This document proposes an efficient model for detecting and identifying cyber attacks in wireless networks using deep learning approaches. The model is designed to perform feature selection and classification on network data to detect malicious behavior. The model architecture includes input, hidden, and output layers for feature extraction, and uses a random forest classifier trained on the NSL KDD Cup dataset. Experimental results using the KDD Cup and NSL-KDD datasets show the model can accurately classify network behaviors and detect cyber attacks with over 82% accuracy.
Hybrid Technique for Detection of Denial of Service (DOS) Attack in Wireless ...Eswar Publications
Wireless Sensor Network (WSNs) are deployed at aggressive environments which are vulnerable to various security attacks such as Wormholes, Denial of Attacks and Sybil Attacks. There are various intrusion detection techniques that are used to identify attacks in a network with high accuracy level. This paper has focused on Denial of Service attack, since it is the most common attack that affects the environment severely. Therefore a new hybrid technique combining Hidden Markov Model with Ant Colony Optimization (HMM+ACO) has been
proposed that gives improved performance than the other techniques.
Co-operative Wireless Intrusion Detection System Using MIBs From SNMPIJNSA Journal
In emerging technology of Internet, security issues are becoming more challenging. In case of wired LAN it is somewhat in control, but in case of wireless networks due to exponential growth in attacks, it has made difficult to detect such security loopholes. Wireless network security is being addressed using firewalls, encryption techniques and wired IDS (Intrusion Detection System) methods. But the approaches which were used in wired network were not successful in producing effective results for wireless networks. It is so because of features of wireless network such as open medium, dynamic changing topology, cooperative algorithms, lack of centralized monitoring and management point, and lack of a clear line of defense etc. So, there is need for new approach which will efficiently detect intrusion in wireless network. Efficiency can be achieved by implementing distributive, co-operative based, multi-agent IDS. The proposed system supports all these three features. It includes mobile agents for intrusion detection which uses SNMP (Simple network Management Protocol) and MIB (Management Information Base) variables for mobile wireless networks.
Hybrid Technique for Detection of Denial of Service (DOS) Attack in Wireless ...Eswar Publications
Wireless Sensor Network (WSNs) are deployed at aggressive environments which are vulnerable to various security attacks such as Wormholes, Denial of Attacks and Sybil Attacks. There are various intrusion detection techniques that are used to identify attacks in a network with high accuracy level. This paper has focused on Denial of Service attack, since it is the most common attack that affects the environment severely. Therefore a new hybrid technique combining Hidden Markov Model with Ant Colony Optimization (HMM+ACO) has been
proposed that gives improved performance than the other techniques.
Co-operative Wireless Intrusion Detection System Using MIBs From SNMPIJNSA Journal
In emerging technology of Internet, security issues are becoming more challenging. In case of wired LAN it is somewhat in control, but in case of wireless networks due to exponential growth in attacks, it has made difficult to detect such security loopholes. Wireless network security is being addressed using firewalls, encryption techniques and wired IDS (Intrusion Detection System) methods. But the approaches which were used in wired network were not successful in producing effective results for wireless networks. It is so because of features of wireless network such as open medium, dynamic changing topology, cooperative algorithms, lack of centralized monitoring and management point, and lack of a clear line of defense etc. So, there is need for new approach which will efficiently detect intrusion in wireless network. Efficiency can be achieved by implementing distributive, co-operative based, multi-agent IDS. The proposed system supports all these three features. It includes mobile agents for intrusion detection which uses SNMP (Simple network Management Protocol) and MIB (Management Information Base) variables for mobile wireless networks.
Multi-stage secure clusterhead selection using discrete rule-set against unkn...IJECEIAES
Security is the rising concern of the wireless network as there are various forms of reonfigurable network that is arised from it. Wireless sensor network (WSN) is one such example that is found to be an integral part of cyber-physical system in upcoming times. After reviewing the existing system, it can be seen that there are less dominant and robust solutions towards mitigating the threats of upcoming applications of WSN. Therefore, this paper introduces a simple and cost-effective modelling of a security system that offers security by ensuring secure selection of clusterhead during the data aggregation process in WSN. The proposed system also makes construct a rule-set in order to learn the nature of the communication iin order to have a discrete knowledge about the intensity of adversaries. With an aid of simulation-based approach over MEMSIC nodes, the proposed system was proven to offer reduced energy consumption with good data delivery performance in contrast to existing approach.
Classification Rule Discovery Using Ant-Miner Algorithm: An Application Of N...IJMER
Enormous studies on intrusion detection have widely applied data mining techniques to
finding out the useful knowledge automatically from large amount of databases, while few studies have
proposed classification data mining approaches. In an actual risk assessment process, the discovery of
intrusion detection prediction knowledge from experts is still regarded as an important task because
experts’ predictions depend on their subjectivity. Traditional statistical techniques and artificial
intelligence techniques are commonly used to solve this classification decision making. This paper
proposes an ant-miner based data mining method for discovering network intrusion detection rules from
large dataset. The obtained result of this experiment shows that clearly the ant-miner is superior than
ID3, J48, ADtree, BFtree, Simple cart. Although different classification models have been developed for
network intrusion detection, each of them has its strength and weakness, including the most commonly
applied Support Vector Machine(SVM)method and the clustering based on Self Organized Ant Colony
Network (CSOACN).Our algorithm is implemented and evaluated using a standard bench mark KDD99
dataset. Experiments show that ant-miner algorithm out performs than other methods in terms of both
classification rate and accuracy
This paper presents a brief study of recent advances in wireless network security issues. The paper makes a number of contributions to the wireless networking field. First, it studies the 4G mail threats and risk and their design decisions. Second, the security of 4G architecture with next generation network security and 8-security dimensions of 4G network. Third, security issues and possible threats on 4G are discussed. Finally, we proposed four layer security model which manages to ensure more secure packets transmission by taking all the necessary security measures.
Integrated Framework for Secure and Energy Efficient Communication System in ...IJECEIAES
Irrespective of different forms and strategies implementing for securing Wireless Sensor Network (WSN), there are very less strategies that offers cost effective security over heterogeneous network. Therefore, this paper presents an integrated set of different processes that emphasize over secure routing, intellectual and delay-compensated routing, and optimization principle with a sole intention of securing the communication to and from the sensor nodes during data aggregation. The processed system advocates the non-usage of complex cryptography and encourages the usage of probability their and analytical modelling in order to render more practical implementation. The simulated outcome of study shows that proposed system offers reduced delay, more throughputs, and reduced energy consumption in contrast to existing system.
An intrusion detection system for packet and flow based networks using deep n...IJECEIAES
Study on deep neural networks and big data is merging now by several aspects to enhance the capabilities of intrusion detection system (IDS). Many IDS models has been introduced to provide security over big data. This study focuses on the intrusion detection in computer networks using big datasets. The advent of big data has agitated the comprehensive assistance in cyber security by forwarding a brunch of affluent algorithms to classify and analysis patterns and making a better prediction more efficiently. In this study, to detect intrusion a detection model has been propounded applying deep neural networks. We applied the suggested model on the latest dataset available at online, formatted with packet based, flow based data and some additional metadata. The dataset is labeled and imbalanced with 79 attributes and some classes having much less training samples compared to other classes. The proposed model is build using Keras and Google Tensorflow deep learning environment. Experimental result shows that intrusions are detected with the accuracy over 99% for both binary and multiclass classification with selected best features. Receiver operating characteristics (ROC) and precision-recall curve average score is also 1. The outcome implies that Deep Neural Networks offers a novel research model with great accuracy for intrusion detection model, better than some models presented in the literature.
Efficient Data Aggregation in Wireless Sensor NetworksIJAEMSJORNAL
Sensor network is a term used to refer to a heterogeneous system combining tiny sensors and actuators with general/special-purpose processors. Sensor networks are assumed to grow in size to include hundreds or thousands of low-power, low-cost, static or mobile nodes. This system is created by observing that for any densely deployed sensor network, high redundancy exists in the gathered information from the sensor nodes that are close to each other we have exploited the redundancy and designed schemes to secure different kinds of aggregation processing against both inside and outside attacks.
Multi-stage secure clusterhead selection using discrete rule-set against unkn...IJECEIAES
Security is the rising concern of the wireless network as there are various forms of reonfigurable network that is arised from it. Wireless sensor network (WSN) is one such example that is found to be an integral part of cyber-physical system in upcoming times. After reviewing the existing system, it can be seen that there are less dominant and robust solutions towards mitigating the threats of upcoming applications of WSN. Therefore, this paper introduces a simple and cost-effective modelling of a security system that offers security by ensuring secure selection of clusterhead during the data aggregation process in WSN. The proposed system also makes construct a rule-set in order to learn the nature of the communication iin order to have a discrete knowledge about the intensity of adversaries. With an aid of simulation-based approach over MEMSIC nodes, the proposed system was proven to offer reduced energy consumption with good data delivery performance in contrast to existing approach.
Classification Rule Discovery Using Ant-Miner Algorithm: An Application Of N...IJMER
Enormous studies on intrusion detection have widely applied data mining techniques to
finding out the useful knowledge automatically from large amount of databases, while few studies have
proposed classification data mining approaches. In an actual risk assessment process, the discovery of
intrusion detection prediction knowledge from experts is still regarded as an important task because
experts’ predictions depend on their subjectivity. Traditional statistical techniques and artificial
intelligence techniques are commonly used to solve this classification decision making. This paper
proposes an ant-miner based data mining method for discovering network intrusion detection rules from
large dataset. The obtained result of this experiment shows that clearly the ant-miner is superior than
ID3, J48, ADtree, BFtree, Simple cart. Although different classification models have been developed for
network intrusion detection, each of them has its strength and weakness, including the most commonly
applied Support Vector Machine(SVM)method and the clustering based on Self Organized Ant Colony
Network (CSOACN).Our algorithm is implemented and evaluated using a standard bench mark KDD99
dataset. Experiments show that ant-miner algorithm out performs than other methods in terms of both
classification rate and accuracy
This paper presents a brief study of recent advances in wireless network security issues. The paper makes a number of contributions to the wireless networking field. First, it studies the 4G mail threats and risk and their design decisions. Second, the security of 4G architecture with next generation network security and 8-security dimensions of 4G network. Third, security issues and possible threats on 4G are discussed. Finally, we proposed four layer security model which manages to ensure more secure packets transmission by taking all the necessary security measures.
Integrated Framework for Secure and Energy Efficient Communication System in ...IJECEIAES
Irrespective of different forms and strategies implementing for securing Wireless Sensor Network (WSN), there are very less strategies that offers cost effective security over heterogeneous network. Therefore, this paper presents an integrated set of different processes that emphasize over secure routing, intellectual and delay-compensated routing, and optimization principle with a sole intention of securing the communication to and from the sensor nodes during data aggregation. The processed system advocates the non-usage of complex cryptography and encourages the usage of probability their and analytical modelling in order to render more practical implementation. The simulated outcome of study shows that proposed system offers reduced delay, more throughputs, and reduced energy consumption in contrast to existing system.
An intrusion detection system for packet and flow based networks using deep n...IJECEIAES
Study on deep neural networks and big data is merging now by several aspects to enhance the capabilities of intrusion detection system (IDS). Many IDS models has been introduced to provide security over big data. This study focuses on the intrusion detection in computer networks using big datasets. The advent of big data has agitated the comprehensive assistance in cyber security by forwarding a brunch of affluent algorithms to classify and analysis patterns and making a better prediction more efficiently. In this study, to detect intrusion a detection model has been propounded applying deep neural networks. We applied the suggested model on the latest dataset available at online, formatted with packet based, flow based data and some additional metadata. The dataset is labeled and imbalanced with 79 attributes and some classes having much less training samples compared to other classes. The proposed model is build using Keras and Google Tensorflow deep learning environment. Experimental result shows that intrusions are detected with the accuracy over 99% for both binary and multiclass classification with selected best features. Receiver operating characteristics (ROC) and precision-recall curve average score is also 1. The outcome implies that Deep Neural Networks offers a novel research model with great accuracy for intrusion detection model, better than some models presented in the literature.
Efficient Data Aggregation in Wireless Sensor NetworksIJAEMSJORNAL
Sensor network is a term used to refer to a heterogeneous system combining tiny sensors and actuators with general/special-purpose processors. Sensor networks are assumed to grow in size to include hundreds or thousands of low-power, low-cost, static or mobile nodes. This system is created by observing that for any densely deployed sensor network, high redundancy exists in the gathered information from the sensor nodes that are close to each other we have exploited the redundancy and designed schemes to secure different kinds of aggregation processing against both inside and outside attacks.
Simulations on Computer Network An Improved Study in the Simulator Methodolog...YogeshIJTSRD
Generally a network simulator is used to analyse the performance and behaviour of a network. The Simulation software plays a vital role in real world implementation. The hardware setup of network topologies are very costly and strenuous to modify often. The simulators act as the protocols for a system. The simulators in network such as Ns 2, Ns 3, OMNeT , NetSim, J SIM, REAL, OPNET, OMNEST, QualNetTraNS, NTCUns etc. It is quite a tedious process to select network simulator that is based up on the requirement for a users specified job. This paper gives a comparison and a general analysis of various network simulators. J. Sumitha | S. Swathi | Ellakkiya. M "Simulations on Computer Network: An Improved Study in the Simulator Methodologies and Their Applications" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-4 , June 2021, URL: https://www.ijtsrd.compapers/ijtsrd41176.pdf Paper URL: https://www.ijtsrd.comcomputer-science/simulation/41176/simulations-on-computer-network-an-improved-study-in-the-simulator-methodologies-and-their-applications/j-sumitha
Overview of the fundamental roles in Hydropower generation and the components involved in wider Electrical Engineering.
This paper presents the design and construction of hydroelectric dams from the hydrologist’s survey of the valley before construction, all aspects and involved disciplines, fluid dynamics, structural engineering, generation and mains frequency regulation to the very transmission of power through the network in the United Kingdom.
Author: Robbie Edward Sayers
Collaborators and co editors: Charlie Sims and Connor Healey.
(C) 2024 Robbie E. Sayers
Hybrid optimization of pumped hydro system and solar- Engr. Abdul-Azeez.pdffxintegritypublishin
Advancements in technology unveil a myriad of electrical and electronic breakthroughs geared towards efficiently harnessing limited resources to meet human energy demands. The optimization of hybrid solar PV panels and pumped hydro energy supply systems plays a pivotal role in utilizing natural resources effectively. This initiative not only benefits humanity but also fosters environmental sustainability. The study investigated the design optimization of these hybrid systems, focusing on understanding solar radiation patterns, identifying geographical influences on solar radiation, formulating a mathematical model for system optimization, and determining the optimal configuration of PV panels and pumped hydro storage. Through a comparative analysis approach and eight weeks of data collection, the study addressed key research questions related to solar radiation patterns and optimal system design. The findings highlighted regions with heightened solar radiation levels, showcasing substantial potential for power generation and emphasizing the system's efficiency. Optimizing system design significantly boosted power generation, promoted renewable energy utilization, and enhanced energy storage capacity. The study underscored the benefits of optimizing hybrid solar PV panels and pumped hydro energy supply systems for sustainable energy usage. Optimizing the design of solar PV panels and pumped hydro energy supply systems as examined across diverse climatic conditions in a developing country, not only enhances power generation but also improves the integration of renewable energy sources and boosts energy storage capacities, particularly beneficial for less economically prosperous regions. Additionally, the study provides valuable insights for advancing energy research in economically viable areas. Recommendations included conducting site-specific assessments, utilizing advanced modeling tools, implementing regular maintenance protocols, and enhancing communication among system components.
Vaccine management system project report documentation..pdfKamal Acharya
The Division of Vaccine and Immunization is facing increasing difficulty monitoring vaccines and other commodities distribution once they have been distributed from the national stores. With the introduction of new vaccines, more challenges have been anticipated with this additions posing serious threat to the already over strained vaccine supply chain system in Kenya.
Explore the innovative world of trenchless pipe repair with our comprehensive guide, "The Benefits and Techniques of Trenchless Pipe Repair." This document delves into the modern methods of repairing underground pipes without the need for extensive excavation, highlighting the numerous advantages and the latest techniques used in the industry.
Learn about the cost savings, reduced environmental impact, and minimal disruption associated with trenchless technology. Discover detailed explanations of popular techniques such as pipe bursting, cured-in-place pipe (CIPP) lining, and directional drilling. Understand how these methods can be applied to various types of infrastructure, from residential plumbing to large-scale municipal systems.
Ideal for homeowners, contractors, engineers, and anyone interested in modern plumbing solutions, this guide provides valuable insights into why trenchless pipe repair is becoming the preferred choice for pipe rehabilitation. Stay informed about the latest advancements and best practices in the field.
COLLEGE BUS MANAGEMENT SYSTEM PROJECT REPORT.pdfKamal Acharya
The College Bus Management system is completely developed by Visual Basic .NET Version. The application is connect with most secured database language MS SQL Server. The application is develop by using best combination of front-end and back-end languages. The application is totally design like flat user interface. This flat user interface is more attractive user interface in 2017. The application is gives more important to the system functionality. The application is to manage the student’s details, driver’s details, bus details, bus route details, bus fees details and more. The application has only one unit for admin. The admin can manage the entire application. The admin can login into the application by using username and password of the admin. The application is develop for big and small colleges. It is more user friendly for non-computer person. Even they can easily learn how to manage the application within hours. The application is more secure by the admin. The system will give an effective output for the VB.Net and SQL Server given as input to the system. The compiled java program given as input to the system, after scanning the program will generate different reports. The application generates the report for users. The admin can view and download the report of the data. The application deliver the excel format reports. Because, excel formatted reports is very easy to understand the income and expense of the college bus. This application is mainly develop for windows operating system users. In 2017, 73% of people enterprises are using windows operating system. So the application will easily install for all the windows operating system users. The application-developed size is very low. The application consumes very low space in disk. Therefore, the user can allocate very minimum local disk space for this application.
Immunizing Image Classifiers Against Localized Adversary Attacksgerogepatton
This paper addresses the vulnerability of deep learning models, particularly convolutional neural networks
(CNN)s, to adversarial attacks and presents a proactive training technique designed to counter them. We
introduce a novel volumization algorithm, which transforms 2D images into 3D volumetric representations.
When combined with 3D convolution and deep curriculum learning optimization (CLO), itsignificantly improves
the immunity of models against localized universal attacks by up to 40%. We evaluate our proposed approach
using contemporary CNN architectures and the modified Canadian Institute for Advanced Research (CIFAR-10
and CIFAR-100) and ImageNet Large Scale Visual Recognition Challenge (ILSVRC12) datasets, showcasing
accuracy improvements over previous techniques. The results indicate that the combination of the volumetric
input and curriculum learning holds significant promise for mitigating adversarial attacks without necessitating
adversary training.
Event Management System Vb Net Project Report.pdfKamal Acharya
In present era, the scopes of information technology growing with a very fast .We do not see any are untouched from this industry. The scope of information technology has become wider includes: Business and industry. Household Business, Communication, Education, Entertainment, Science, Medicine, Engineering, Distance Learning, Weather Forecasting. Carrier Searching and so on.
My project named “Event Management System” is software that store and maintained all events coordinated in college. It also helpful to print related reports. My project will help to record the events coordinated by faculties with their Name, Event subject, date & details in an efficient & effective ways.
In my system we have to make a system by which a user can record all events coordinated by a particular faculty. In our proposed system some more featured are added which differs it from the existing system such as security.