The serious issue in the field of wireless communication is the security and how an organization implements the steps against security breach. The major attack on any organization is Man in the Middle attack which is difficult to manage. This attack leads to number of unauthorized access points, called rogue access points which are not detected easily. In this paper, we proposed a Hopfield Neural Network approach for an automatic detection of these rogue access points in wireless networking. Here, we store the passwords of the authentic devices in the weight matrix format and match the patterns at the time of login. Simulation experiment shows that this method is more secure than the traditional one in WLAN.
This document summarizes various soft computing techniques that can be used for intrusion detection, including fuzzy logic, graph-based approaches, and neural networks. Fuzzy logic can be used to classify parameters and detect anomalies by comparing normal and new fuzzy association rule sets. Graph-based approaches model network traffic as graphs of nodes and edges and use clustering algorithms to detect anomalies. Neural networks can be trained on audit log data to recognize normal behavior and detect deviations that may indicate attacks. These soft computing methods aim to improve on signature-based detection by learning patterns of normal network activity and detecting anomalies.
This document discusses implementing an Intrusion Detection System (IDS) for WiFi security. The IDS would detect vulnerable activities of devices connected to the network and alert the system.
The paper provides background on common WiFi security vulnerabilities and attacks. It then describes the components and methodology of an IDS, including using sensors to monitor network traffic, analyzers to evaluate the traffic for attacks, and user interfaces to manage the system. The proposed IDS would collect network information using Wireshark, detect intrusions, and respond to threats to improve security for wireless networks.
Intrusion Detection Systems (IDSs) have become widely recognized as powerful tools for identifying, deterring and deflecting malicious attacks over the network. Intrusion detection systems (IDSs) are designed and installed to aid in deterring or mitigating the damage that can be caused by hacking, or breaking into sensitive IT systems. . The attacks can come from outsider attackers on the Internet, authorized insiders who misuse the privileges that have been given them and unauthorized insiders who attempt to gain unauthorized privileges. IDSs cannot be used in isolation, but must be part of a larger framework of IT security measures. Essential to almost every intrusion detection system is the ability to search through packets and identify content that matches known attacks. Space and time efficient string matching algorithms are therefore important for identifying these packets at line rate. In this paper we examine string matching algorithm and their use for Intrusion Detection. Keywords: System Design, Network Algorithm
IRJET- A Review on Intrusion Detection SystemIRJET Journal
This document provides a review of intrusion detection systems (IDS). It discusses the purpose of IDS in monitoring networks to detect anomalous behavior and security exploits. The document outlines the basic components and architecture of IDS, including sensors to collect data, an analyzer to examine data for intrusions, a knowledgebase of activity logs and signatures, and a user interface. It also covers different types of attacks IDS aims to detect, such as denial-of-service, spoofing and probing attacks. Finally, the document summarizes the typical workflow of an IDS in collecting data, selecting relevant features for analysis, analyzing data for intrusions, and taking appropriate actions in response.
IRJET- Phishdect & Mitigator: SDN based Phishing Attack DetectionIRJET Journal
The document proposes a new system called PhishDect and Mitigator to detect and mitigate phishing attacks using software-defined networking (SDN). It uses deep packet inspection techniques and a convolutional neural network (CNN) to classify phishing signatures. Traffic is directed through either a "store and forward" or "forward and inspect" mode. In store and forward mode, packets are stored and inspected before forwarding. In forward and inspect mode, packets are forwarded first and then a copy is inspected. The system aims to overcome limitations of existing phishing detection methods.
Detecting and Preventing Attacks Using Network Intrusion Detection SystemsCSCJournals
Intrusion detection is an important technology in business sector as well as an active area of research. It is an important tool for information security. A Network Intrusion Detection System is used to monitor networks for attacks or intrusions and report these intrusions to the administrator in order to take evasive action. Today computers are part of networked; distributed systems that may span multiple buildings sometimes located thousands of miles apart. The network of such a system is a pathway for communication between the computers in the distributed system. The network is also a pathway for intrusion. This system is designed to detect and combat some common attacks on network systems. It follows the signature based IDs methodology for ascertaining attacks. A signature based IDS will monitor packets on the network and compare them against a database of signatures or attributes from known malicious threats. It has been implemented in VC++. In this system the attack log displays the list of attacks to the administrator for evasive action. This system works as an alert device in the event of attacks directed towards an entire network.
A Modular Approach To Intrusion Detection in Homogenous Wireless NetworkIOSR Journals
This document discusses a modular approach to intrusion detection in homogeneous wireless networks. It begins by introducing wireless networks and the need for intrusion detection systems (IDS) due to security vulnerabilities. It then discusses different types of IDS, including signature-based detection that identifies known attacks, and anomaly-based detection that identifies deviations from normal behavior but can result in high false positives. The document proposes a modular approach combining advantages of signature-based and anomaly-based detection for high detection rates and low false positives. Requirements for IDS in wireless networks are also outlined.
International Journal of Engineering Research and Development (IJERD)IJERD Editor
journal publishing, how to publish research paper, Call For research paper, international journal, publishing a paper, IJERD, journal of science and technology, how to get a research paper published, publishing a paper, publishing of journal, publishing of research paper, reserach and review articles, IJERD Journal, How to publish your research paper, publish research paper, open access engineering journal, Engineering journal, Mathemetics journal, Physics journal, Chemistry journal, Computer Engineering, Computer Science journal, how to submit your paper, peer reviw journal, indexed journal, reserach and review articles, engineering journal, www.ijerd.com, research journals,
yahoo journals, bing journals, International Journal of Engineering Research and Development, google journals, hard copy of journal
This document summarizes various soft computing techniques that can be used for intrusion detection, including fuzzy logic, graph-based approaches, and neural networks. Fuzzy logic can be used to classify parameters and detect anomalies by comparing normal and new fuzzy association rule sets. Graph-based approaches model network traffic as graphs of nodes and edges and use clustering algorithms to detect anomalies. Neural networks can be trained on audit log data to recognize normal behavior and detect deviations that may indicate attacks. These soft computing methods aim to improve on signature-based detection by learning patterns of normal network activity and detecting anomalies.
This document discusses implementing an Intrusion Detection System (IDS) for WiFi security. The IDS would detect vulnerable activities of devices connected to the network and alert the system.
The paper provides background on common WiFi security vulnerabilities and attacks. It then describes the components and methodology of an IDS, including using sensors to monitor network traffic, analyzers to evaluate the traffic for attacks, and user interfaces to manage the system. The proposed IDS would collect network information using Wireshark, detect intrusions, and respond to threats to improve security for wireless networks.
Intrusion Detection Systems (IDSs) have become widely recognized as powerful tools for identifying, deterring and deflecting malicious attacks over the network. Intrusion detection systems (IDSs) are designed and installed to aid in deterring or mitigating the damage that can be caused by hacking, or breaking into sensitive IT systems. . The attacks can come from outsider attackers on the Internet, authorized insiders who misuse the privileges that have been given them and unauthorized insiders who attempt to gain unauthorized privileges. IDSs cannot be used in isolation, but must be part of a larger framework of IT security measures. Essential to almost every intrusion detection system is the ability to search through packets and identify content that matches known attacks. Space and time efficient string matching algorithms are therefore important for identifying these packets at line rate. In this paper we examine string matching algorithm and their use for Intrusion Detection. Keywords: System Design, Network Algorithm
IRJET- A Review on Intrusion Detection SystemIRJET Journal
This document provides a review of intrusion detection systems (IDS). It discusses the purpose of IDS in monitoring networks to detect anomalous behavior and security exploits. The document outlines the basic components and architecture of IDS, including sensors to collect data, an analyzer to examine data for intrusions, a knowledgebase of activity logs and signatures, and a user interface. It also covers different types of attacks IDS aims to detect, such as denial-of-service, spoofing and probing attacks. Finally, the document summarizes the typical workflow of an IDS in collecting data, selecting relevant features for analysis, analyzing data for intrusions, and taking appropriate actions in response.
IRJET- Phishdect & Mitigator: SDN based Phishing Attack DetectionIRJET Journal
The document proposes a new system called PhishDect and Mitigator to detect and mitigate phishing attacks using software-defined networking (SDN). It uses deep packet inspection techniques and a convolutional neural network (CNN) to classify phishing signatures. Traffic is directed through either a "store and forward" or "forward and inspect" mode. In store and forward mode, packets are stored and inspected before forwarding. In forward and inspect mode, packets are forwarded first and then a copy is inspected. The system aims to overcome limitations of existing phishing detection methods.
Detecting and Preventing Attacks Using Network Intrusion Detection SystemsCSCJournals
Intrusion detection is an important technology in business sector as well as an active area of research. It is an important tool for information security. A Network Intrusion Detection System is used to monitor networks for attacks or intrusions and report these intrusions to the administrator in order to take evasive action. Today computers are part of networked; distributed systems that may span multiple buildings sometimes located thousands of miles apart. The network of such a system is a pathway for communication between the computers in the distributed system. The network is also a pathway for intrusion. This system is designed to detect and combat some common attacks on network systems. It follows the signature based IDs methodology for ascertaining attacks. A signature based IDS will monitor packets on the network and compare them against a database of signatures or attributes from known malicious threats. It has been implemented in VC++. In this system the attack log displays the list of attacks to the administrator for evasive action. This system works as an alert device in the event of attacks directed towards an entire network.
A Modular Approach To Intrusion Detection in Homogenous Wireless NetworkIOSR Journals
This document discusses a modular approach to intrusion detection in homogeneous wireless networks. It begins by introducing wireless networks and the need for intrusion detection systems (IDS) due to security vulnerabilities. It then discusses different types of IDS, including signature-based detection that identifies known attacks, and anomaly-based detection that identifies deviations from normal behavior but can result in high false positives. The document proposes a modular approach combining advantages of signature-based and anomaly-based detection for high detection rates and low false positives. Requirements for IDS in wireless networks are also outlined.
International Journal of Engineering Research and Development (IJERD)IJERD Editor
journal publishing, how to publish research paper, Call For research paper, international journal, publishing a paper, IJERD, journal of science and technology, how to get a research paper published, publishing a paper, publishing of journal, publishing of research paper, reserach and review articles, IJERD Journal, How to publish your research paper, publish research paper, open access engineering journal, Engineering journal, Mathemetics journal, Physics journal, Chemistry journal, Computer Engineering, Computer Science journal, how to submit your paper, peer reviw journal, indexed journal, reserach and review articles, engineering journal, www.ijerd.com, research journals,
yahoo journals, bing journals, International Journal of Engineering Research and Development, google journals, hard copy of journal
TACTiCS_WP Security_Addressing Security in SDN EnvironmentSaikat Chaudhuri
This document discusses addressing security concerns in SDN environments. It proposes an approach using an application on the SDN controller to monitor alerts from an IDS, analyze network traffic samples, and automate blocking of malicious flows. The application would function similarly to a security operations center (SOC) by correlating security events and taking action. The implementation is demonstrated using the OpenDaylight controller and Mininet virtual network, with SNORT for intrusion detection and sFlow for traffic sampling.
A firewall protects a network by blocking unauthorized access, while an intrusion detection system (IDS) detects intrusion attempts without blocking. A firewall can block connections, while an IDS only detects packets and alerts administrators. Firewalls perform actions like blocking and filtering, while IDSs just detect connections. IDS types include network IDS, host IDS, and protocol/anomaly-based IDS, while firewall types include packet filtering, stateful inspection, and application firewalls.
Network Based Intrusion Detection and Prevention Systems: Attack Classificati...researchinventy
Complex and common security attackshave become a common issue nowadays. Success rate of detecting these attacks through existing tools seems to be decreasing due to simple rule-bases Some attacks are too complex to identify for today’s firewall systems.This paper highlights various security attacks classification techniques pertaining to TCP/IP protocol stack, it also covers an existingintrusion detection techniques used for intrusion detection , and features of various open source and commercial Network Intrusion Detection and Prevention (IDPS) tools. Finally paper concludes with comparison and evaluation of an open source and commercial IDPS tools and techniques which are used to detect and prevent the security attacks.
IRJET- Software Defined Network: DDOS Attack DetectionIRJET Journal
This document discusses software defined networks (SDNs) and detecting distributed denial-of-service (DDoS) attacks in SDNs. It provides background on SDN architecture and how DDoS attacks work. The paper aims to address risks of DDoS attacks in SDNs and focuses on detection. It describes existing DDoS attack techniques and solutions. The document proposes using algorithms like TCM-KNN and DPTCM-KNN for detection of attacks in network traffic flows, and compares the two algorithms using parameters like packet length and response time.
REAL-TIME INTRUSION DETECTION SYSTEM FOR BIG DATAijp2p
The objective of the proposed system is to integrate the high volume of data along with the important
considerations like monitoring a wide array of heterogeneous security. When a real time cyber attack
occurred, the Intrusion Detection System automatically store the log in distributed environment and
monitor the log with existing intrusion dictionary. At the same time the system will check and categorize the
severity of the log to high, medium, and low respectively. After the categorization, the system will
automatically take necessary action against the user-unit with respect to the severity of the log. The
advantage of the system is that it utilize anomaly detection, evaluates data and issue alert message or
reports based on abnormal behaviour.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Pattern Analysis and Signature Extraction for Intrusion Attacks on Web ServicesIJNSA Journal
The increasing popularity of web service technology is attracting hackers and attackers to hack the web services and the servers on which they run. Organizations are therefore facing the challenge of implementing adequate security for Web Services. A major threat is that of intruders which may maliciously try to access the data or services. The automated methods of signature extraction extract the binary pattern blindly resulting in more false positives. In this paper a semi automated approach is proposed to analyze the attacks and generate signatures for web services. For data collection, apart from the conventional SOAP data loggers, honeypots are also used that collect small data which is of high value. To filter out the most suspicious part of the data, SVM based classifier is employed to aid the system administrator. By applying an attack signature algorithm on the filtered data, a more balanced attack signature is extracted that results in fewer false positives and negatives. It helps the Security Administrator to identify the web services that are vulnerable or are attacked more frequently.
IRJET- HTTP Flooding Attack Detection using Data Mining TechniquesIRJET Journal
This document discusses using data mining techniques to detect HTTP flooding attacks, a type of distributed denial of service (DDoS) attack. It describes how HTTP floods work by overloading servers with requests from compromised devices called "zombies." The document then outlines several data mining techniques that can be used for detection, including intrusion detection systems (IDS) and IP traceback. IDS uses techniques like misuse detection, anomaly detection, and signature-based detection to monitor network traffic. IP traceback aims to trace attack packets back to their origin. The document concludes that continued improvement in data mining techniques can help better handle DDoS and DoS attacks.
IRJET- Survey on Phishing Attack Detection and MitigationIRJET Journal
The document discusses phishing attacks and methods to detect and mitigate them. It provides background on phishing, describing types like spear phishing and causes. It then summarizes previous research on phishing detection techniques, including blacklisting approaches and using Snort as an intrusion detection system. The document also introduces the challenges of static detection rules not keeping up with evolving phishing attacks and the need for faster detection and mitigation times.
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
The use of honeynet to detect exploited systems (basic version)amar koppal
This document discusses the use of honeynets to detect exploited systems and hackers. It begins with an abstract and introduction on the topic. It then provides definitions of key terms like honeynet and honeypot. It describes the principles of data capture and data control that honeynets rely on. It discusses the differences between first (GEN I) and second (GEN II) generation honeynets. It outlines the typical honeynet architecture including honeypots and honeywalls. It explains how honeynets work to study attacker activities and methods. Finally, it discusses some advantages like high value data and simplicity, and disadvantages like narrow field of view of using honeynets.
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
Detection of Session Hijacking and IP Spoofing Using Sensor Nodes and Cryptog...IOSR Journals
This document discusses techniques for detecting session hijacking and IP spoofing attacks in wireless networks. It proposes using sensor nodes to detect fake access points, which are used to perform session hijacking. It also describes adding protection against IP spoofing through public-private key cryptography during key exchange. The document provides background on session hijacking, IP spoofing, and related work on detecting these attacks. It then describes the proposed mechanism in more detail.
A Collaborative Intrusion Detection System for Cloud Computingijsrd.com
Cloud computing is a computing paradigm that shifts drastically from traditional computing architecture. Although this new computing paradigm brings many advantages like utility computing model but the design in not flawless and hence suffers from not only many known computer vulnerabilities but also introduces unique information confidentiality, integrity and availability risks as well due its inherent design paradigm. To provide secure and reliable services in cloud computing environment is an important issue. To counter a variety of attacks, especially large-scale coordinated attacks, a framework of Collaborative Intrusion Detection System (IDS) is proposed. The proposed system could reduce the impact of these kinds of attacks through providing timely notifications about new intrusions to Cloud users' systems. To provide such ability, IDSs in the cloud computing regions both correlate alerts from multiple elementary detectors and exchange knowledge of interconnected Clouds with each other.
Intrusion Detection and Prevention System in an Enterprise NetworkOkehie Collins
This document describes a project on intrusion detection and prevention systems in an enterprise network. It was submitted by Okehie Collins Obinna to the Department of Computer Science at the Federal University of Technology in partial fulfillment of a Bachelor of Technology degree in Computer Science. The project analyzes intrusion detection and prevention technologies used in enterprise networks and designs a desktop application to monitor a computer network system for possible intrusions and provide an interface for a network administrator.
This document summarizes and evaluates techniques for identifying adversary attacks in wireless sensor networks. It begins by describing common types of attacks and issues with cryptographic identification methods. It then evaluates existing localization techniques like Received Signal Strength (RSS) and spatial correlation analysis. Specifically, it proposes the Generalized Model for Attack Detection (GMFAD) which uses Partitioning Around Medoids (PaM) clustering on RSS readings to detect multiple attackers. It also presents the Coherent Detection and Localization Model (CDAL-M) which integrates PaM with localization algorithms like RADAR and Bayesian networks to determine attacker locations. The document analyzes these techniques' effectiveness at detecting and localizing multiple adversary attackers in wireless sensor networks.
Intrusion Detection System (IDS) is meant to be a software application which monitors the network or system activities and finds if any malicious operations take place. Tremendous growth and practice of internet raises concerns about how to protect and communicate the digital data in a safe manner. Nowadays, hackers use different types of attacks for getting the valuable information. Many intrusion detection techniques, methods and algorithms assist to identify these attacks. This main objective of this paper is to provide a complete study about the description of intrusion detection, history, life cycle, types of intrusion detection methods, types of attacks, different tools and techniques, research needs, tasks and applications
This document discusses security threats to wireless networks. It begins by introducing wireless network vulnerabilities and various threats including accidental association, malicious associations, passive eavesdropping, ad-hoc networks, MAC spoofing, man-in-the-middle attacks, and denial of service attacks. It then discusses the consequences of poor wireless network security and strategies to improve security such as using encryption, passwords, firewalls, and educating users. The document provides details on specific threats and countermeasures organizations can take to secure their wireless networks.
Augment Method for Intrusion Detection around KDD Cup 99 DatasetIRJET Journal
This document discusses augmenting methods for intrusion detection using the KDD Cup 99 dataset. It aims to improve detection accuracy and reduce false positives. The key points are:
- It analyzes detection precision and true positive rate (recall) for different attack classes in the KDD Cup 99 dataset to help improve dataset accuracy.
- Experimental results show the contribution of each attack class to recall and precision, which can help optimize the dataset to achieve highest accuracy with lowest false positives.
- The goal is to enhance testing of detection models and improve data quality to advance offline intrusion detection capabilities.
Wireless Security Needs For Enterprisesshrutisreddy
This document discusses improving wireless security for enterprise/corporate users compared to home users. It analyzes security threats like encryption attacks and outlines techniques like WEP, WPA, and WPA2. The key points are:
1) Wireless networks are vulnerable to attacks using tools like AirSnort but techniques like WPA2 with AES encryption provide stronger security.
2) Corporate networks require robust security as they contain sensitive customer data, while basic techniques like WEP may suffice for home networks.
3) The document recommends home users enable security settings and use WPA-PSK encryption to protect their wireless networks.
This seminar covers network security from its history to modern techniques. It introduces network security, the need for it due to increased internet usage, and basic concepts like authentication and common attacks. The document outlines early security protocols and why confidentiality, availability and integrity of information were important as the internet grew. It discusses how to secure a network from outside intrusion and different authentication techniques. Specific security methods like WPA, WEP and how hackers have evolved are also summarized. The advantages and challenges of network security are presented, as well as the importance of a well-designed security architecture for an organization's network.
TACTiCS_WP Security_Addressing Security in SDN EnvironmentSaikat Chaudhuri
This document discusses addressing security concerns in SDN environments. It proposes an approach using an application on the SDN controller to monitor alerts from an IDS, analyze network traffic samples, and automate blocking of malicious flows. The application would function similarly to a security operations center (SOC) by correlating security events and taking action. The implementation is demonstrated using the OpenDaylight controller and Mininet virtual network, with SNORT for intrusion detection and sFlow for traffic sampling.
A firewall protects a network by blocking unauthorized access, while an intrusion detection system (IDS) detects intrusion attempts without blocking. A firewall can block connections, while an IDS only detects packets and alerts administrators. Firewalls perform actions like blocking and filtering, while IDSs just detect connections. IDS types include network IDS, host IDS, and protocol/anomaly-based IDS, while firewall types include packet filtering, stateful inspection, and application firewalls.
Network Based Intrusion Detection and Prevention Systems: Attack Classificati...researchinventy
Complex and common security attackshave become a common issue nowadays. Success rate of detecting these attacks through existing tools seems to be decreasing due to simple rule-bases Some attacks are too complex to identify for today’s firewall systems.This paper highlights various security attacks classification techniques pertaining to TCP/IP protocol stack, it also covers an existingintrusion detection techniques used for intrusion detection , and features of various open source and commercial Network Intrusion Detection and Prevention (IDPS) tools. Finally paper concludes with comparison and evaluation of an open source and commercial IDPS tools and techniques which are used to detect and prevent the security attacks.
IRJET- Software Defined Network: DDOS Attack DetectionIRJET Journal
This document discusses software defined networks (SDNs) and detecting distributed denial-of-service (DDoS) attacks in SDNs. It provides background on SDN architecture and how DDoS attacks work. The paper aims to address risks of DDoS attacks in SDNs and focuses on detection. It describes existing DDoS attack techniques and solutions. The document proposes using algorithms like TCM-KNN and DPTCM-KNN for detection of attacks in network traffic flows, and compares the two algorithms using parameters like packet length and response time.
REAL-TIME INTRUSION DETECTION SYSTEM FOR BIG DATAijp2p
The objective of the proposed system is to integrate the high volume of data along with the important
considerations like monitoring a wide array of heterogeneous security. When a real time cyber attack
occurred, the Intrusion Detection System automatically store the log in distributed environment and
monitor the log with existing intrusion dictionary. At the same time the system will check and categorize the
severity of the log to high, medium, and low respectively. After the categorization, the system will
automatically take necessary action against the user-unit with respect to the severity of the log. The
advantage of the system is that it utilize anomaly detection, evaluates data and issue alert message or
reports based on abnormal behaviour.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Pattern Analysis and Signature Extraction for Intrusion Attacks on Web ServicesIJNSA Journal
The increasing popularity of web service technology is attracting hackers and attackers to hack the web services and the servers on which they run. Organizations are therefore facing the challenge of implementing adequate security for Web Services. A major threat is that of intruders which may maliciously try to access the data or services. The automated methods of signature extraction extract the binary pattern blindly resulting in more false positives. In this paper a semi automated approach is proposed to analyze the attacks and generate signatures for web services. For data collection, apart from the conventional SOAP data loggers, honeypots are also used that collect small data which is of high value. To filter out the most suspicious part of the data, SVM based classifier is employed to aid the system administrator. By applying an attack signature algorithm on the filtered data, a more balanced attack signature is extracted that results in fewer false positives and negatives. It helps the Security Administrator to identify the web services that are vulnerable or are attacked more frequently.
IRJET- HTTP Flooding Attack Detection using Data Mining TechniquesIRJET Journal
This document discusses using data mining techniques to detect HTTP flooding attacks, a type of distributed denial of service (DDoS) attack. It describes how HTTP floods work by overloading servers with requests from compromised devices called "zombies." The document then outlines several data mining techniques that can be used for detection, including intrusion detection systems (IDS) and IP traceback. IDS uses techniques like misuse detection, anomaly detection, and signature-based detection to monitor network traffic. IP traceback aims to trace attack packets back to their origin. The document concludes that continued improvement in data mining techniques can help better handle DDoS and DoS attacks.
IRJET- Survey on Phishing Attack Detection and MitigationIRJET Journal
The document discusses phishing attacks and methods to detect and mitigate them. It provides background on phishing, describing types like spear phishing and causes. It then summarizes previous research on phishing detection techniques, including blacklisting approaches and using Snort as an intrusion detection system. The document also introduces the challenges of static detection rules not keeping up with evolving phishing attacks and the need for faster detection and mitigation times.
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
The use of honeynet to detect exploited systems (basic version)amar koppal
This document discusses the use of honeynets to detect exploited systems and hackers. It begins with an abstract and introduction on the topic. It then provides definitions of key terms like honeynet and honeypot. It describes the principles of data capture and data control that honeynets rely on. It discusses the differences between first (GEN I) and second (GEN II) generation honeynets. It outlines the typical honeynet architecture including honeypots and honeywalls. It explains how honeynets work to study attacker activities and methods. Finally, it discusses some advantages like high value data and simplicity, and disadvantages like narrow field of view of using honeynets.
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
Detection of Session Hijacking and IP Spoofing Using Sensor Nodes and Cryptog...IOSR Journals
This document discusses techniques for detecting session hijacking and IP spoofing attacks in wireless networks. It proposes using sensor nodes to detect fake access points, which are used to perform session hijacking. It also describes adding protection against IP spoofing through public-private key cryptography during key exchange. The document provides background on session hijacking, IP spoofing, and related work on detecting these attacks. It then describes the proposed mechanism in more detail.
A Collaborative Intrusion Detection System for Cloud Computingijsrd.com
Cloud computing is a computing paradigm that shifts drastically from traditional computing architecture. Although this new computing paradigm brings many advantages like utility computing model but the design in not flawless and hence suffers from not only many known computer vulnerabilities but also introduces unique information confidentiality, integrity and availability risks as well due its inherent design paradigm. To provide secure and reliable services in cloud computing environment is an important issue. To counter a variety of attacks, especially large-scale coordinated attacks, a framework of Collaborative Intrusion Detection System (IDS) is proposed. The proposed system could reduce the impact of these kinds of attacks through providing timely notifications about new intrusions to Cloud users' systems. To provide such ability, IDSs in the cloud computing regions both correlate alerts from multiple elementary detectors and exchange knowledge of interconnected Clouds with each other.
Intrusion Detection and Prevention System in an Enterprise NetworkOkehie Collins
This document describes a project on intrusion detection and prevention systems in an enterprise network. It was submitted by Okehie Collins Obinna to the Department of Computer Science at the Federal University of Technology in partial fulfillment of a Bachelor of Technology degree in Computer Science. The project analyzes intrusion detection and prevention technologies used in enterprise networks and designs a desktop application to monitor a computer network system for possible intrusions and provide an interface for a network administrator.
This document summarizes and evaluates techniques for identifying adversary attacks in wireless sensor networks. It begins by describing common types of attacks and issues with cryptographic identification methods. It then evaluates existing localization techniques like Received Signal Strength (RSS) and spatial correlation analysis. Specifically, it proposes the Generalized Model for Attack Detection (GMFAD) which uses Partitioning Around Medoids (PaM) clustering on RSS readings to detect multiple attackers. It also presents the Coherent Detection and Localization Model (CDAL-M) which integrates PaM with localization algorithms like RADAR and Bayesian networks to determine attacker locations. The document analyzes these techniques' effectiveness at detecting and localizing multiple adversary attackers in wireless sensor networks.
Intrusion Detection System (IDS) is meant to be a software application which monitors the network or system activities and finds if any malicious operations take place. Tremendous growth and practice of internet raises concerns about how to protect and communicate the digital data in a safe manner. Nowadays, hackers use different types of attacks for getting the valuable information. Many intrusion detection techniques, methods and algorithms assist to identify these attacks. This main objective of this paper is to provide a complete study about the description of intrusion detection, history, life cycle, types of intrusion detection methods, types of attacks, different tools and techniques, research needs, tasks and applications
This document discusses security threats to wireless networks. It begins by introducing wireless network vulnerabilities and various threats including accidental association, malicious associations, passive eavesdropping, ad-hoc networks, MAC spoofing, man-in-the-middle attacks, and denial of service attacks. It then discusses the consequences of poor wireless network security and strategies to improve security such as using encryption, passwords, firewalls, and educating users. The document provides details on specific threats and countermeasures organizations can take to secure their wireless networks.
Augment Method for Intrusion Detection around KDD Cup 99 DatasetIRJET Journal
This document discusses augmenting methods for intrusion detection using the KDD Cup 99 dataset. It aims to improve detection accuracy and reduce false positives. The key points are:
- It analyzes detection precision and true positive rate (recall) for different attack classes in the KDD Cup 99 dataset to help improve dataset accuracy.
- Experimental results show the contribution of each attack class to recall and precision, which can help optimize the dataset to achieve highest accuracy with lowest false positives.
- The goal is to enhance testing of detection models and improve data quality to advance offline intrusion detection capabilities.
Wireless Security Needs For Enterprisesshrutisreddy
This document discusses improving wireless security for enterprise/corporate users compared to home users. It analyzes security threats like encryption attacks and outlines techniques like WEP, WPA, and WPA2. The key points are:
1) Wireless networks are vulnerable to attacks using tools like AirSnort but techniques like WPA2 with AES encryption provide stronger security.
2) Corporate networks require robust security as they contain sensitive customer data, while basic techniques like WEP may suffice for home networks.
3) The document recommends home users enable security settings and use WPA-PSK encryption to protect their wireless networks.
This seminar covers network security from its history to modern techniques. It introduces network security, the need for it due to increased internet usage, and basic concepts like authentication and common attacks. The document outlines early security protocols and why confidentiality, availability and integrity of information were important as the internet grew. It discusses how to secure a network from outside intrusion and different authentication techniques. Specific security methods like WPA, WEP and how hackers have evolved are also summarized. The advantages and challenges of network security are presented, as well as the importance of a well-designed security architecture for an organization's network.
This document provides an overview of network security. It discusses the history and need for network security. It describes common network attacks and authentication methods. The document outlines basic network security techniques like Wi-Fi Protected Access (WPA) and Wired Equivalent Privacy (WEP). It also discusses network security architecture and concludes that network security is an important field that requires ongoing improvement to address evolving threats.
This document discusses a seminar on network security. It covers topics like the history and need for network security, types of network security including authentication methods, common network attacks, and network security architecture. Network security aims to prevent unauthorized access to systems and data on a network. It discusses how network security has become more important as networks have expanded and grown more complex, and outlines some of the key aspects of designing and evaluating network security architecture.
IRJET- Wireless LAN Intrusion Detection and Prevention System for Malicious A...IRJET Journal
This document discusses a wireless LAN intrusion detection and prevention system for malicious access points. It aims to automatically detect and block rogue access points on a network, while also protecting unprotected clients. The system uses a whitelist containing authorized clients and compares IP addresses, SSIDs, detection/prevention times, and MAC addresses of access points and clients to identify unauthorized ones. It examines different techniques for detecting malicious access points and implements a lightweight server-side and client-side solution to efficiently detect and prevent malicious access points and protect unprotected clients, including detecting live attacks. The system aims to address limitations of prior work that only protected the client-side or server-side individually.
A Review On Network Security And PrivacyTodd Turner
This document summarizes a research paper that reviews network security and privacy. It begins by introducing the importance of data security and privacy as data and technology usage increases. It then discusses various network security layers and measures to protect data, such as network access control, antivirus software, firewalls, and virtual private networks. The document also covers different types of network attacks and security threats. It concludes by emphasizing the importance of network security for both individuals and companies in today's digital world.
Data Mining For Intrusion Detection in Mobile SystemsIOSR Journals
This document discusses using data mining techniques for intrusion detection in mobile systems. It proposes a network-based approach that removes processing overhead from mobile phones. An application on the phone collects user data and sends it to a remote server, where a previously trained neural network classifier analyzes the logs and detects abnormalities. The method was shown to detect intrusions at a 95% rate while outperforming existing mobile intrusion detection methods. It reduces processing on phones while effectively detecting intrusions in mobile networks and systems.
Hacking and cracking passwords on Wi-Fi in campus location is criminal acts that might approach because it could be considered stealing. Many Wi-Fi SSID are protected. It means that the owner of the Wi-Fi does not allow connections used freely by strangers. The are Many ways to crack it. A penetration test is one of the popular techniques to break the password. This tool directs the user to try to connect to the similar SSID name. However, they do not realize the name they join in is a fake SSID. This moment is used by the attackers to obtain the password. Soon after they try to connect several times, the attacker has been already recorded the SSID password.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
An Extensive Survey of Intrusion Detection SystemsIRJET Journal
This document summarizes an extensive survey of intrusion detection systems. It discusses the general architecture of IDS, including host-based and network-based systems. It describes different types of attacks (e.g. DoS, probing, user-to-root) and defenses. It analyzes previous work applying data mining techniques like machine learning to improve detection rates and reduce false alarms. A key problem is the massive number of false alarms that overburden security managers; the document aims to investigate solutions to lower the false alarm rate so that real threats are not missed.
IRJET- Analysis of Router Poisoning using Network AttacksIRJET Journal
This document discusses security threats in wireless ad hoc networks. It begins by describing the key security goals of confidentiality, availability, authentication, integrity, and non-repudiation. It then categorizes attacks as either passive or active. Passive attacks involve eavesdropping without altering data, while active attacks disrupt normal network functioning. Specific active attacks discussed include black holes, gray holes, worm holes, jellyfish attacks, spoofing, Sybil attacks, eavesdropping, Byzantine attacks, jamming attacks, and state pollution attacks. The document provides an overview of these prominent attacks on routing protocols in ad hoc networks.
This document discusses security issues in wireless networks and proposes different levels of security. It begins with an introduction to information security and wireless network security. It then describes various types of attacks on wireless networks such as unauthorized user access, network neighbor attacks, and intercepting data in wireless links. The document proposes three levels of security for wireless networks. Level 1 uses WEP, which has weaknesses that allow attacks. Level 2 uses WPA, which provides stronger access control and security than WEP. Level 3 uses WPA2, which implements the full IEEE 802.11i standard and is more robust than WPA.
A Performance Analysis of Chasing Intruders by Implementing Mobile AgentsCSCJournals
This document summarizes a research paper that proposes using mobile agents to improve intrusion detection systems. The paper presents an architecture for an intrusion detection system that uses mobile agents to autonomously collect intrusion-related information from systems on a network. Information collector agents gather data, while chasing agents work to trace the path of intrusions and locate their origin. The paper evaluates this approach and discusses how mobile agents can enhance intrusion detection through their mobility and autonomous functionality.
Intrusion Detection Techniques In Mobile NetworksIOSR Journals
This document discusses intrusion detection techniques for mobile networks. It begins by outlining the vulnerabilities of wireless networks, including the open medium, dynamic topology, lack of centralized monitoring, and cooperative algorithms. It then explains the need for intrusion detection systems, as completely preventing intrusions is unrealistic. The document classifies intrusion detection systems and outlines their requirements, including continuous monitoring, fault tolerance, and adaptability. It concludes by describing the two main techniques of intrusion detection: anomaly detection, which flags deviations from a normal activity profile; and misuse detection, which searches for patterns matching known attacks.
Network security presentation that briefly covers the aspect of security in networks. The slide consists of procedural steps for network security then some of the important network security components are described. To give it a practical approach, attacks on networks are also covered.
Computer networks connect devices through communication systems. Network security aims to protect information and allow authorized access. It involves authentication of users, monitoring network traffic for intrusions, and other strategies. Intrusion detection systems monitor for suspicious activity and notify administrators. There are different types of intrusion detection including network-based and host-based systems. Penetration testing evaluates security by simulating attacks. Cryptography also helps secure networks through techniques like public key encryption, hashing, and key exchange algorithms.
Final Project – Incident Response Exercise SAMPLE.docxlmelaine
Final Project – Incident Response Exercise
SAMPLE
1. Contact Information for the Incident Reporter and Handler
– Mruga Patel
– Cyber Incident Response Team Lead
– Organizational Information - Sifers-Grayson Corporation (Blue Team), Information Technology Department
– [email protected]
– 410-923-9221
– Location - 100 Fairway Ave, Suite 101, Catonsville, MD 21228
2. Incident Details
– The attack occurred during off-hours at 22:00 EST. Incident was discovered when the system became unusable due to high volume traffic from an unauthorized IP Address. The incident ended at approximately 22:45 EST.
– Catonsville, MD
– Attack has ended
– The attack occurred from an IP address of 11.125.22.198 with no host name. The cause of the incident has yet to be determined.
– The attack was discovered when the system became unusable due to high levels of latency. It was detected using logging information from a server from the Task Manager.
– The system remains unaffected. Only data was stolen from our company. The server which was extracted from the Employee server. IP address- 192.168.1.0, hotname SifersHouston.com.
– N/A
– The system resumed to normal function after attacked occurred.
– Data stolen was from the server containing employee information.
– Network was turned off once attack was discovered. The system logged all necessary information for forensic evidence.
– N/A
3. Cause of Incident was from an unsecured network which was uses to steal company information.
4. The cost of the incident has yet to be determined. PII stolen has no calculated price. However, estimated person hours are about 200. It would cost around $100 per hour for IT staff to perform “clean-up” activities. As of now it would cost around $20,000.00.
5. The impact of the incident is significant. The necessary measures to combat this problem has yet to be determined.
6. General Comments- Our network poses a lot of security risks. Going forward, we need to implement certain security measures from further incidents from taking place.
Background
The Sifers-Grayson company has hired an outside organization to penetrate our network and report on vulnerabilities found within the network. Upon penetration testing and weeks of trying to exploit our system, the red team (testing team) has been successful. Holding a government contract, the Department of Defense (DoD) requires additional security requirements for the R&D and SCADA lab operations. Both of which hold classified and secret information and happen to be where the red team was able to exploit.
The company is now required to use the NIST publications for protection controlled unclassified information in Nonfederal information systems and organizations. Failure to comply can result in fines and even contract termination. The (DFARS) Defense Federal Acquisition Regulations also outlines the safeguarding of Cyber Security Incident Reporting. Fortunately, identifying these risks before hacke ...
NETWORK INTRUSION DETECTION AND COUNTERMEASURE SELECTION IN VIRTUAL NETWORK (...ijsptm
Intrusion in a network or a system is a problem today as the trend of successful network attacks continue to
rise. Intruders can explore vulnerabilities of a network system to gain access in order to deploy some virus
or malware such as Denial of Service (DOS) attack. In this work, a frequency-based Intrusion Detection
System (IDS) is proposed to detect DOS attack. The frequency data is extracted from the time-series data
created by the traffic flow using Discrete Fourier Transform (DFT). An algorithm is developed for
anomaly-based intrusion detection with fewer false alarms which further detect known and unknown attack
signature in a network. The frequency of the traffic data of the virus or malware would be inconsistent with
the frequency of the legitimate traffic data. A Centralized Traffic Analyzer Intrusion Detection System
called CTA-IDS is introduced to further detect inside attackers in a network. The strategy is effective in
detecting abnormal content in the traffic data during information passing from one node to another and
also detects known attack signature and unknown attack. This approach is tested by running the artificial
network intrusion data in simulated networks using the Network Simulator2 (NS2) software.
Similar to Detection of Rogue Access Point in WLAN using Hopfield Neural Network (20)
Redefining brain tumor segmentation: a cutting-edge convolutional neural netw...IJECEIAES
Medical image analysis has witnessed significant advancements with deep learning techniques. In the domain of brain tumor segmentation, the ability to
precisely delineate tumor boundaries from magnetic resonance imaging (MRI)
scans holds profound implications for diagnosis. This study presents an ensemble convolutional neural network (CNN) with transfer learning, integrating
the state-of-the-art Deeplabv3+ architecture with the ResNet18 backbone. The
model is rigorously trained and evaluated, exhibiting remarkable performance
metrics, including an impressive global accuracy of 99.286%, a high-class accuracy of 82.191%, a mean intersection over union (IoU) of 79.900%, a weighted
IoU of 98.620%, and a Boundary F1 (BF) score of 83.303%. Notably, a detailed comparative analysis with existing methods showcases the superiority of
our proposed model. These findings underscore the model’s competence in precise brain tumor localization, underscoring its potential to revolutionize medical
image analysis and enhance healthcare outcomes. This research paves the way
for future exploration and optimization of advanced CNN models in medical
imaging, emphasizing addressing false positives and resource efficiency.
Embedded machine learning-based road conditions and driving behavior monitoringIJECEIAES
Car accident rates have increased in recent years, resulting in losses in human lives, properties, and other financial costs. An embedded machine learning-based system is developed to address this critical issue. The system can monitor road conditions, detect driving patterns, and identify aggressive driving behaviors. The system is based on neural networks trained on a comprehensive dataset of driving events, driving styles, and road conditions. The system effectively detects potential risks and helps mitigate the frequency and impact of accidents. The primary goal is to ensure the safety of drivers and vehicles. Collecting data involved gathering information on three key road events: normal street and normal drive, speed bumps, circular yellow speed bumps, and three aggressive driving actions: sudden start, sudden stop, and sudden entry. The gathered data is processed and analyzed using a machine learning system designed for limited power and memory devices. The developed system resulted in 91.9% accuracy, 93.6% precision, and 92% recall. The achieved inference time on an Arduino Nano 33 BLE Sense with a 32-bit CPU running at 64 MHz is 34 ms and requires 2.6 kB peak RAM and 139.9 kB program flash memory, making it suitable for resource-constrained embedded systems.
Advanced control scheme of doubly fed induction generator for wind turbine us...IJECEIAES
This paper describes a speed control device for generating electrical energy on an electricity network based on the doubly fed induction generator (DFIG) used for wind power conversion systems. At first, a double-fed induction generator model was constructed. A control law is formulated to govern the flow of energy between the stator of a DFIG and the energy network using three types of controllers: proportional integral (PI), sliding mode controller (SMC) and second order sliding mode controller (SOSMC). Their different results in terms of power reference tracking, reaction to unexpected speed fluctuations, sensitivity to perturbations, and resilience against machine parameter alterations are compared. MATLAB/Simulink was used to conduct the simulations for the preceding study. Multiple simulations have shown very satisfying results, and the investigations demonstrate the efficacy and power-enhancing capabilities of the suggested control system.
Neural network optimizer of proportional-integral-differential controller par...IJECEIAES
Wide application of proportional-integral-differential (PID)-regulator in industry requires constant improvement of methods of its parameters adjustment. The paper deals with the issues of optimization of PID-regulator parameters with the use of neural network technology methods. A methodology for choosing the architecture (structure) of neural network optimizer is proposed, which consists in determining the number of layers, the number of neurons in each layer, as well as the form and type of activation function. Algorithms of neural network training based on the application of the method of minimizing the mismatch between the regulated value and the target value are developed. The method of back propagation of gradients is proposed to select the optimal training rate of neurons of the neural network. The neural network optimizer, which is a superstructure of the linear PID controller, allows increasing the regulation accuracy from 0.23 to 0.09, thus reducing the power consumption from 65% to 53%. The results of the conducted experiments allow us to conclude that the created neural superstructure may well become a prototype of an automatic voltage regulator (AVR)-type industrial controller for tuning the parameters of the PID controller.
An improved modulation technique suitable for a three level flying capacitor ...IJECEIAES
This research paper introduces an innovative modulation technique for controlling a 3-level flying capacitor multilevel inverter (FCMLI), aiming to streamline the modulation process in contrast to conventional methods. The proposed
simplified modulation technique paves the way for more straightforward and
efficient control of multilevel inverters, enabling their widespread adoption and
integration into modern power electronic systems. Through the amalgamation of
sinusoidal pulse width modulation (SPWM) with a high-frequency square wave
pulse, this controlling technique attains energy equilibrium across the coupling
capacitor. The modulation scheme incorporates a simplified switching pattern
and a decreased count of voltage references, thereby simplifying the control
algorithm.
A review on features and methods of potential fishing zoneIJECEIAES
This review focuses on the importance of identifying potential fishing zones in seawater for sustainable fishing practices. It explores features like sea surface temperature (SST) and sea surface height (SSH), along with classification methods such as classifiers. The features like SST, SSH, and different classifiers used to classify the data, have been figured out in this review study. This study underscores the importance of examining potential fishing zones using advanced analytical techniques. It thoroughly explores the methodologies employed by researchers, covering both past and current approaches. The examination centers on data characteristics and the application of classification algorithms for classification of potential fishing zones. Furthermore, the prediction of potential fishing zones relies significantly on the effectiveness of classification algorithms. Previous research has assessed the performance of models like support vector machines, naïve Bayes, and artificial neural networks (ANN). In the previous result, the results of support vector machine (SVM) were 97.6% more accurate than naive Bayes's 94.2% to classify test data for fisheries classification. By considering the recent works in this area, several recommendations for future works are presented to further improve the performance of the potential fishing zone models, which is important to the fisheries community.
Electrical signal interference minimization using appropriate core material f...IJECEIAES
As demand for smaller, quicker, and more powerful devices rises, Moore's law is strictly followed. The industry has worked hard to make little devices that boost productivity. The goal is to optimize device density. Scientists are reducing connection delays to improve circuit performance. This helped them understand three-dimensional integrated circuit (3D IC) concepts, which stack active devices and create vertical connections to diminish latency and lower interconnects. Electrical involvement is a big worry with 3D integrates circuits. Researchers have developed and tested through silicon via (TSV) and substrates to decrease electrical wave involvement. This study illustrates a novel noise coupling reduction method using several electrical involvement models. A 22% drop in electrical involvement from wave-carrying to victim TSVs introduces this new paradigm and improves system performance even at higher THz frequencies.
Electric vehicle and photovoltaic advanced roles in enhancing the financial p...IJECEIAES
Climate change's impact on the planet forced the United Nations and governments to promote green energies and electric transportation. The deployments of photovoltaic (PV) and electric vehicle (EV) systems gained stronger momentum due to their numerous advantages over fossil fuel types. The advantages go beyond sustainability to reach financial support and stability. The work in this paper introduces the hybrid system between PV and EV to support industrial and commercial plants. This paper covers the theoretical framework of the proposed hybrid system including the required equation to complete the cost analysis when PV and EV are present. In addition, the proposed design diagram which sets the priorities and requirements of the system is presented. The proposed approach allows setup to advance their power stability, especially during power outages. The presented information supports researchers and plant owners to complete the necessary analysis while promoting the deployment of clean energy. The result of a case study that represents a dairy milk farmer supports the theoretical works and highlights its advanced benefits to existing plants. The short return on investment of the proposed approach supports the paper's novelty approach for the sustainable electrical system. In addition, the proposed system allows for an isolated power setup without the need for a transmission line which enhances the safety of the electrical network
Bibliometric analysis highlighting the role of women in addressing climate ch...IJECEIAES
Fossil fuel consumption increased quickly, contributing to climate change
that is evident in unusual flooding and draughts, and global warming. Over
the past ten years, women's involvement in society has grown dramatically,
and they succeeded in playing a noticeable role in reducing climate change.
A bibliometric analysis of data from the last ten years has been carried out to
examine the role of women in addressing the climate change. The analysis's
findings discussed the relevant to the sustainable development goals (SDGs),
particularly SDG 7 and SDG 13. The results considered contributions made
by women in the various sectors while taking geographic dispersion into
account. The bibliometric analysis delves into topics including women's
leadership in environmental groups, their involvement in policymaking, their
contributions to sustainable development projects, and the influence of
gender diversity on attempts to mitigate climate change. This study's results
highlight how women have influenced policies and actions related to climate
change, point out areas of research deficiency and recommendations on how
to increase role of the women in addressing the climate change and
achieving sustainability. To achieve more successful results, this initiative
aims to highlight the significance of gender equality and encourage
inclusivity in climate change decision-making processes.
Voltage and frequency control of microgrid in presence of micro-turbine inter...IJECEIAES
The active and reactive load changes have a significant impact on voltage
and frequency. In this paper, in order to stabilize the microgrid (MG) against
load variations in islanding mode, the active and reactive power of all
distributed generators (DGs), including energy storage (battery), diesel
generator, and micro-turbine, are controlled. The micro-turbine generator is
connected to MG through a three-phase to three-phase matrix converter, and
the droop control method is applied for controlling the voltage and
frequency of MG. In addition, a method is introduced for voltage and
frequency control of micro-turbines in the transition state from gridconnected mode to islanding mode. A novel switching strategy of the matrix
converter is used for converting the high-frequency output voltage of the
micro-turbine to the grid-side frequency of the utility system. Moreover,
using the switching strategy, the low-order harmonics in the output current
and voltage are not produced, and consequently, the size of the output filter
would be reduced. In fact, the suggested control strategy is load-independent
and has no frequency conversion restrictions. The proposed approach for
voltage and frequency regulation demonstrates exceptional performance and
favorable response across various load alteration scenarios. The suggested
strategy is examined in several scenarios in the MG test systems, and the
simulation results are addressed.
Enhancing battery system identification: nonlinear autoregressive modeling fo...IJECEIAES
Precisely characterizing Li-ion batteries is essential for optimizing their
performance, enhancing safety, and prolonging their lifespan across various
applications, such as electric vehicles and renewable energy systems. This
article introduces an innovative nonlinear methodology for system
identification of a Li-ion battery, employing a nonlinear autoregressive with
exogenous inputs (NARX) model. The proposed approach integrates the
benefits of nonlinear modeling with the adaptability of the NARX structure,
facilitating a more comprehensive representation of the intricate
electrochemical processes within the battery. Experimental data collected
from a Li-ion battery operating under diverse scenarios are employed to
validate the effectiveness of the proposed methodology. The identified
NARX model exhibits superior accuracy in predicting the battery's behavior
compared to traditional linear models. This study underscores the
importance of accounting for nonlinearities in battery modeling, providing
insights into the intricate relationships between state-of-charge, voltage, and
current under dynamic conditions.
Smart grid deployment: from a bibliometric analysis to a surveyIJECEIAES
Smart grids are one of the last decades' innovations in electrical energy.
They bring relevant advantages compared to the traditional grid and
significant interest from the research community. Assessing the field's
evolution is essential to propose guidelines for facing new and future smart
grid challenges. In addition, knowing the main technologies involved in the
deployment of smart grids (SGs) is important to highlight possible
shortcomings that can be mitigated by developing new tools. This paper
contributes to the research trends mentioned above by focusing on two
objectives. First, a bibliometric analysis is presented to give an overview of
the current research level about smart grid deployment. Second, a survey of
the main technological approaches used for smart grid implementation and
their contributions are highlighted. To that effect, we searched the Web of
Science (WoS), and the Scopus databases. We obtained 5,663 documents
from WoS and 7,215 from Scopus on smart grid implementation or
deployment. With the extraction limitation in the Scopus database, 5,872 of
the 7,215 documents were extracted using a multi-step process. These two
datasets have been analyzed using a bibliometric tool called bibliometrix.
The main outputs are presented with some recommendations for future
research.
Use of analytical hierarchy process for selecting and prioritizing islanding ...IJECEIAES
One of the problems that are associated to power systems is islanding
condition, which must be rapidly and properly detected to prevent any
negative consequences on the system's protection, stability, and security.
This paper offers a thorough overview of several islanding detection
strategies, which are divided into two categories: classic approaches,
including local and remote approaches, and modern techniques, including
techniques based on signal processing and computational intelligence.
Additionally, each approach is compared and assessed based on several
factors, including implementation costs, non-detected zones, declining
power quality, and response times using the analytical hierarchy process
(AHP). The multi-criteria decision-making analysis shows that the overall
weight of passive methods (24.7%), active methods (7.8%), hybrid methods
(5.6%), remote methods (14.5%), signal processing-based methods (26.6%),
and computational intelligent-based methods (20.8%) based on the
comparison of all criteria together. Thus, it can be seen from the total weight
that hybrid approaches are the least suitable to be chosen, while signal
processing-based methods are the most appropriate islanding detection
method to be selected and implemented in power system with respect to the
aforementioned factors. Using Expert Choice software, the proposed
hierarchy model is studied and examined.
Enhancing of single-stage grid-connected photovoltaic system using fuzzy logi...IJECEIAES
The power generated by photovoltaic (PV) systems is influenced by
environmental factors. This variability hampers the control and utilization of
solar cells' peak output. In this study, a single-stage grid-connected PV
system is designed to enhance power quality. Our approach employs fuzzy
logic in the direct power control (DPC) of a three-phase voltage source
inverter (VSI), enabling seamless integration of the PV connected to the
grid. Additionally, a fuzzy logic-based maximum power point tracking
(MPPT) controller is adopted, which outperforms traditional methods like
incremental conductance (INC) in enhancing solar cell efficiency and
minimizing the response time. Moreover, the inverter's real-time active and
reactive power is directly managed to achieve a unity power factor (UPF).
The system's performance is assessed through MATLAB/Simulink
implementation, showing marked improvement over conventional methods,
particularly in steady-state and varying weather conditions. For solar
irradiances of 500 and 1,000 W/m2
, the results show that the proposed
method reduces the total harmonic distortion (THD) of the injected current
to the grid by approximately 46% and 38% compared to conventional
methods, respectively. Furthermore, we compare the simulation results with
IEEE standards to evaluate the system's grid compatibility.
Enhancing photovoltaic system maximum power point tracking with fuzzy logic-b...IJECEIAES
Photovoltaic systems have emerged as a promising energy resource that
caters to the future needs of society, owing to their renewable, inexhaustible,
and cost-free nature. The power output of these systems relies on solar cell
radiation and temperature. In order to mitigate the dependence on
atmospheric conditions and enhance power tracking, a conventional
approach has been improved by integrating various methods. To optimize
the generation of electricity from solar systems, the maximum power point
tracking (MPPT) technique is employed. To overcome limitations such as
steady-state voltage oscillations and improve transient response, two
traditional MPPT methods, namely fuzzy logic controller (FLC) and perturb
and observe (P&O), have been modified. This research paper aims to
simulate and validate the step size of the proposed modified P&O and FLC
techniques within the MPPT algorithm using MATLAB/Simulink for
efficient power tracking in photovoltaic systems.
Adaptive synchronous sliding control for a robot manipulator based on neural ...IJECEIAES
Robot manipulators have become important equipment in production lines, medical fields, and transportation. Improving the quality of trajectory tracking for
robot hands is always an attractive topic in the research community. This is a
challenging problem because robot manipulators are complex nonlinear systems
and are often subject to fluctuations in loads and external disturbances. This
article proposes an adaptive synchronous sliding control scheme to improve trajectory tracking performance for a robot manipulator. The proposed controller
ensures that the positions of the joints track the desired trajectory, synchronize
the errors, and significantly reduces chattering. First, the synchronous tracking
errors and synchronous sliding surfaces are presented. Second, the synchronous
tracking error dynamics are determined. Third, a robust adaptive control law is
designed,the unknown components of the model are estimated online by the neural network, and the parameters of the switching elements are selected by fuzzy
logic. The built algorithm ensures that the tracking and approximation errors
are ultimately uniformly bounded (UUB). Finally, the effectiveness of the constructed algorithm is demonstrated through simulation and experimental results.
Simulation and experimental results show that the proposed controller is effective with small synchronous tracking errors, and the chattering phenomenon is
significantly reduced.
Remote field-programmable gate array laboratory for signal acquisition and de...IJECEIAES
A remote laboratory utilizing field-programmable gate array (FPGA) technologies enhances students’ learning experience anywhere and anytime in embedded system design. Existing remote laboratories prioritize hardware access and visual feedback for observing board behavior after programming, neglecting comprehensive debugging tools to resolve errors that require internal signal acquisition. This paper proposes a novel remote embeddedsystem design approach targeting FPGA technologies that are fully interactive via a web-based platform. Our solution provides FPGA board access and debugging capabilities beyond the visual feedback provided by existing remote laboratories. We implemented a lab module that allows users to seamlessly incorporate into their FPGA design. The module minimizes hardware resource utilization while enabling the acquisition of a large number of data samples from the signal during the experiments by adaptively compressing the signal prior to data transmission. The results demonstrate an average compression ratio of 2.90 across three benchmark signals, indicating efficient signal acquisition and effective debugging and analysis. This method allows users to acquire more data samples than conventional methods. The proposed lab allows students to remotely test and debug their designs, bridging the gap between theory and practice in embedded system design.
Detecting and resolving feature envy through automated machine learning and m...IJECEIAES
Efficiently identifying and resolving code smells enhances software project quality. This paper presents a novel solution, utilizing automated machine learning (AutoML) techniques, to detect code smells and apply move method refactoring. By evaluating code metrics before and after refactoring, we assessed its impact on coupling, complexity, and cohesion. Key contributions of this research include a unique dataset for code smell classification and the development of models using AutoGluon for optimal performance. Furthermore, the study identifies the top 20 influential features in classifying feature envy, a well-known code smell, stemming from excessive reliance on external classes. We also explored how move method refactoring addresses feature envy, revealing reduced coupling and complexity, and improved cohesion, ultimately enhancing code quality. In summary, this research offers an empirical, data-driven approach, integrating AutoML and move method refactoring to optimize software project quality. Insights gained shed light on the benefits of refactoring on code quality and the significance of specific features in detecting feature envy. Future research can expand to explore additional refactoring techniques and a broader range of code metrics, advancing software engineering practices and standards.
Smart monitoring technique for solar cell systems using internet of things ba...IJECEIAES
Rapidly and remotely monitoring and receiving the solar cell systems status parameters, solar irradiance, temperature, and humidity, are critical issues in enhancement their efficiency. Hence, in the present article an improved smart prototype of internet of things (IoT) technique based on embedded system through NodeMCU ESP8266 (ESP-12E) was carried out experimentally. Three different regions at Egypt; Luxor, Cairo, and El-Beheira cities were chosen to study their solar irradiance profile, temperature, and humidity by the proposed IoT system. The monitoring data of solar irradiance, temperature, and humidity were live visualized directly by Ubidots through hypertext transfer protocol (HTTP) protocol. The measured solar power radiation in Luxor, Cairo, and El-Beheira ranged between 216-1000, 245-958, and 187-692 W/m 2 respectively during the solar day. The accuracy and rapidity of obtaining monitoring results using the proposed IoT system made it a strong candidate for application in monitoring solar cell systems. On the other hand, the obtained solar power radiation results of the three considered regions strongly candidate Luxor and Cairo as suitable places to build up a solar cells system station rather than El-Beheira.
An efficient security framework for intrusion detection and prevention in int...IJECEIAES
Over the past few years, the internet of things (IoT) has advanced to connect billions of smart devices to improve quality of life. However, anomalies or malicious intrusions pose several security loopholes, leading to performance degradation and threat to data security in IoT operations. Thereby, IoT security systems must keep an eye on and restrict unwanted events from occurring in the IoT network. Recently, various technical solutions based on machine learning (ML) models have been derived towards identifying and restricting unwanted events in IoT. However, most ML-based approaches are prone to miss-classification due to inappropriate feature selection. Additionally, most ML approaches applied to intrusion detection and prevention consider supervised learning, which requires a large amount of labeled data to be trained. Consequently, such complex datasets are impossible to source in a large network like IoT. To address this problem, this proposed study introduces an efficient learning mechanism to strengthen the IoT security aspects. The proposed algorithm incorporates supervised and unsupervised approaches to improve the learning models for intrusion detection and mitigation. Compared with the related works, the experimental outcome shows that the model performs well in a benchmark dataset. It accomplishes an improved detection accuracy of approximately 99.21%.
Software Engineering and Project Management - Introduction, Modeling Concepts...Prakhyath Rai
Introduction, Modeling Concepts and Class Modeling: What is Object orientation? What is OO development? OO Themes; Evidence for usefulness of OO development; OO modeling history. Modeling
as Design technique: Modeling, abstraction, The Three models. Class Modeling: Object and Class Concept, Link and associations concepts, Generalization and Inheritance, A sample class model, Navigation of class models, and UML diagrams
Building the Analysis Models: Requirement Analysis, Analysis Model Approaches, Data modeling Concepts, Object Oriented Analysis, Scenario-Based Modeling, Flow-Oriented Modeling, class Based Modeling, Creating a Behavioral Model.
Rainfall intensity duration frequency curve statistical analysis and modeling...bijceesjournal
Using data from 41 years in Patna’ India’ the study’s goal is to analyze the trends of how often it rains on a weekly, seasonal, and annual basis (1981−2020). First, utilizing the intensity-duration-frequency (IDF) curve and the relationship by statistically analyzing rainfall’ the historical rainfall data set for Patna’ India’ during a 41 year period (1981−2020), was evaluated for its quality. Changes in the hydrologic cycle as a result of increased greenhouse gas emissions are expected to induce variations in the intensity, length, and frequency of precipitation events. One strategy to lessen vulnerability is to quantify probable changes and adapt to them. Techniques such as log-normal, normal, and Gumbel are used (EV-I). Distributions were created with durations of 1, 2, 3, 6, and 24 h and return times of 2, 5, 10, 25, and 100 years. There were also mathematical correlations discovered between rainfall and recurrence interval.
Findings: Based on findings, the Gumbel approach produced the highest intensity values, whereas the other approaches produced values that were close to each other. The data indicates that 461.9 mm of rain fell during the monsoon season’s 301st week. However, it was found that the 29th week had the greatest average rainfall, 92.6 mm. With 952.6 mm on average, the monsoon season saw the highest rainfall. Calculations revealed that the yearly rainfall averaged 1171.1 mm. Using Weibull’s method, the study was subsequently expanded to examine rainfall distribution at different recurrence intervals of 2, 5, 10, and 25 years. Rainfall and recurrence interval mathematical correlations were also developed. Further regression analysis revealed that short wave irrigation, wind direction, wind speed, pressure, relative humidity, and temperature all had a substantial influence on rainfall.
Originality and value: The results of the rainfall IDF curves can provide useful information to policymakers in making appropriate decisions in managing and minimizing floods in the study area.
Optimizing Gradle Builds - Gradle DPE Tour Berlin 2024Sinan KOZAK
Sinan from the Delivery Hero mobile infrastructure engineering team shares a deep dive into performance acceleration with Gradle build cache optimizations. Sinan shares their journey into solving complex build-cache problems that affect Gradle builds. By understanding the challenges and solutions found in our journey, we aim to demonstrate the possibilities for faster builds. The case study reveals how overlapping outputs and cache misconfigurations led to significant increases in build times, especially as the project scaled up with numerous modules using Paparazzi tests. The journey from diagnosing to defeating cache issues offers invaluable lessons on maintaining cache integrity without sacrificing functionality.
Design and optimization of ion propulsion dronebjmsejournal
Electric propulsion technology is widely used in many kinds of vehicles in recent years, and aircrafts are no exception. Technically, UAVs are electrically propelled but tend to produce a significant amount of noise and vibrations. Ion propulsion technology for drones is a potential solution to this problem. Ion propulsion technology is proven to be feasible in the earth’s atmosphere. The study presented in this article shows the design of EHD thrusters and power supply for ion propulsion drones along with performance optimization of high-voltage power supply for endurance in earth’s atmosphere.
Null Bangalore | Pentesters Approach to AWS IAMDivyanshu
#Abstract:
- Learn more about the real-world methods for auditing AWS IAM (Identity and Access Management) as a pentester. So let us proceed with a brief discussion of IAM as well as some typical misconfigurations and their potential exploits in order to reinforce the understanding of IAM security best practices.
- Gain actionable insights into AWS IAM policies and roles, using hands on approach.
#Prerequisites:
- Basic understanding of AWS services and architecture
- Familiarity with cloud security concepts
- Experience using the AWS Management Console or AWS CLI.
- For hands on lab create account on [killercoda.com](https://killercoda.com/cloudsecurity-scenario/)
# Scenario Covered:
- Basics of IAM in AWS
- Implementing IAM Policies with Least Privilege to Manage S3 Bucket
- Objective: Create an S3 bucket with least privilege IAM policy and validate access.
- Steps:
- Create S3 bucket.
- Attach least privilege policy to IAM user.
- Validate access.
- Exploiting IAM PassRole Misconfiguration
-Allows a user to pass a specific IAM role to an AWS service (ec2), typically used for service access delegation. Then exploit PassRole Misconfiguration granting unauthorized access to sensitive resources.
- Objective: Demonstrate how a PassRole misconfiguration can grant unauthorized access.
- Steps:
- Allow user to pass IAM role to EC2.
- Exploit misconfiguration for unauthorized access.
- Access sensitive resources.
- Exploiting IAM AssumeRole Misconfiguration with Overly Permissive Role
- An overly permissive IAM role configuration can lead to privilege escalation by creating a role with administrative privileges and allow a user to assume this role.
- Objective: Show how overly permissive IAM roles can lead to privilege escalation.
- Steps:
- Create role with administrative privileges.
- Allow user to assume the role.
- Perform administrative actions.
- Differentiation between PassRole vs AssumeRole
Try at [killercoda.com](https://killercoda.com/cloudsecurity-scenario/)
artificial intelligence and data science contents.pptxGauravCar
What is artificial intelligence? Artificial intelligence is the ability of a computer or computer-controlled robot to perform tasks that are commonly associated with the intellectual processes characteristic of humans, such as the ability to reason.
› ...
Artificial intelligence (AI) | Definitio
Introduction- e - waste – definition - sources of e-waste– hazardous substances in e-waste - effects of e-waste on environment and human health- need for e-waste management– e-waste handling rules - waste minimization techniques for managing e-waste – recycling of e-waste - disposal treatment methods of e- waste – mechanism of extraction of precious metal from leaching solution-global Scenario of E-waste – E-waste in India- case studies.
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are in the network [5]. In wired communication detection of this type of attack is easy while in the case of a
wireless communication attacker easily access the information by making fake access points. These access
points can be easily bought as they are inexpensive. These unauthorized access points are called rogue access
points [6]. Any unsanctioned, unauthorized wireless point that connects to an enterprise‟s authorized network
is defined as a rogue access point. It is one of the greatest risks to an organization‟s security. These access
points work as an open network system for the outsiders which are ready to take out information from the
enterprise‟s traffic.
We explore the use Hopfield neural network method of Artificial Neural Network for detecting the
presence of rogue access points in the network. Hopfield network is trained with known patterns and recall
that pattern at the time of execution. Section II focuses on different types of rogue access point present in any
organization and their methods of detection. Section III describes the work done by different researchers and
industry solutions related to this problem. Section IV explains Hopfield Neural Network and then the
simulation part for detection of rogue access points using the neural network tool.
2. THE ROGUE ACCESS POINT
Rogue access point is a point connected to the network without the permission of the administrator.
Therefore, it is called an unauthorized point which accesses the information. The unauthorized access point is
divided into two categories: – 2.1) Rogue access point, 2.2) Fake access point.
2.1. Rogue access point
Rogue access point is an access point which is installed by not only the outsider, but also by the
authorized user to take benefit of the network. There are four common types of the rogue access point:
2.1.1. Employee Rogue Access Point
This type of access point occurred when employee buy an access point and installs it on the
company‟s LAN for its own benefit without permission. It also opens the way for outside attackers to access
the network. This type of incident takes place where there is a lack of wireless security policies and lack of
awareness in employees.
2.1.2. Attacker’s external rogue access point
This type of access point is setup outside the organization by the attacker and does not connect to the
network. It aims to allow the target employee to connect to a rogue access point. All user traffic is redirected
through this rogue access point and attacker analyzes it. This attack is also called Man-in-the Middle Attack.
2.1.3. Attacker’s internal rogue access point
In contrast, with above access point this access point is set up inside the organization by the attacker
and does not connect to the network. But an attacker uses this rogue access point at a later time to access the
internal LAN. Once it is successful, it would be a serious security breach.
2.1.4. Neighborhood rogue access point
As the name suggests, the access point is set-up by another company in the close vicinity.
2.2. Fake access point
Fake access point is an access point that is inserted by an outsider or an attacker without the
permission of the authorized user of the network [7]. He used this access point for stealing information and
for other false purposes. All these types of rogue access point are prevented by the two processes, first is
rogue access point detection to identify the rogue access point and the second one has taken security
measures to disable the rogue access point.
Most enterprises use WPA2 security for wireless communication. But even WPA2 also cannot
protect from rogue access point, we can incorporate WPA2 only on managed access point, but the rogue
access point is an unauthorized access point. So, we cannot enforce security control over it. Although
detecting rogue access points is a challenging process. There are many existing techniques for detection of
rogue access point [8],[9]. These techniques divided into following categories like traditional approach, client
side approach, server side approach and hybrid approaches.
2.3. Traditional Approach
Traditional approach based on matching concept. It verifies the MAC address and SSID. If all the
attributes are same then it is an authorized access point. Traditional approach isn't effective for authentication
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of authorized access points as the number of tools being available in the market that spoof MAC address and
logical address. So, this approach is not sufficient.
2.4. Server side Approach
It is the central controller of the wired and wireless network. Software tools are installed on a
centralized server and they analyze the whole network and detect rogue access point by performing some
operations and if found something wrong, it checks the status of that particular access point.
2.5. Client Side Approach
This is a challenging process as there is former information about networks and about the access
point list [10]. This approach takes services from server sides for detection of rogue access points or they also
install software on their device of access point whether it is authorized or not.
3. LITERATURE SURVEY
Along with academic solutions there are some industrial solutions also exist which are as follows:
Air Defense contains sensors deploy throughout the network [11]. Here, network manager handles the
software tool, which detects attacker and attacks in the network. The only problem with this tool is that its
response time is slow but it is a commercial product and easily available.
Air Magnet is also a commercial product and helps in detecting an unauthorized access point and
denial of service attack by flooding [12]. This also requires a technical manager for detection. Jana et
al.proposed server side solution using clock skews of the access point [13]. This approach is unable to detect
MAC spoofing and has a lack of accuracy and speed in the calculation of clock skews. Kindberg et al.
Proposed a model for security for public Wi-Fi network [14]. It uses encryption and authentication
techniques to authenticate the access point in the wireless network.
Shivraj et al. Present server side Hidden Markov Model (HMM) based approach to detect rogue
access point [15]. This technique achieves more than 80% accuracy and uses a variation in packet inter
arrival time to detect authorized and unauthorized access points. This approach is also in denial of service
attack. Kim et al. Proposed client side approach for detecting fake access point using the idea of received
signal strength (RSS). They collect the signals, normalize it and then apply sequential hypothesis technique.
They never consider the distance, as it affects the signal strength.
Kao et al. Proposed client side approach for detecting rogue access point [16]. It uses a passive
packet analysis approach based on bandwidth estimation. Liran Ma et al. Proposed hybrid approach for
detecting the rogue access points [17]. It is a cost effective solution and also the proposed model uses a
traditional approach for detecting fake access points. Here, in this paper, we propose the automatic detection
of rogue access points by using the Hopfield neural network approach. For accessing any service or resource
of the network, the device must first communicate with another device, i.e. pair with each other for
communication. A four way handshake protocol is involved in the set up of WLAN [18-21]. The main
purpose of this process is to enable an access point to authenticate itself to the client and then use the user‟s
login and password. In conventional method passwords are easily tracked by the intruders, but in this
mechanism the tracking/cracking of password is impossible.
4. HOPFIELD NEURAL NETWORK
In the neural networks, when we use feed forward flow of information, i.e. one output vector is
associated to every input vector is called a Feed Forward Network. But sometimes, it is possible where
output value can return back to the input repeatedly, then; these types of situations come under feedback
networks. John Hopfield proposed this type of concept of neural network in his paper which was published in
1982 [22]. Hopfield works on auto associative non-linear properties of the network. It is a fully connected or
recurrent type of network in which each neuron is linked with each other but not with it. Neural networks are
complex and non-linear in nature, so analyzing their behavior is difficult. Hopfield used non-linear dynamical
system theory on neural networks. In the network architecture, he embedded the physical principle and set up
an energy function. Hopfield Neural Network basically uses the concept of content addressable memory [23].
The network develops a number of stable points in state space and the other points in the state space move
into the direction of stable points, here known as attractors which are energy minima. Attractors can also be
applied when we reconstruct the missing information and often called associative memory on the Hopfield
Neural Network. Operation of auto associative memory is rooted from reconstruction property in the sense
that the new input states can be linked to the appropriate patterns already stored in the memory. The Hopfield
Neural Network is a single layer, non-linear and constant addressable memory network and of two types:
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discrete and continuous. The Hopfield Neural Network model consists of two layers, one is input and other is
output, where each unit is connected to every other unit in the network other than itself [24], [25]. HPNN
consists of neurons and each neuron can be in one of two states, i.e. +1 and p bipolar patterns:
Xu
= )
The connection of weight matrix is square and symmetric i.e. all the diagonal elements of Hopfield
network are zero:
Wij = Wji and Wii = 0
Hopfield specified the Wij „s by using the Hebbian rule [26] i.e
Wij = ∑ (i≠j)
Hopfield associated with a function known as an energy function or Lyapunov function. This
function proves that the net will converge to a stable limit point. The energy function is given by:
E = ∑ ∑ ∑ ∑
So for storing a pattern, the energy function should be minimized. Figure 1 shows a Hopfield model with
eight nodes, where each node is connected to every other node in the network.
Figure1. Hopfield Neural Network Figure 2. Devices paired with the router
5. SIMULATION DESIGN
Figure 2, depicts the connection of different devices to the router used for simulation
implementation. In this segment we take eight entities, smart phones, laptops and other wireless devices that
are connected to the Wi-Fi router. The passwords for accessing the devices are stored in the router and also
known to the authentic user. Memory of router stores the different trained patterns of the passwords that are
used by the organization staff and other authentic employees. The passwords are first normalized and then
convert into bipolar, as Hopfield network take bipolar inputs. We train our network for a particular pattern
and stored in the memory. By looking at network parameters, an attacker did not find out the design of the
network. In this section, we are conducting the simulation of real test data [27]. Here we, memorize the input
pattern sets by minimizing the error between the desired and actual output for 8 sets having 40 bits each.
Input data set
H = [0 0 1 1 0 0 0 1
0 0 0 0 1 1 1 1
0 0 0 0 1 1 0 1
1 0 1 0 1 1 1 1
0 1 1 1 1 0 1 0
0 0 0 1 0 1 1 0
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Figure 3 shows the performance of network done by Hopfield Neural Network and Table 1 explains
network parameters used by network for training. Figure 4 shows the performance of the network when input
data is not similar to the previously stored data.
Figure 3. Training graph for Network Performance by
Hopfield Neural Network
Figure 4. Graph showing variation in the input and
output
Table 1. The parameters used for The Training of Hopfield Neural Network
Parameter Value
Neurons in Input Layer 40
Neurons in Output Layer 40
Total Number of Patterns 8
Minimum Error Exist in the Network 12
Training Time 0.000003 sec
Initial Weight and biased term values Values between 0 and 1
6. RESULT AND DISCUSSION
The simulation is carried out on MATLAB tool. The straight line of the graph in Figure 3 shows that
the memory stores the passwords on the different devices in the form that no one can find out which training
algorithm has been used for training the network. These network parameters are stored in the memory and
when user access the network with the stored password, then system proves it as an authentic person who is
in the premises of the organization. In contrast, if there are intruders who attack on the system security, i.e.
perform man-in-the-middle-attack and want to hack the sensitive data from the organization, then the patterns
that are stored in the network will give the network performance that is shown in Figure 4 by dotted line
which shows some variation in the graph. Network parameters are also changes if some unauthentic users are
interfering in the organization.
7. CONCLUSION
In this paper, we proposed an automatic detection of rogue access point which is based on a
Hopfield Neural Network algorithm. Above simulations conclude that this neural network algorithm takes
very less time for execution and stores number of patterns very accurately. The connections of different
devices were stored in the form of network parameters which is hard to crack and the variation in the input,
output data show the presence of unauthorized points i.e. rogue access points. The researchers generated a
secret key for encryption and decryption of the messages using HPNN. Some of the researchers train the
HPNN model that could recall the legal users and reject the illegal users correctly and covered registration
and authorization phases. Different researchers implemented various approaches and methods, but none of
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them use Hopfield Neural Network Mechanism for detecting the rogue access points in wireless
communication.This proposed neural network approach is a safe and easy operated method than the
conventional method of encryption. The proposed model is designed for utilizing the existing WLAN
infrastructure and there is no need of extra equipment for performing this detection.
REFERENCES
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Advancements in Computer Science (RACS), 2011.
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New York, USA, 1999.
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BIOGRAPHIES OF AUTHORS
Ms Menal Dahiya is Assistant Professor of Computer Science at Maharaja Surajmal
Institute(GGSIP University,Delhi) and a Research Scholar of Maharshi Dayanand
University,Rohtak in the Dept. Of Computer Science and Applications. She received her MPhil
in Computer Science from Chaudhary Devi Lal University, Sirsa, India in 2007.Before she had
studied at Guru Jambheshwar University of Science & Technology (GJU), Hisar and KUK,
Kurukshetra,India. Her main research interest are Neural Network,Wireless Security and
Wireless Communication. Several of her research papers have been published in international
peer-reviewed journals indexed in Scopus, Copernicus and others.
Dr Sumeet Gill is Assistant Professor of Computer Science at Department of Mathematics at
Maharshi Dayanand University, Rohatk, India. He received his Ph.D in Computer Science from
Dr.B. R .Ambedgar University, Agra, India in 2009. Before he had done MSc (Physics) from
KUK, Kurukshetra in 1999 and S.S. Plasma Astro Physics from Indian Institute of Science,
Bangalore, India in 1998. His main research area are Neural Network, Wireless Communication.
He is on Research Panel of various universities like Dr.B. R. Ambedger University, RTM
University, SGV University etc.. He is also a Liaison officer of the USENIX Association, U.S.A.
He published 2 Books and several Research Papers indexed in SCOPUS and Copernicus.