A multi hop mobile ad hoc network is a peer to peer network of wireless nodes where nodes are required to perform routing activity to provide end to end connectivity among nodes. As mobile nodes are constrained by battery power and... more
A multi hop mobile ad hoc network is a peer to peer network of wireless nodes where nodes are required to perform routing activity to provide end to end connectivity among nodes. As mobile nodes are constrained by battery power and bandwidth, some nodes may behave selfishly and deny forwarding packets for other nodes, even though they expect other nodes to forward packets to keep network connected. We simulate two selfish behaviors on top of Dynamic Source Routing (DSR) protocol: the first, selfish nodes do not forward data or control packets (routing packets) for other nodes and the second, selfish nodes turn off their network interface card when they have nothing to communicate. We compare the energy saving to the selfish nodes for both the misbehaviors and show that the second selfish behavior saves more energy. This is important result because most of the cooperation enforcement mechanisms in literature, except PCOM [2], address the first selfish behavior. Also, the second selfish behavior can be easily done by layman users without any protocol level changes. Secondly, with our simulation study we find that in dense mobile ad hoc networks where route breakages are frequent, routing control packets consume significant fraction of node energy and selfish behavior by certain number of nodes reduce the overall routing overhead in network which in turn result in energy saving for both, well behaving nodes and selfish nodes.
Grid is an advanced wide area parallel distributed computing environment where unused processor cycles and underutilized storage of numerous computers are utilized efficiently which act as a supercomputer. Security is the most important... more
Grid is an advanced wide area parallel distributed computing environment where unused processor cycles and underutilized storage of numerous computers are utilized efficiently which act as a supercomputer. Security is the most important concern in Grid computing environment. Among all other security issues authentication is the first step of security requirement for any Grid environment to validate the user. This paper proposes an authentication scheme for Grid environment. The proposed authentication scheme optimises the security required for the entry level user and prevents malicious user from entering into the Grid environment.
In this paper I am going to first explain in detail the role of Game Theory over Social Network Analysis. Then I will look into the Predictive model of Artificial Neural network & will explain in details that how this model will be used... more
In this paper I am going to first explain in detail the role of Game Theory over Social Network Analysis. Then I will look into the Predictive model of Artificial Neural network & will explain in details that how this model will be used to develop a mathematical model which will fairly and efficiently allocate the required rate of bandwidth to all the users in a Multiuser Network System. Afterwards, I will propose some newly designed algorithms which will help me in the implementation of the mathematical model. The testing result of the implementation will compare our proposed architecture with the existing model. Finally, I will end this discussion by self-estimating our proposed model and judging the future scope of the same.
To implement security in cloud platform, the significance of virtualization can’t be neglected. The hypervisors, which is also known as virtual machine monitor, offer a handful of facilities to configure the virtual machines to redesign... more
To implement security in cloud platform, the significance of virtualization can’t be neglected. The hypervisors, which is also known as virtual machine monitor, offer a handful of facilities to configure the virtual machines to redesign the communication channel through which they can interact with each other or with the internet. We have studied how the facilities of virtualization can be optimally used to secure the communication between virtual machines and internet in a private cloud infrastructure. In this regard, we have tried to enhance the communication mechanism through constructing a cloud infrastructure framework. This paper deals with the isolation of virtual instances to improve the private cloud security through prevention from spreading infections between virtual machines (VMs) & also between VM & internet. Moreover, our proposal focuses on the filtering of inflow and outflow traffic to and from the outside world through a dedicated VM of a host implemented in layered...
1Dept. of Computer Science and Engineering, , Assam down town University, Assam, India 2Assistant Professor, Dept. of Computer Science and Engineering, Assam down town University, Assam, India... more
1Dept. of Computer Science and Engineering, , Assam down town University, Assam, India 2Assistant Professor, Dept. of Computer Science and Engineering, Assam down town University, Assam, India ---------------------------------------------------------------------***--------------------------------------------------------------------Abstract With technology getting better and advanced every single day through intensive inventions and discoveries carried out by experts all around the world, our lives are getting modified and bent more towards being dependent on technology and making the best out of it. With such a level of enhancements, it will be really illogical, if we still struggle to interact with our systems through various contemporary I/O devices (input/output). As, we need to interact with our smart systems almost every hour of the day and it is really necessary to use hands-free techniques other than the use of peripheral devices to communicate with these computer systems; te...
Cloud computing has become an inevitable part of information technology (IT) and other non-IT businesses. Every computational facility is now provided as computing services by the cloud service providers (CSPs). While providing these... more
Cloud computing has become an inevitable part of information technology (IT) and other non-IT businesses. Every computational facility is now provided as computing services by the cloud service providers (CSPs). While providing these services, CSPs try to maintain efficiency by keeping the performance index as high as possible. Although virtualization technology has made this possible by applying resource provisioning techniques, but this approach is still hectic and expertise-dependent. In this paper, we propose an efficient infrastructure as code (IaC) based novel framework for optimizing resource utilization percentage through an automatic provisioning approach. This framework maximizes the resource utilization and performance metrics of virtualized cloud platforms. In this context, we have presented some mathematical formulations and considering those, we addressed our designed programming model for the proposed IaC-based framework. Extensive simulations have been performed to establish the novelty of the proposed approach. We have also presented a comparative study by considering two data centers, one with IaC based proposed model and the other is a conventional contemporary model. Result analysis confirms the performance of our proposed IaC-based framework.
In this paper we deal with misbehaving nodes in mobile ad hoc networks (MANETs) that drop packets supposed to be relayed, whose purpose may be either saving their resources or launching a DoS attack. We propose a new solution to monitor,... more
In this paper we deal with misbehaving nodes in mobile ad hoc networks (MANETs) that drop packets supposed to be relayed, whose purpose may be either saving their resources or launching a DoS attack. We propose a new solution to monitor, detect, and safely isolate such misbehaving nodes.in our approach watchdog method is used for observation of nodes behavior. And also varying threshold based policy is used for save nodes falsely accused in dense network. All strategies are described in detail in various paper sections with results.
An online bookstore software projects that acts as a central database containing various books in stock along with their title, author and cost. This project is a website that acts as a central book store. This web project is developed... more
An online bookstore software projects that acts as a central database containing various books in stock along with their title, author and cost. This project is a website that acts as a central book store. This web project is developed using asp.net as the front end and sql as a back-end. The sql database stores various book related details. A user visiting the website can see a wide range of books arranged in respective categories. The user may select desired book and view its price. The user may even search for specific books on the website. Once the user selects a book , he then has to fill in a form and the book is booked for the user. Hardware Components: Processor -i3 Hard Disk -5 GB Memory -1GB RAM Advantages:
Real-time detection of objects is receiving growing attention. The pedestrian is the most critical object that needs to be detecting and tracking by autonomous vehicles. The major challenges to this mission are caused by the difference in... more
Real-time detection of objects is receiving growing attention. The pedestrian is the most critical object that needs to be detecting and tracking by autonomous vehicles. The major challenges to this mission are caused by the difference in objects like pedestrians in age, gender, clothing, lighting, backgrounds, and occlusion. This paper starts with a brief introduction of problem-related to pedestrians, objects detection framework and Neural Networks Algorithms, and Real-Time Systems. And we focus on pedestrians as moving objects that need to detect, track, and solve problems related to computer vision. And based on our study we present a suggested solution for solving problems related to Pedestrians Detection in real-time particular. These techniques aim to be used in many applications such as Autonomous Vehicles, and Advanced Driver Assistance Systems (ADAS).
In present academic system, regular class attendance of students plays a significant role in performance assessment and quality monitoring. The conventional methods practiced in most of the educational institutions are by calling names,... more
In present academic system, regular class attendance of students plays a significant role in performance assessment and quality monitoring. The conventional methods practiced in most of the educational institutions are by calling names, which is highly time-consuming. The human face is one of the natural traits that can uniquely identify an individual. Therefore, it is used to trace identity as the possibilities for multi-faces to deviate or being duplicated is low. In this project, face databases will be created to pump data into the recognizer algorithm. Then, during the attendance taking session, faces will be compared against the database to seek for identity. The proses start at specific time, and when an individual is identified, its attendance will be taken down automatically saving necessary information into a database system. At the end of the day . In the proposed system, a Convolutional Neural Network (CNN) is used to detect faces in images, and deep learning is used in the process. Thus, the computer can recognize faces automatically. The main purpose of this project is to build a face recognition-based attendance monitoring system for Syrian Private University to enhance and upgrade the current attendance process into more efficient and effective as compared to before.
There are sub-classes of pedestrians that can be defined and it is important to distinguish between them for the detection in autonomous vehicle applications, such as elderly, and children, to reduce the risk of collision. It is necessary... more
There are sub-classes of pedestrians that can be defined and it is important to distinguish between them for the detection in autonomous vehicle applications, such as elderly, and children, to reduce the risk of collision. It is necessary to talk about effective pedestrian tracking besides detection so that object remains accurately monitored, here the effective pre-trained algorithms come to achieve this goal in real-time. In this paper, we make a comparison between the detection and tracking algorithms, we applied the transfer learning technique to train the detection model on new sub-classes, after making Images augmentation in previous work [1], we got better results in detection, reached 0.81 mAP in real-time by using Yolov5 model, with a good tracking performance by the tracking algorithm dependent on detection Deep-SORT.
There are sub-classes of pedestrians that can be defined and it is important to distinguish between them for the detection in autonomous vehicle applications, such as elderly, and children, to reduce the risk of collision. It is necessary... more
There are sub-classes of pedestrians that can be defined and it is important to distinguish between them for the detection in autonomous vehicle applications, such as elderly, and children, to reduce the risk of collision. It is necessary to talk about effective pedestrian tracking besides detection so that object remains accurately monitored, here the effective pre-trained algorithms come to achieve this goal in real-time. In this paper, we make a comparison between the detection and tracking algorithms, we applied the transfer learning technique to train the detection model on new sub-classes, after making Images augmentation in previous work, we got better results in detection, reached 0.81 mAP in real-time by using Yolov5 model, with a good tracking performance by the tracking algorithm dependent on detection Deep-SORT.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permit...
Effective collision risk reduction in autonomous vehicles relies on robust and straightforward pedestrian tracking. Challenges posed by occlusion and switching scenarios significantly impede the reliability of pedestrian tracking. In the... more
Effective collision risk reduction in autonomous vehicles relies on robust and straightforward pedestrian tracking. Challenges posed by occlusion and switching scenarios significantly impede the reliability of pedestrian tracking. In the current study, we strive to enhance the reliability and also the efficacy of pedestrian tracking in complex scenarios. Particularly, we introduce a new pedestrian tracking algorithm that leverages both the YOLOv8 (You Only Look Once) object detector technique and the StrongSORT algorithm, which is an advanced deep learning multi-object tracking (MOT) method. Our findings demonstrate that StrongSORT, an enhanced version of the DeepSORT MOT algorithm, substantially improves tracking accuracy through meticulous hyperparameter tuning.Overall, the experimental results reveal that the proposed algorithm is an effective and efficient method for pedestrian tracking, particularly in complex scenarios encountered in the MOT16 and MOT17 datasets. The combined use of Yolov8 and StrongSORT contributes to enhanced tracking results, emphasizing the synergistic relationship between detection and tracking modules.
With the quickly increase development of website and web application, internet user utilize that benefits. They make their all day to day daily life activity like reading a newspaper, online shopping, online payment etc. Hence the chances... more
With the quickly increase development of website and web application, internet user utilize that benefits. They make their all day to day daily life activity like reading a newspaper, online shopping, online payment etc. Hence the chances of the users to get caught in the web threat its called phishing attack. There for the phishing detection is necessary. There is no conclusive solution to detect phishing. In this paper we present novel technique to detect phishing attack and compare with the other existing technique. Our proposed framework work on combine algorithm of rule mining and SVM.
Organization like financial, medical, airline, and banking are require a very high quality software. If failure happen in this system cause high financial cost and affect the people lives. So it is important to develop the fault free... more
Organization like financial, medical, airline, and banking are require a very high quality software. If failure happen in this system cause high financial cost and affect the people lives. So it is important to develop the fault free software. Software fault detection is important for the software quality. Limited testing resources used to assurance the quality of software. The classification model is trained using the dataset. We tend to propose the framework which consist data pre-processing approach with Support vector Machine (SVM) classifier. In Data pre-processing relevance analysis perform using feature raking and redundant feature remove using the Fuzzy C-Means clustering techniques.
