29 research outputs found
Using Hybrid Cryptography and Improved EAACK Develop Secure Intrusion Detection System for MANETs
No full textAssociation rule mining methods for applying encryption techniques in transaction dataset
No full textProposed Framework for Quality Assurance System with Duplicate Bug Detection
No full textWhen project are having so cost. Many times the problem of bug will get occur. So, it becomes very important to have proper quality assurance system(QAS).Poorly designed quality assurance systems may exchange wrong information between developers. The purpose of this paper is to make understandings of different quality assurance systems and explain them, to find out problems present in them and give proper direction for improvement so as attract customers, raise customers satisfaction, to reduce downtime .This Paper proposes a framework to detect duplicate bug. detection, QAS, bugs
Survey and comparative analysis of phishing detection techniques: current trends, challenges, and future directions
No full textIn the age of digital communication, scams such as phishing continue to be a problem, necessitating the need for ever-more-advanced detection techniques to safeguard sensitive data. Examining several methods now in use, this review article groups them according to the application (email, web server, mail server, or browser-based). It explores the advantages and disadvantages of behavior-based, heuristic-based, machine learning (ML)-based, and signature-based techniques and offers a comparative evaluation of their efficacy. The essay delves deeper into the latest developments in phishing detection research, such as ML-powered social media exploration and real-time website analysis. The evaluation goes beyond just identifying detecting techniques; it also includes a data-driven analysis. In particular, random forest and support vector machines are ML algorithms that regularly produce results with high accuracy for detecting phishing attempts. Metrics like as recall, F1-score, and precision show how well these algorithms. Furthermore, specialised techniques such as heuristic-based and cantina-based approaches provide remarkable performance, underscoring the possibility of additional research in this field. Future research explores improved phishing detection through: better accuracy with ML, integrating new technologies, analyzing user behavior. A hybrid approach combining these techniques offers a stronger defense
Prevention in Healthcare: An Explainable AI Approach
No full textIntrusion prevention is a critical aspect of maintaining the security of healthcare systems, especially in the context of sensitive patient data. Explainable AI can provide a way to improve the effectiveness of intrusion prevention by using machine learning algorithms to detect and prevent security breaches in healthcare systems. This approach not only helps ensure the confidentiality, integrity, and availability of patient data but also supports regulatory compliance. By providing clear and interpretable explanations for its decisions, explainable AI can enable healthcare professionals to understand the reasoning behind the intrusion detection system's alerts and take appropriate action. This paper explores the application of explainable AI for intrusion prevention in healthcare and its potential benefits for maintaining the security of healthcare systems
Intrusion prevention system using convolutional neural network for wireless sensor network
No full textNow-a-days, there is exponential growth in the field of wireless sensor network. In wireless sensor networks (WSN’s), most of communication happen through wireless media hence probability of attacks increases drastically. With the help of intrusion prevention system, we can classify user activities into two categories, normal and suspicious activity. There is need to design effective intrusion prevention system by exploring deep learning for WSN. This research aims to deal with proposing algorithms and techniques for intrusion prevention system using deep packet inspection based on deep learning. In this, we have proposed deep learning model using convolutional neural network. The proposed model includes two steps, intrusion detection and intrusion prevention. The proposed model learns useful feature representations from large amount of labeled data and then classifies them. In this work, convolutional neural network is used to prevent intrusion for WSN. To evaluate and check the effectiveness of the proposed system, the wireless sensor network dataset (WSNDS) dataset is used and the tests are performed. The test results show that proposed system has an accuracy of 97% and works better than existing system. The proposed work can be used as future benchmark for the deep learning and intrusion prevention research communities
EFFICIENT REBROADCASTING USING TRUSTWORTHINESS OF NODE WITH NEIGHBOUR KNOWLEDGE IN MANET
No full textMobile Ad hoc network is an infrastructure less communication network with limited resources. To maintain virtual infrastructure for communication broadcasting mechanisms is used. Due to lack of energy efficiency in Mobile Ad hoc network, there is a need to develop an efficient broadcasting model which enhances energy efficiency. Also nodes with malicious behaviour cause an internal threat that disobeys the standard and degrades the performance of routing protocols. This paper introduced an enhanced rebroadcasting algorithm, where rebroadcasting decision for next hop is immediate or delayed on the basis of trust value and energy level of particular node. This approach helps to decrease number of rebroadcast, energy consumption and also enhances security. The decision is made with trust value associated with node, their remaining energy and total number of uncovered nodes.
https://www.ijiert.org/paper-details?paper_id=14037
A SURVEY ON MULTIPATH ROUTING STRATEGY IN MULTI-HOPWIRELESS SENSOR NETWORK
No full textThere are number of routing protocols proposed for the data transmission in WSN. Initially single path routing schemes with number of variations are proposed. Still there were some drawbacks in single path routing. Single path routing was unable to provide the reliability and high throughput. Also security level was not considered while routing. Recently, to remove the drawbacks of the single path routing new routing technique is proposed called as multipath routing
EFFICIENT REBROADCASTING USING TRUSTWORTHINESS OF NODE WITH NEIGHBOUR KNOWLEDGE IN MANET
No full textMobile Ad hoc network is an infrastructure less communication network with limited resources. To maintain virtual infrastructure for communication broadcasting mechanisms is used. Due to lack of energy efficiency in Mobile Ad hoc network, there is a need to develop an efficient broadcasting model which enhances energy efficiency. Also nodes with malicious behaviour cause an internal threat that disobeys the standard and degrades the performance of routing protocols. This paper introduced an enhanced rebroadcasting algorithm, where rebroadcasting decision for next hop is immediate or delayed on the basis of trust value and energy level of particular node. This approach helps to decrease number of rebroadcast, energy consumption and also enhances security
EFFICIENT REBROADCASTING USING TRUSTWORTHINESS OF NODE WITH NEIGHBOUR KNOWLEDGE IN MANET
No full textMobile Ad hoc network is an infrastructure less communication network with limited resources. To maintain virtual infrastructure for communication broadcasting mechanisms is used. Due to lack of energy efficiency in Mobile Ad hoc network, there is a need to develop an efficient broadcasting model which enhances energy efficiency. Also nodes with malicious behaviour cause an internal threat that disobeys the standard and degrades the performance of routing protocols. This paper introduced an enhanced rebroadcasting algorithm, where rebroadcasting decision for next hop is immediate or delayed on the basis of trust value and energy level of particular node. This approach helps to decrease number of rebroadcast, energy consumption and also enhances security
