internet, the requirement for reliable, efficient and robust network designs rising day by day. Multi-Protocol Label Switching technology (MPLS) Virtual Private Networks (VPNs) have committed to provide optimal network services. They are gaining popularity in industry day by day. Enterprise customers are moving to service providers that offer MPLS VPNs. The main reason for this shifting is the capability of MPLS VPN to provide built in security features and any-to-any connectivity. MPLS VPNs improved the network performance due to fast label switching as compare to traditional IP Forwarding but traffic classification and policing was still required on per hop basis to enhance the performance of real time traffic which is delay sensitive (particularly voice and video). QoS (Quality of service) is the most important factor to prioritize enterprise networks’ real time traffic such as voice and video. This thesis is focused on the study of QoS parameters (e.g. delay, jitter and MOS (Mean Opinion Score)) for the real time traffic over MPLS VPNs. DiffServ (Differentiated Services) QoS model will be used over MPLS VPN network to get end-to-end service quality.

Keywords: network, MPLS, VPN, DiffServ, MPLS VPN, DiffServ QoS, QoS Model, GNS2

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Authors: Muntadher Sallal, Gareth Owenson, Mo Adda, Safa Shubbar

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Bitcoin is a digital currency based on a peer-to-peer network to propagate and verify transactions. Bitcoin is gaining wider adoption than any previous crypto-currency. However, the mechanism of peers randomly choosing logical neighbors without any knowledge about underlying physical topology can cause a delay overhead in information propagation, which makes the system vulnerable to double-spend attacks. Aiming at alleviating the propagation delay problem, this paper introduces proximity-aware extensions to the current Bitcoin protocol, named Master Node Based Clustering (MNBC). The ultimate purpose of the proposed protocol, that are based on how clusters are formulated and how nodes can define their membership, is to improve the information propagation delay in the Bitcoin network. In MNBC protocol, physical internet connectivity increases, as well as the number of hops between nodes, decreases through assigning nodes to be responsible for maintaining clusters based on physical internet proximity. We show, through simulations, that the proposed protocol defines better clustering structures that optimize the performance of the transaction propagation over the Bitcoin protocol. The evaluation of partition attacks in the MNBC protocol, as well as the Bitcoin network, was done in this paper. Evaluation results prove that even though the Bitcoin network is more resistant against the partitioning attack than the MNBC protocol, more resources are needed to be spent to split the network in the MNBC protocol, especially with a higher number of nodes.

Keywords: Bitcoin network, propagation delay, clustering, scalability

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Authors: Omid Khodabakhshi, Amir Rozdel

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The subject of cloud computing security research has allocated a number of challenges and competitions because the data center is comprised of complex private information and are always faced various risks of information disclosure by hacker attacks or internal enemies. Accordingly, the security of virtual machines in the cloud computing infrastructure layer is very important. So far, there are many software solutions to develop security in virtual machines. But using software alone is not enough to solve security problems. The purpose of this article is to examine the challenges and security requirements for accessing and storing data in an insecure cloud environment. In other words, in this article, a structure is proposed for the implementation of highly isolated security-sensitive codes using secure computing hardware in virtual environments. It also allows remote code validation with inputs and outputs. We provide these security features even in situations where the BIOS, the operating system, and even the super-supervisor are infected. To achieve these goals, we will use the hardware support provided by the new Intel and AMD processors, as well as the TPM security chip. In conclusion, the use of these technologies ultimately creates a root of dynamic trust and reduces TCB to security-sensitive codes.

Keywords: code, cloud computing, security, virtual machines

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Authors: Mohammed Affanuddin H. Siddique, Jayesh S. Shukla, Chetan B. Meshram

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The neural networks are one of the power tools of machine learning. After the invention of perceptron in early 1980's, the neural networks and its application have grown rapidly. Neural networks are a technique originally developed for pattern investigation. The structure of a neural network consists of neurons connected through synapse. Here, we have investigated the different algorithms and cost function reduction techniques for optimization of vertical axis wind turbine (VAWT) rotor blades. The aerodynamic force coefficients corresponding to the airfoils are stored in a database along with the airfoil coordinates. A forward propagation neural network is created with the input as aerodynamic coefficients and output as the airfoil co-ordinates. In the proposed algorithm, the hidden layer is incorporated into cost function having linear and non-linear error terms. In this article, it is observed that the ANNs (Artificial Neural Network) can be used for the VAWT’s optimization.

Keywords: VAWT, ANN, optimization, inverse design

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Authors: Kyoung-Jae Kim

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Collaborative Filtering (CF) is a popular technique for the personalization in the E-commerce domain to reduce information overload. In general, CF provides recommending items list based on other similar users’ preferences from the user-item matrix and predicts the focal user’s preference for particular items by using them. Many recommender systems in real-world use CF techniques because it’s excellent accuracy and robustness. However, it has some limitations including sparsity problems and complex dimensionality in a user-item matrix. In addition, traditional CF does not consider the emotional interaction between users. In this study, we propose recommender systems using social network and singular value decomposition (SVD) to alleviate some limitations. The purpose of this study is to reduce the dimensionality of data set using SVD and to improve the performance of CF by using emotional information from social network data of the focal user. In this study, we test the usability of hybrid CF, SVD and social network information model using the real-world data. The experimental results show that the proposed model outperforms conventional CF models.

Keywords: recommender systems, collaborative filtering, social network information, singular value decomposition

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Authors: J. S. Saini, P. P. K. Sandhu

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The multi-hop nature of Wireless Mesh Networks and the hasty progression of throughput demands results in multi- channels and multi-radios structures in mesh networks, but the main problem of co-channels interference reduces the total throughput, specifically in multi-hop networks. Quality of Service mentions a vast collection of networking technologies and techniques that guarantee the ability of a network to make available desired services with predictable results. Quality of Service (QoS) can be directed at a network interface, towards a specific server or router's performance, or in specific applications. Due to interference among various transmissions, the QoS routing in multi-hop wireless networks is formidable task. In case of multi-channel wireless network, since two transmissions using the same channel may interfere with each other. This paper has considered the Destination Sequenced Distance Vector (DSDV) routing protocol to locate the secure and optimised path. The proposed technique also utilizes the Lempel–Ziv–Welch (LZW) based lossless data compression and intra cluster data aggregation to enhance the communication between the source and the destination. The use of clustering has the ability to aggregate the multiple packets and locates a single route using the clusters to improve the intra cluster data aggregation. The use of the LZW based lossless data compression has ability to reduce the data packet size and hence it will consume less energy, thus increasing the network QoS. The MATLAB tool has been used to evaluate the effectiveness of the projected technique. The comparative analysis has shown that the proposed technique outperforms over the existing techniques.

Keywords: WMNS, QOS, flooding, collision avoidance, LZW, congestion control

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