Showing papers by "National University of Computer and Emerging Sciences published in 2017"

DDoS Attack Detection and Mitigation Using SDN: Methods, Practices, and Solutions

Abstract: Distributed denial-of-service (DDoS) attacks have become a weapon of choice for hackers, cyber extortionists, and cyber terrorists. These attacks can swiftly incapacitate a victim, causing huge revenue losses. Despite the large number of traditional mitigation solutions that exists today, DDoS attacks continue to grow in frequency, volume, and severity. This calls for a new network paradigm to address the requirements of today’s challenging security threats. Software-defined networking (SDN) is an emerging network paradigm which has gained significant traction by many researchers to address the requirement of today’s data centers. Inspired by the capabilities of SDN, we present a comprehensive survey of existing SDN-based DDoS attack detection and mitigation solutions. We classify solutions based on DDoS attack detection techniques and identify requirements of an effective solution. Based on our findings, we propose a novel framework for detection and mitigation of DDoS attacks in a large-scale network which comprises a smart city built on SDN infrastructure. Our proposed framework is capable of meeting application-specific DDoS attack detection and mitigation requirements. The primary contribution of this paper is twofold. First, we provide an in-depth survey and discussion of SDN-based DDoS attack detection and mitigation mechanisms, and we classify them with respect to the detection techniques. Second, leveraging the characteristics of SDN for network security, we propose and present an SDN-based proactive DDoS Defense Framework (ProDefense). We show how this framework can be utilized to secure applications built for smart cities. Moreover, the paper highlights open research challenges, future research directions, and recommendations related to SDN-based DDoS detection and mitigation.

Millimeter Wave Receiver Efficiency: A Comprehensive Comparison of Beamforming Schemes With Low Resolution ADCs

Abstract: In this paper, we study the achievable rate and the energy efficiency of analog, hybrid, and digital combining (AC, HC, and DC) for millimeter wave (mmW) receivers. We take into account the power consumption of all receiver components, not just analog-to-digital converters (ADCs), determine some practical limitations of beamforming in each architecture, and develop performance analysis charts that enable comparison of different receivers simultaneously in terms of two metrics, namely, spectral efficiency (SE) and energy efficiency (EE). We present a multi-objective utility optimization interpretation to find the best SE-EE weighted tradeoff among AC, DC, and HC schemes. We consider an additive quantization noise model to evaluate the achievable rates with low resolution ADCs. Our analysis shows that AC is only advantageous if the channel rank is strictly one, the link has very low SNR, or there is a very stringent low power constraint at the receiver. Otherwise, we show that the usual claim that DC requires the highest power is not universally valid. Rather, either DC or HC alternatively results in the better SE versus EE tradeoff depending strongly on the considered power consumption characteristic values for each component of the mmW receiver.

Smart home automation system using Bluetooth technology

Abstract: In this paper a low cost and user friendly remote controlled home automation system is presented using Arduino board, Bluetooth module, smartphone, ultrasonic sensor and moisture sensor. A smartphone application is used in the suggested system which allows the users to control up to 18 devices including home appliances and sensors using Bluetooth technology. Nowadays, most of conventional home automation systems are designed for special purposes while proposed system is a general purpose home automation system. Which can easily be implement in existing home. The suggested system has more features than conventional home automation systems such as an ultrasonic sensor is used for water level detection and soil moisture sensor is use for automatic plant irrigation system. This paper also describes the hardware and software architecture of system, future work and scope. The proposed prototype of home automation system is implemented and tested on hardware and it gave the exact and expected results.

Prospects of robotics in food industry

Abstract: Technological advancements in various domains have broadened the application horizon of robotics to an incredible extent. Highlighting a very recent application area, this paper presents a comprehensive review of robotics application in food industry. Robots essentially have the potential to transform the processes in food processing and handling, palletizing and packing and food serving. Therefore, recent years witnessed tremendously increased trend of robots deployment in food sector. Consequently, the aspects related with robot kinematics, dynamics, hygiene, economic efficiency, human-robot interaction, safety and protection and operation and maintenance are of critical importance and are discussed in the present review. A comparison of actual robots being used in the industry is also presented. The review reveals that the food serving sector is the new potential area in which ample research opportunities exist by integrating advancements from various technology domains. It is anticipated that wider dissemination of research developments in ‘robo-food’ will stimulate more collaborations among the research community and contribute to further developments.

Precise Indoor Positioning Using UWB: A Review of Methods, Algorithms and Implementations

Abstract: The demand and growth of indoor positioning has increased rapidly in the past few years for a diverse range of applications. Various innovative techniques and technologies have been introduced but precise and reliable indoor positioning still remains a challenging task due to dependence on a large number of factors and limitations of the technologies. Positioning technologies based on radio frequency (RF) have many advantages over the technologies utilizing ultrasonic, optical and infrared devices. Both narrowband and wideband RF systems have been implemented for short range indoor positioning/real-time locating systems. Ultra wideband (UWB) technology has emerged as a viable candidate for precise indoor positioning due its unique characteristics. This article presents a comparison of UWB and narrowband RF technologies in terms of modulation, throughput, transmission time, energy efficiency, multipath resolving capability and interference. Secondly, methods for measurement of the positioning parameters are discussed based on a generalized measurement model and, in addition, widely used position estimation algorithms are surveyed. Finally, the article provides practical UWB positioning systems and state-of-the-art implementations. We believe that the review presented in this article provides a structured overview and comparison of the positioning methods, algorithms and implementations in the field of precise UWB indoor positioning, and will be helpful for practitioners as well as for researchers to keep abreast of the recent developments in the field.

Flow and heat transfer analysis of Jeffery nano fluid impinging obliquely over a stretched plate

Abstract: This study investigates the problem of oblique stagnation point flow using Jeffery nanofluid as a rheological fluid model. Effects of thermophoresis and Brownian motion are taken into account. The governing nonlinear partial differential equations for the flow field are obtained and then converted to ordinary differential equations via suitable transformations. Consequential highly non-linear system of differential equations is solved numerically through mid-point integration as a basic scheme along with Richardson's extrapolation as an enhancement scheme and analytical results are also obtained using optimal homotopy analysis Method (OHAM). Non-dimensional velocities, temperature and concentration profiles are expressed through graphs. Numerical values of local skin friction coefficients, local heat and mass flux are tabulated numerically as well as analytically for various physical parameters emerging in our flow problem. The obtained results revealed that both normal and tangential skin friction coefficients decrease with an increase in Jeffery fluid parameter. It is also observed that an enhancement in Thermophoresis and Brownian motion parameters leads to a reduction in heat flux at the wall. Comparison of numerical data is made with previous existing literature to confirm accuracy of present study for the case of Newtonian fluid.

Noether symmetry approach in $$f(\mathcal {G},T)$$ f ( G , T ) gravity

Abstract: We explore the recently introduced modified Gauss–Bonnet gravity (Sharif and Ikram in Eur Phys J C 76:640, 2016), $$f(\mathcal {G},T)$$ pragmatic with $$\mathcal {G}$$ , the Gauss–Bonnet term, and T, the trace of the energy-momentum tensor. Noether symmetry approach has been used to develop some cosmologically viable $$f(\mathcal {G},T)$$ gravity models. The Noether equations of modified gravity are reported for flat FRW universe. Two specific models have been studied to determine the conserved quantities and exact solutions. In particular, the well known deSitter solution is reconstructed for some specific choice of $$f(\mathcal {G},T)$$ gravity model.

Monitoring Tweets for Depression to Detect At-risk Users

Abstract: We propose an automated system that can identify at-risk users from their public social media activity, more specifically, from Twitter. The data that we collected is from the #BellLetsTalk campaign, which is a wide-reaching, multi-year program designed to break the silence around mental illness and support mental health across Canada. To achieve our goal, we trained a user-level classifier that can detect at-risk users that achieves a reasonable precision and recall. We also trained a tweet-level classifier that predicts if a tweet indicates depression. This task was much more difficult due to the imbalanced data. In the dataset that we labeled, we came across 5% depression tweets and 95% non-depression tweets. To handle this class imbalance, we used undersampling methods. The resulting classifier had high recall, but low precision. Therefore, we only use this classifier to compute the estimated percentage of depressed tweets and to add this value as a feature for the user-level classifier.

Some exact solutions in f(,T) gravity via Noether symmetries

Abstract: This paper is devoted to investigate the recently proposed modified Gauss–Bonnet f(𝒢,T) gravity, with 𝒢, the Gauss–Bonnet term, coupled with T, the trace of energy–momentum tensor. We have used the Noether symmetry methodology to discuss some cosmologically important f(𝒢,T) gravity models with anisotropic background. In particular, the Noether symmetry equations for modified f(𝒢,T) gravity are reported for locally rotationally symmetric Bianchi type I universe. Explicitly, two models have been proposed to explore the exact solutions and the conserved quantities. It is concluded that the specific models of modified Gauss–Bonnet gravity may be used to reconstruct ΛCDM cosmology without involving any cosmological constant.

Robust off-line text independent writer identification using bagged discrete cosine transform features

Abstract: A robust system for offline text independent writer identification is proposed.Bagged discrete cosine transform(BDCT) descriptors used in place of conventional DCT.Proposed system tested on four challenging data sets (two English and two Arabic).BDCT has shown robustness to noise and blurring. Efficient writer identification systems identify the authorship of an unknown sample of text with high confidence. This has made automatic writer identification a very important topic of research for forensic document analysis. In this paper, we propose a robust system for offline text independent writer identification using bagged discrete cosine transform (BDCT) descriptors. Universal codebooks are first used to generate multiple predictor models. A final decision is then obtained by using the majority voting rule from these predictor models. The BDCT approach allows for DCT features to be effectively exploited for robust hand writer identification. The proposed system has first been assessed on the original version of hand written documents of various datasets and results have shown comparable performance with state-of-the-art systems. Next, blurry and noisy documents of two different datasets have been considered through intensive experiments where the system has been shown to perform significantly better than its competitors. To the best of our knowledge this is the first work that addresses the robustness aspect in automatic hand writer identification. This is particularly suitable in digital forensics as the documents acquired by the analyst may not be in ideal conditions.

Opportunities and challenges in control of smart grids – Pakistani perspective

Abstract: With the advancement in technologies, the power requirement around the globe is tremendously increasing, putting extra loads on grids. The existing grids cannot bear that load and also do not provide the interface with Distributed Renewable Energy Sources (DRES). Building new lines and substations alone do not serve the purpose of overcoming energy shortfall. Thus a major transformation in electricity infrastructure is need of the hour to meet the ever growing demands of electricity. Converting current power management system to a smart autonomic system is pertinent to achieve an increasing amount of renewable energy generation. This paper presents a comprehensive review of advances in control of smart grids. Various robust and adaptive strategies are spotlighted with a detailed description of control of overloads and power smart grids. Also, power generation, storage and management techniques and development of operational schedule of sources and loads are elaborated. Recently reported systems and Information and Communication Technologies (ICT) techniques in smart grid are highlighted. Renewable energy has potential to eliminate the current electricity crisis in Pakistan's energy sector. The solar, wind, hydro and biogas/biomass are the alternative energy resources found abundantly in the country, which have tremendous potential to offer environment-friendly energy solutions. This in-depth study reveals that a lot of opportunities and potential of smart grid technology exist in developing countries like Pakistan that need to be exploited so as to cope with energy crisis.

Physical Attributes of Anisotropic Compact Stars in $f(R,G)$ Gravity

Abstract: Modified gravity is one of the potential candidates to explain the accelerated expansion of the universe. Current study highlights the materialization of anisotropic compact stars in the context of f(R, G) theory of gravity. In particular, to gain insight in the physical behavior of three stars namely, Her X1, SAX J 1808-3658 and 4U 1820-30, energy density, and radial and tangential pressures are calculated. The f(R, G) gravity model is split into a Starobinsky like f(R) model and a power law f(G) model. The main feature of the work is a 3-dimensional graphical analysis in which, anisotropic measurements, energy conditions and stability attributes of these stars are discussed. It is shown that all three stars behave as usual for positive values of the f(G) model parameter n.

A comparative study of chemically reacting 2D flow of Casson and Maxwell fluids

Abstract: Theoretical investigation is performed to discuss the heat and mass transfer behavior of chemically reacting magnetohydrodynamic Casson and Maxwell fluids past a stretching sheet with Brownian moment and thermophoresis effects with internal heat source/sink Runge-Kutta based shooting procedure is employed to yield the solutions of the problem Effects of the pertinent parameters on velocity, thermal and concentration boundary layers are analyzed through graphical illustrations Also computed the reduced Nusselt and Sherwood numbers and presented through tables It is found that the boundary layers of temperature and concentration fields are non-uniform for Casson and Maxwell fluids Thermal and concentration fields of Maxwell fluid is highly influenced by the pertinent parameters when compared with the Casson fluid

A flat-panel-shaped hybrid piezo/triboelectric nanogenerator for ambient energy harvesting.

Abstract: Recently, many researchers have been paying attention to nanogenerators (NGs) as energy sources for self-powered mirco-nano systems, and studying how to achieve their higher power generation. Hence, we propose a hybrid-type NG for harvesting both the piezoelectric and triboelectric effect simultaneously. In the proposed hybrid NG, the piezoelectric NG (PNG) and triboelectric NG (TENG) are fabricated using polydimethylsiloxane (PDMS) and perovskite zinc stannite (ZnSnO3) nanocubes with a high charge polarization of 59 uC cm−2 composite (PDMS + ZnSnO3) and UV surface-treated PDMS, respectively. To effectively combine a high output current of PNG and a high voltage of TENG, these two NGs are stacked upon each other, and separated by sponge spacers providing a uniform air gap for the triboelectric effect. In particular, this fabricated structure has a low Young's modulus for piezoelectricity. The proposed hybrid NG device effectively achieves a combined peak voltage of 300 V on an open circuit, a power density of 10.41 mW cm−2 at 1 MΩ load, and a maximum short circuit current density of 16 mA cm−2 at 50 Ω load. It is feasible that the proposed NG can be utilized as a source for various self-powered systems.

Emerging anisotropic compact stars in $$f(\mathcal {G},T)$$ f ( G , T ) gravity

Abstract: The possible emergence of compact stars has been investigated in the recently introduced modified Gauss–Bonnet $$f(\mathcal {G},T)$$ gravity, where $$\mathcal {G}$$ is the Gauss–Bonnet term and T is the trace of the energy-momentum tensor (Sharif and Ikram, Eur Phys J C 76:640, 2016) Specifically, for this modified $$f(\mathcal {G}, T)$$ theory, the analytic solutions of Krori and Barua have been applied to an anisotropic matter distribution To determine the unknown constants appearing in the Krori and Barua metric, the well-known three models of the compact stars, namely 4U1820-30, Her X-I, and SAX J 18084-3658 have been used The analysis of the physical behaviour of the compact stars has been presented and the physical features like energy density and pressure, energy conditions, static equilibrium, stability, measure of anisotropy, and regularity of the compact stars, have been discussed

An analysis of Cattaneo-Christov double-diffusion model for Sisko fluid flow with velocity slip

Abstract: The present frame work examines the characteristics of Cattaneo-Christov double-diffusion model to the Sisko fluid flow over a flat stretching sheet with velocity slip and thermal radiation. Instead of using classical Fourier's law and Fick's law the inclusion of thermal and concentration relaxation times lead us to the Cattaneo-Christov double-diffusion model. Utilization of the suitable transformations makes it convenient to transform our governing partial differential equations into ordinary differential equations. Further, the numerical solutions to these normalized ordinary differential equations are obtained by adopting the shooting technique along with Runge-Kutta fourth order method. The results are then plotted for various values of the pertinent parameters and discussed deliberately. Also, a comparison of the present results with the previously reported results as well as analytic results obtained through the homotopy analysis method (HAM) helps to ensure their validity. This investigation leads us to the fact that the velocity diminishes with the velocity slip parameter. Also, in temperature and concentration profiles a decline can obviously be verdict with the larger relaxation times.

The potential role of renewable energy sources in robot's power system: A case study of Pakistan

Abstract: The domain of ‘robotics’ is undergoing a major transformation in dimension as well as scope. Recent advances in various disciplines of technology have revolutionized this domain at an incredible pace far beyond the contemporary state of the art. Highlighting the forecasted population of robots in future and the resulting demand of massive energy consumption, this review addresses the application of renewable energy sources in uninterruptible supply for robots. The study analyzes the extensive field of renewable energy technology and discovers that comparing with traditional sources; green energies like solar, wind and biological have significant potential to drive robots. Listing the world-wide achievements attained by the applications of renewable energy technology for robots, the review finally presents the subject matter in context of Pakistan. It is shown that being rich in renewable energy resources, broad possibilities for robot technologies exist here. With a discussion on challenges to exploit this potential, suggestions are outlined. It is anticipated that wider dissemination of research developments in the integration of these streams will stimulate more exchanges and collaborations among the research community and contribute to further advancements.

LOMCF: Forwarding and Caching in Named Data Networking Based MANETs

Abstract: Named data networking (NDN) resolves traditional transmission control protocol/internet protocol (TCP/IP)-based Internet problems (i.e., location dependent, complex usage, scalability, poor resource utilization, etc.) and is considered as an eligible candidate for futuristic Internet paradigm. In NDN-based mobile ad hoc networks (MANETs), the participating nodes are operated in highly dynamic and challengeable environment such as low battery power, channel fluctuations, intermittent connectivity, etc. Due to the broadcast nature of the wireless channel, the NDN-based MANETs highlight severe issues (e.g., packet collisions, flooding, data redundancy, and packet retransmissions), which further degrade network performance. In this paper, to cope with these problems, we have proposed a novel protocol, named location-aware on-demand multipath caching and forwarding for NDN-based MANETs. Performance of the proposed protocol is evaluated by using a simulator called ndnSIM. Extensive experiments along their results show that proposed protocol performs better as compared with the other recent proposed protocols in terms of content retrieval time, Interest retransmissions, and the total number of Interest packets injected, as well as discarded, in the network.

Building Information Modeling (BIM) Enabled Facilities Management Using Hadoop Architecture

Abstract: Protecting the safety of occupants and the environment is a core value within Facilities Management. Data acquisition systems such as wireless sensor networks can help to monitor facilities to reduce hazards such as fire, water flooding and burglaries. Building Information Modeling (BIM) is a revolutionary development that is reshaping the Architecture Engineering and Construction (AEC) industry. BIM is both a process and a technology, offers wide solutions for facilities management. In order to monitor and manage facilities data in a BIM based simulated environment, this work reports upon a development of a system that uses BIM software and a wireless sensor technology to develop a proactive safety management system. However, to link BIM data with data values of wireless sensors motes will challenge the traditional approaches to data management and massive sensor data will contribute to the emerging model of big data. To extract relevant information out from the collected data, a prototype system uses Hadoop architecture for data storage and processing. The results of processing BIM and sensor data in a Hadoop architecture have demonstrated that proposed system can effectively provide data visualizations to facility managers with the most accurate information needed to make decisions. It also ultimately attempts to reduce safety hazards during the facility management phase of a building.

Social engineering: Revisiting end-user awareness and susceptibility to classic attack vectors

Abstract: Social engineering relies on human vulnerability to exploit system security Social engineering attacks are relatively harder to protect against as they mainly target the user, and not just hardware or software system defenses End user awareness can be considered as one of the simplest yet most effective ways to protect the end user against social engineering vectors The present study ascertains the level of user susceptibility to social engineering attacks in a cooperating corporate organization Two attack scenarios, a spear-phishing campaign and a physical intrusion vector were designed targeting the organization's user population (employees) based on publicly available information from the Internet Clues relating to social engineering techniques were included in the attacks to alert suspicious users Despite the revealing signs of a social engineering campaign, the results indicated that a significantly high proportion (46–60%) of the users fell prey and failed to identify the attacks It was observed that lack of user awareness remained the primary cause of the success of the attacks, requiring corrective action through post-incident training and regular IT security drills

Towards autonomous cleaning of photovoltaic modules: Design and realization of a robotic cleaner

Abstract: Solar panels typically consist of photovoltaic (PV) cells covered by a protective glass coating, which generate electricity when subjected to radiations. However, the capability of electricity generation is constrained due to layer of dust on PV modules. In contrast with conventional method of cleaning the modules using water, this paper presents design and development of a robotic cleaner for cleaning PV modules of Quaid-e-Azam Solar Park (QASP). The hardware as well as software architectures of the proposed robotic cleaner are detailed. The novelty of the design lies in its low cost indigenous development and simplicity in design. The mechanism primarily consists of ducted fan, roller brush and blower fan to offer slippage-free motion and cleaning on a glassy surface. Series of experiments and field trials demonstrate efficiency of the mechanism in cleaning the modules effectively.

Slip Analysis at Fluid-Solid Interface in MHD Squeezing Flow of Casson Fluid through Porous Medium

Abstract: An unsteady squeezing flow of Casson fluid having Magneto Hydro Dynamic effect and passing through porous medium channel with slip at the boundaries has been modelled and analyzed. Similarity transformations are applied to the governing partial differential equations of the Casson model to get a highly non-linear fourth order ordinary differential equation. The obtained equation is then solved analytically using the Homotopy Perturbation Method (HPM) for uniform and non-uniform slip at the boundaries. Five cases of boundary conditions, representing slip at upper wall only, uniform slip at both walls, non-uniform slip where slip at upper wall is greater than that of lower wall, non-uniform slip where slip at lower wall is greater than that of upper wall, and slip at lower wall only are considered and thoroughly investigated. Validation is performed by solving the equation numerically using fourth order explicit Runge Kutta method (ERK4). Both analytical and numerical results show good agreement. Lastly, the effects of various fluid parameters on the velocity profile are investigated for each case graphically. Analysis of these plots show that the positive and negative squeeze numbers have opposite effect on the velocity profile throughout all the cases. It is also observed that various fluid parameters like Casson, MHD, and Permeability have similar effects on the velocity profile in the cases when slip is occurring at the upper wall only, and non-uniform slip at both the boundaries with slip at lower wall is greater than upper wall. Furthermore, similar effects have been observed when slip is uniform at both the boundaries, and in case of non-uniform slip with slip at lower wall is less than the upper wall.

SPECTRE: supporting consumption policies in window-based parallel complex event processing

Abstract: Distributed Complex Event Processing (DCEP) is a paradigm to infer the occurrence of complex situations in the surrounding world from basic events like sensor readings. In doing so, DCEP operators detect event patterns on their incoming event streams. To yield high operator throughput, data parallelization frameworks divide the incoming event streams of an operator into overlapping windows that are processed in parallel by a number of operator instances. In doing so, the basic assumption is that the different windows can be processed independently from each other. However, consumption policies enforce that events can only be part of one pattern instance; then, they are consumed, i.e., removed from further pattern detection. That implies that the constituent events of a pattern instance detected in one window are excluded from all other windows as well, which breaks the data parallelism between different windows. In this paper, we tackle this problem by means of speculation: Based on the likelihood of an event's consumption in a window, subsequent windows may speculatively suppress that event. We propose the SPECTRE framework for speculative processing of multiple dependent windows in parallel. Our evaluations show an up to linear scalability of SPECTRE with the number of CPU cores.