Numerical Investigation of Dynamic Stall over a Wind Turbine Pitching Airfoil by Using OpenFOAM

Computations for two-dimensional flow past a stationary and harmonically pitching wind turbine airfoil at a moderate value of Reynolds number (400000) are carried out by progressively increasing the angle of attack for stationary airfoil and at fixed pitching frequencies for rotary one. The incompressible Navier-Stokes equations in conjunction with Unsteady Reynolds Average Navier-Stokes (URANS) equations for turbulence modeling are solved by OpenFOAM package to investigate the aerodynamic phenomena occurred at stationary and pitching conditions on a NACA 6-series wind turbine airfoil. The aim of this study is to enhance the accuracy of numerical simulation in predicting the aerodynamic behavior of an oscillating airfoil in OpenFOAM. Hence, for turbulence modelling, k-ω-SST with low-Reynolds correction is employed to capture the unsteady phenomena occurred in stationary and oscillating motion of the airfoil. Using aerodynamic and pressure coefficients along with flow patterns, the unsteady aerodynamics at pre-, near-, and post-static stall regions are analyzed in harmonically pitching airfoil, and the results are validated with the corresponding experimental data possessed by the authors. The results indicate that implementing the mentioned turbulence model leads to accurate prediction of the angle of static stall for stationary airfoil and flow separation, dynamic stall phenomenon, and reattachment of the flow on the surface of airfoil for pitching one. Due to the geometry of the studied 6-series airfoil, the vortex on the upper surface of the airfoil during upstrokes is formed at the trailing edge. Therefore, the pattern flow obtained by our numerical simulations represents the formation and change of the trailing-edge vortex at near- and post-stall regions where this process determines the dynamic stall phenomenon.

A Distributed Mobile Agent Based on Intrusion Detection System for MANET

This study is about an algorithmic dependence of Artificial Neural Network on Multilayer Perceptron (MPL) pertaining to the classification and clustering presentations for Mobile Adhoc Network vulnerabilities. Moreover, mobile ad hoc network (MANET) is ubiquitous intelligent internetworking devices in which it has the ability to detect their environment using an autonomous system of mobile nodes that are connected via wireless links. Security affairs are the most important subject in MANET due to the easy penetrative scenarios occurred in such an auto configuration network. One of the powerful techniques used for inspecting the network packets is Intrusion Detection System (IDS); in this article, we are going to show the effectiveness of artificial neural networks used as a machine learning along with stochastic approach (information gain) to classify the malicious behaviors in simulated network with respect to different IDS techniques. The monitoring agent is responsible for detection inference engine, the audit data is collected from collecting agent by simulating the node attack and contrasted outputs with normal behaviors of the framework, whenever. In the event that there is any deviation from the ordinary behaviors then the monitoring agent is considered this event as an attack , in this article we are going to demonstrate the  signature-based IDS approach in a MANET by implementing the back propagation algorithm over ensemble-based Traffic Table (TT), thus the signature of malicious behaviors or undesirable activities are often significantly prognosticated and efficiently figured out, by increasing the parametric set-up of Back propagation algorithm during the experimental results which empirically shown its effectiveness  for the ratio of detection index up to 98.6 percentage. Consequently it is proved in empirical results in this article, the performance matrices are also being included in this article with Xgraph screen show by different through puts like Packet Delivery Ratio (PDR), Through Put(TP), and Average Delay(AD).

Secure E-Pay System Using Steganography and Visual Cryptography

Today’s internet world is highly prone to various online attacks, of which the most harmful attack is phishing. The attackers host the fake websites which are very similar and look alike. We propose an image based authentication using steganography and visual cryptography to prevent phishing. This paper presents a secure steganographic technique for true color (RGB) images and uses Discrete Cosine Transform to compress the images. The proposed method hides the secret data inside the cover image. The use of visual cryptography is to preserve the privacy of an image by decomposing the original image into two shares. Original image can be identified only when both qualified shares are simultaneously available. Individual share does not reveal the identity of the original image. Thus, the existence of the secret message is hard to be detected by the RS steganalysis.

An Improved Method on Static Binary Analysis to Enhance the Context-Sensitive CFI

Control Flow Integrity (CFI) is one of the most promising technique to defend Code-Reuse Attacks (CRAs). Traditional CFI Systems and recent Context-Sensitive CFI use coarse control flow graphs (CFGs) to analyze whether the control flow hijack occurs, left vast space for attackers at indirect call-sites. Coarse CFGs make it difficult to decide which target to execute at indirect control-flow transfers, and weaken the existing CFI systems actually. It is an unsolved problem to extract CFGs precisely and perfectly from binaries now. In this paper, we present an algorithm to get a more precise CFG from binaries. Parameters are analyzed at indirect call-sites and functions firstly. By comparing counts of parameters prepared before call-sites and consumed by functions, targets of indirect calls are reduced. Then the control flow would be more constrained at indirect call-sites in runtime. Combined with CCFI, we implement our policy. Experimental results on some popular programs show that our approach is efficient. Further analysis show that it can mitigate COOP and other advanced attacks.

A Retrospective Cohort Study on an Outbreak of Gastroenteritis Linked to a Buffet Lunch Served during a Conference in Accra

On 21st November, 2016, an outbreak of foodborne illness occurred after a buffet lunch served during a stakeholders’ consultation meeting held in Accra. An investigation was conducted to characterise the affected people, determine the etiologic food, the source of contamination and the etiologic agent and to implement appropriate public health measures to prevent future occurrences. A retrospective cohort study was conducted via telephone interviews, using a structured questionnaire developed from the buffet menu. A case was defined as any person suffering from symptoms of foodborne illness e.g. diarrhoea and/or abdominal cramps after eating food served during the stakeholder consultation meeting in Accra on 21st November, 2016. The exposure status of all the members of the cohort was assessed by taking the food history of each respondent during the telephone interview. The data obtained was analysed using Epi Info 7. An environmental risk assessment was conducted to ascertain the source of the food contamination. Risks of foodborne infection from the foods eaten were determined using attack rates and odds ratios. Data was obtained from 54 people who consumed food served during the stakeholders’ meeting. Out of this population, 44 people reported with symptoms of food poisoning representing 81.45% (overall attack rate). The peak incubation period was seven hours with a minimum and maximum incubation periods of four and 17 hours, respectively. The commonly reported symptoms were diarrhoea (97.73%, 43/44), vomiting (84.09%, 37/44) and abdominal cramps (75.00%, 33/44). From the incubation period, duration of illness and the symptoms, toxin-mediated food poisoning was suspected. The environmental risk assessment of the implicated catering facility indicated a lack of time/temperature control, inadequate knowledge on food safety among workers and sanitation issues. Limited number of food samples was received for microbiological analysis. Multivariate analysis indicated that illness was significantly associated with the consumption of the snacks served (OR 14.78, P < 0.001). No stool and blood or samples of etiologic food were available for organism isolation; however, the suspected etiologic agent was Staphylococcus aureus or Clostridium perfringens. The outbreak could probably be due to the consumption of unwholesome snack (tuna sandwich or chicken. The contamination and/or growth of the etiologic agent in the snack may be due to the breakdown in cleanliness, time/temperature control and good food handling practices. Training of food handlers in basic food hygiene and safety is recommended.

Identifying Common Behavioural Traits of Lone-Wolves in Recent Terrorist Attacks in Europe

This article attempts to analyse behavioural traits of lone-wolves who struck and killed innocents in six different attacks in Europe in last nine months. The main objective of this study is to develop a profiling template in order to capture commonality of characteristics of these attackers. This study tries to understand the homogeneity of lone-wolves in terms of their social background and state of mind. The commonality among them can possibly be used to build a profiling template that could help detecting vulnerable persons who are prone to be self-radicalised or radicalised by someone else. The result of this study provides us an understanding of their commonality in terms of their state of mind and social characteristics.

Secure Hashing Algorithm and Advance Encryption Algorithm in Cloud Computing

Cloud computing is one of the most sharp and important movement in various computing technologies. It provides flexibility to users, cost effectiveness, location independence, easy maintenance, enables multitenancy, drastic performance improvements, and increased productivity. On the other hand, there are also major issues like security. Being a common server, security for a cloud is a major issue; it is important to provide security to protect user’s private data, and it is especially important in e-commerce and social networks. In this paper, encryption algorithms such as Advanced Encryption Standard algorithms, their vulnerabilities, risk of attacks, optimal time and complexity management and comparison with other algorithms based on software implementation is proposed. Encryption techniques to improve the performance of AES algorithms and to reduce risk management are given. Secure Hash Algorithms, their vulnerabilities, software implementations, risk of attacks and comparison with other hashing algorithms as well as the advantages and disadvantages between hashing techniques and encryption are given.

HelpMeBreathe: A Web-Based System for Asthma Management

We present in this paper a web-based system called “HelpMeBreathe” for managing asthma. The proposed system provides analytical tools, which allow better understanding of environmental triggers of asthma, hence better support of data-driven decision making. The developed system provides warning messages to a specific asthma patient if the weather in his/her area might cause any difficulty in breathing or could trigger an asthma attack. HelpMeBreathe collects, stores, and analyzes individuals’ moving trajectories and health conditions as well as environmental data. It then processes and displays the patients’ data through an analytical tool that leads to an effective decision making by physicians and other decision makers.

ParkedGuard: An Efficient and Accurate Parked Domain Detection System Using Graphical Locality Analysis and Coarse-To-Fine Strategy

As world wild internet has non-stop developments, making profit by lending registered domain names emerges as a new business in recent years. Unfortunately, the larger the market scale of domain lending service becomes, the riskier that there exist malicious behaviors or malwares hiding behind parked domains will be. Also, previous work for differentiating parked domain suffers two main defects: 1) too much data-collecting effort and CPU latency needed for features engineering and 2) ineffectiveness when detecting parked domains containing external links that are usually abused by hackers, e.g., drive-by download attack. Aiming for alleviating above defects without sacrificing practical usability, this paper proposes ParkedGuard as an efficient and accurate parked domain detector. Several scripting behavioral features were analyzed, while those with special statistical significance are adopted in ParkedGuard to make feature engineering much more cost-efficient. On the other hand, finding memberships between external links and parked domains was modeled as a graph mining problem, and a coarse-to-fine strategy was elaborately designed by leverage the graphical locality such that ParkedGuard outperforms the state-of-the-art in terms of both recall and precision rates.

Analysis of Threats in Interoperability of Medical Devices

Interoperable medical devices (IMDs) face threats due to the increased attack surface accessible by interoperability and the corresponding infrastructure. Initiating networking and coordination functionalities primarily modify medical systems' security properties. Understanding the threats is a vital first step in ultimately crafting security solutions for such systems. The key to this problem is coming up with some common types of threats or attacks with those of security and privacy, and providing this information as a roadmap. This paper analyses the security issues in interoperability of devices and presents the main types of threats that have to be considered to build a secured system.

Advantages of Neural Network Based Air Data Estimation for Unmanned Aerial Vehicles

Redundancy requirements for UAV (Unmanned Aerial Vehicle) are hardly faced due to the generally restricted amount of available space and allowable weight for the aircraft systems, limiting their exploitation. Essential equipment as the Air Data, Attitude and Heading Reference Systems (ADAHRS) require several external probes to measure significant data as the Angle of Attack or the Sideslip Angle. Previous research focused on the analysis of a patented technology named Smart-ADAHRS (Smart Air Data, Attitude and Heading Reference System) as an alternative method to obtain reliable and accurate estimates of the aerodynamic angles. This solution is based on an innovative sensor fusion algorithm implementing soft computing techniques and it allows to obtain a simplified inertial and air data system reducing external devices. In fact, only one external source of dynamic and static pressures is needed. This paper focuses on the benefits which would be gained by the implementation of this system in UAV applications. A simplification of the entire ADAHRS architecture will bring to reduce the overall cost together with improved safety performance. Smart-ADAHRS has currently reached Technology Readiness Level (TRL) 6. Real flight tests took place on ultralight aircraft equipped with a suitable Flight Test Instrumentation (FTI). The output of the algorithm using the flight test measurements demonstrates the capability for this fusion algorithm to embed in a single device multiple physical and virtual sensors. Any source of dynamic and static pressure can be integrated with this system gaining a significant improvement in terms of versatility.

Secure Distance Bounding Protocol on Ultra-WideBand Based Mapping Code

Ultra WidBand-IR physical layer technology has seen a great development during the last decade which makes it a promising candidate for short range wireless communications, as they bring considerable benefits in terms of connectivity and mobility. However, like all wireless communication they suffer from vulnerabilities in terms of security because of the open nature of the radio channel. To face these attacks, distance bounding protocols are the most popular counter measures. In this paper, we presented a protocol based on distance bounding to thread the most popular attacks: Distance Fraud, Mafia Fraud and Terrorist fraud. In our work, we study the way to adapt the best secure distance bounding protocols to mapping code of ultra-wideband (TH-UWB) radios. Indeed, to ameliorate the performances of the protocol in terms of security communication in TH-UWB, we combine the modified protocol to ultra-wideband impulse radio technology (IR-UWB). The security and the different merits of the protocols are analyzed.

Stackelberg Security Game for Optimizing Security of Federated Internet of Things Platform Instances

This paper presents an approach for optimal cyber security decisions to protect instances of a federated Internet of Things (IoT) platform in the cloud. The presented solution implements the repeated Stackelberg Security Game (SSG) and a model called Stochastic Human behaviour model with AttRactiveness and Probability weighting (SHARP). SHARP employs the Subjective Utility Quantal Response (SUQR) for formulating a subjective utility function, which is based on the evaluations of alternative solutions during decision-making. We augment the repeated SSG (including SHARP and SUQR) with a reinforced learning algorithm called Naïve Q-Learning. Naïve Q-Learning belongs to the category of active and model-free Machine Learning (ML) techniques in which the agent (either the defender or the attacker) attempts to find an optimal security solution. In this way, we combine GT and ML algorithms for discovering optimal cyber security policies. The proposed security optimization components will be validated in a collaborative cloud platform that is based on the Industrial Internet Reference Architecture (IIRA) and its recently published security model.

A Robust Hybrid Blind Digital Image Watermarking System Using Discrete Wavelet Transform and Contourlet Transform

In this paper, a hybrid blind digital watermarking system using Discrete Wavelet Transform (DWT) and Contourlet Transform (CT) has been implemented and tested. The implemented combined digital watermarking system has been tested against five common types of image attacks. The performance evaluation shows improved results in terms of imperceptibility, robustness, and high tolerance against these attacks; accordingly, the system is very effective and applicable.

Detection of New Attacks on Ubiquitous Services in Cloud Computing and Countermeasures

Cloud computing provides infrastructure to the enterprise through the Internet allowing access to cloud services at anytime and anywhere. This pervasive aspect of the services, the distributed nature of data and the wide use of information make cloud computing vulnerable to intrusions that violate the security of the cloud. This requires the use of security mechanisms to detect malicious behavior in network communications and hosts such as intrusion detection systems (IDS). In this article, we focus on the detection of intrusion into the cloud sing IDSs. We base ourselves on client authentication in the computing cloud. This technique allows to detect the abnormal use of ubiquitous service and prevents the intrusion of cloud computing. This is an approach based on client authentication data. Our IDS provides intrusion detection inside and outside cloud computing network. It is a double protection approach: The security user node and the global security cloud computing.

Experimental Study on Strength and Durability Properties of Bio-Self-Cured Fly Ash Based Concrete under Aggressive Environments

High performance concrete is not only characterized by its high strength, workability, and durability but also by its smartness in performance without human care since the first day. If the concrete can cure on its own without external curing without compromising its strength and durability, then it is said to be high performance self-curing concrete. In this paper, an attempt is made on the performance study of internally cured concrete using biomaterials, namely Spinacea pleracea and Calatropis gigantea as self-curing agents, and it is compared with the performance of concrete with existing self-cure chemical, namely polyethylene glycol. The present paper focuses on workability, strength, and durability study on M20, M30, and M40 grade concretes replacing 30% of fly ash for cement. The optimum dosage of Spinacea pleracea, Calatropis gigantea, and polyethylene glycol was taken as 0.6%, 0.24%, and 0.3% by weight of cement from the earlier research studies. From the slump tests performed, it was found that there is a minimum variation between conventional concrete and self-cured concrete. The strength activity index is determined by keeping compressive strength of conventionally cured concrete for 28 days as unity and observed that, for self-cured concrete, it is more than 1 after 28 days and more than 1.15 after 56 days because of secondary reaction of fly ash. The performance study of concretes in aggressive environment like acid attack, sea water attack, and chloride attack was made, and the results are positive and encouraging in bio-self-cured concretes which are ecofriendly, cost effective, and high performance materials.

Mechanical Strengths of Self-Compacting Mortars Prepared with the Pozzolanic Cement in Aggressive Environments

The objective of this research is to study the physical and mechanical properties and durability of self-compacting mortars prepared by substituting a part of cement up to a percentage of 30% pozzolan according to different Blaine specific surface area (SSB1=7000 cm2/g and SSB=9000 cm2/g)). Order to evaluate durability, mortars were subjected to chemical attacks in various aggressive environments, a solution of a mixture of nitric acid and ammonium nitrate (HNO3 + NH4NO3) and a magnesium sulfate salt solution (MgSO4)) with a concentration of 10%, for a period of one month. This study is complemented by a comparative study of the durability of mortars elaborated with sulphate resistant cement (SRC). The results show that these mortars develop long-term, mechanical and chemical resistance better than mortars based Portland cement with 5% gypsum (CEM 1) and SRC. We found that the mass losses are lowest in mortars elaborated with pozzolanic cement (30% substitution with SSB2) in both of chemical attack solutions (3.28% in the solution acid and 1.16% in the salt solution) and the compressive strength gains of 14.68% and 8.5% respectively in the two media. This is due to the action of pozzolan which fixes portlandite to form hydrated calcium silicate (CSH) from the hydration of tricalcic silicate (C3S).

A POX Controller Module to Collect Web Traffic Statistics in SDN Environment

Software Defined Networking (SDN) is a new norm of networks. It is designed to facilitate the way of managing, measuring, debugging and controlling the network dynamically, and to make it suitable for the modern applications. Generally, measurement methods can be divided into two categories: Active and passive methods. Active measurement method is employed to inject test packets into the network in order to monitor their behaviour (ping tool as an example). Meanwhile the passive measurement method is used to monitor the traffic for the purpose of deriving measurement values. The measurement methods, both active and passive, are useful for the collection of traffic statistics, and monitoring of the network traffic. Although there has been a work focusing on measuring traffic statistics in SDN environment, it was only meant for measuring packets and bytes rates for non-web traffic. In this study, a feasible method will be designed to measure the number of packets and bytes in a certain time, and facilitate obtaining statistics for both web traffic and non-web traffic. Web traffic refers to HTTP requests that use application layer; while non-web traffic refers to ICMP and TCP requests. Thus, this work is going to be more comprehensive than previous works. With a developed module on POX OpenFlow controller, information will be collected from each active flow in the OpenFlow switch, and presented on Command Line Interface (CLI) and wireshark interface. Obviously, statistics that will be displayed on CLI and on wireshark interfaces include type of protocol, number of bytes and number of packets, among others. Besides, this module will show the number of flows added to the switch whenever traffic is generated from and to hosts in the same statistics list. In order to carry out this work effectively, our Python module will send a statistics request message to the switch requesting its current ports and flows statistics in every five seconds; while the switch will reply with the required information in a message called statistics reply message. Thus, POX controller will be notified and updated with any changes could happen in the entire network in a very short time. Therefore, our aim of this study is to prepare a list for the important statistics elements that are collected from the whole network, to be used for any further researches; particularly, those that are dealing with the detection of the network attacks that cause a sudden rise in the number of packets and bytes like Distributed Denial of Service (DDoS).

Two-Stage Launch Vehicle Trajectory Modeling for Low Earth Orbit Applications

This paper presents a study on the trajectory of a two stage launch vehicle. The study includes dynamic responses of motion parameters as well as the variation of angles affecting the orientation of the launch vehicle (LV). LV dynamic characteristics including state vector variation with corresponding altitude and velocity for the different LV stages separation, as well as the angle of attack and flight path angles are also discussed. A flight trajectory study for the drop zone of first stage and the jettisoning of fairing are introduced in the mathematical modeling to study their effect. To increase the accuracy of the LV model, atmospheric model is used taking into consideration geographical location and the values of solar flux related to the date and time of launch, accurate atmospheric model leads to enhancement of the calculation of Mach number, which affects the drag force over the LV. The mathematical model is implemented on MATLAB based software (Simulink). The real available experimental data are compared with results obtained from the theoretical computation model. The comparison shows good agreement, which proves the validity of the developed simulation model; the maximum error noticed was generally less than 10%, which is a result that can lead to future works and enhancement to decrease this level of error.

A Video Watermarking Algorithm Based on Chaotic and Wavelet Neural Network

This paper presented a video watermarking algorithm based on wavelet chaotic neural network. First, to enhance binary image’s security, the algorithm encrypted it with double chaotic based on Arnold and Logistic map, Then, the host video was divided into some equal frames and distilled the key frame through chaotic sequence which generated by Logistic. Meanwhile, we distilled the low frequency coefficients of luminance component and self-adaptively embedded the processed image watermark into the low frequency coefficients of the wavelet transformed luminance component with the wavelet neural network. The experimental result suggested that the presented algorithm has better invisibility and robustness against noise, Gaussian filter, rotation, frame loss and other attacks.