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
Intrusion Detection System (IDS) is meant to be a software application which monitors the network or system activities and finds if any malicious operations occur. Tremendous growth and usage of internet raises concerns about how to protect and communicate the digital information in a safe manner. Nowadays, hackers use different types of attacks for getting the valuable information. Many intrusion detection techniques, methods and algorithms help to detect these attacks. This main objective of this paper
is to provide a complete study about the definition of intrusion detection, history, life cycle, types of intrusion detection methods, types of attacks, different tools and techniques, research needs, challenges and
applications.
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.
This document summarizes an international journal on information technology and management information systems. It discusses detecting and classifying attacks in a computer network. Existing approaches to intrusion detection include anomaly-based systems, host-based intrusion detection systems (HIDS), and network-based intrusion detection systems (NIDS). A multilayer perceptron (MLP) algorithm is commonly used for intrusion detection but has limitations. The paper proposes a modified apriori algorithm to generate rules for detecting and classifying attacks into categories and types to enable recommending appropriate responses.
Intrusion detection and anomaly detection system using sequential pattern miningeSAT Journals
Abstract
Nowadays the security methods from password protected access up to firewalls which are used to secure the data as well as the networks from attackers. Several times these types of security methods are not enough to protect data. We can consider the use of Intrusion Detection Systems (IDS) is the one way to secure the data on critical systems. Most of the research work is going on the effectiveness and exactness of the intrusion detection, but these attempts are for the detection of the intrusions at the operating system and network level only. It is unable to detect the unexpected behavior of systems due to malicious transactions in databases. The method used for spotting any interferes on the information in the form of database known as database intrusion detection. It relies on enlisting the execution of a transaction. After that, if the recognized pattern is aside from those regular patterns actual is considered as an intrusion. But the identified problem with this process is that the accuracy algorithm which is used may not identify entire patterns. This type of challenges can affect in two ways. 1) Missing of the database with regular patterns. 2) The detection process neglects some new patterns. Therefore we proposed sequential data mining method by using new Modified Apriori Algorithm. The algorithm upturns the accurateness and rate of pattern detection by the process. The Apriori algorithm with modifications is used in the proposed model.
Keywords — Anomaly Detection, Modified Apriori Algorithm, Misuse detection, Sequential Pattern Mining
Report: Study and Implementation of Advance Intrusion Detection and Preventio...Deepak Mishra
This document discusses building an intrusion detection system that combines network-based and log-based detection. It proposes using the Security Onion distribution and its included tools like Snort, Sguil, Squert and OSSEC. It describes configuring Security Onion sensors to monitor network traffic and logs, storing alerts in databases, and using the management consoles to analyze alerts. The goal is to create a comprehensive security monitoring platform through centralized log management and correlation of network and host-based events.
An Assessment of Intrusion Detection System IDS and Data Set Overview A Compr...ijtsrd
Millions of people worldwide have Internet access today. Intrusion detection technology is a modern wave of information technology monitoring devices to deter malicious activities. Malware development malicious software is a vital problem when it comes to designing intrusion detection systems IDS . The key challenge is to recognize unknown and hidden malware, because malware writers use various evasion techniques to mask information to avoid IDS detection. Malicious attacks have become more sophisticated and Furthermore, threats to security have increased, including a zero day attack on internet users. Through the use of IT in our daily lives, computer security has become critical. Cyber threats are becoming more complex and pose growing challenges when it comes to successful intrusion detection. Failure to prevent invading information, such as data privacy, integrity and availability can undermine the credibility of security services. Specific intrusion detection approaches were proposed in the literature to combat computer security threats. This paper consists of a literature survey of the IDS that uses program algorithms to use specific data collection and forensic techniques in real time. Data mining techniques for cyber research are introduced in support of intrusion detection. Mohammed I. Alghamdi "An Assessment of Intrusion Detection System (IDS) and Data-Set Overview: A Comprehensive Review of Recent Works" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-2 , February 2021, URL: https://www.ijtsrd.com/papers/ijtsrd35730.pdf Paper Url: https://www.ijtsrd.com/computer-science/computer-security/35730/an-assessment-of-intrusion-detection-system-ids-and-dataset-overview-a-comprehensive-review-of-recent-works/mohammed-i-alghamdi
Comparative Study on Intrusion Detection Systems for Smartphonesiosrjce
IOSR Journal of Computer Engineering (IOSR-JCE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of computer engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in computer technology. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
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 System (IDS) is meant to be a software application which monitors the network or system activities and finds if any malicious operations occur. Tremendous growth and usage of internet raises concerns about how to protect and communicate the digital information in a safe manner. Nowadays, hackers use different types of attacks for getting the valuable information. Many intrusion detection techniques, methods and algorithms help to detect these attacks. This main objective of this paper
is to provide a complete study about the definition of intrusion detection, history, life cycle, types of intrusion detection methods, types of attacks, different tools and techniques, research needs, challenges and
applications.
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.
This document summarizes an international journal on information technology and management information systems. It discusses detecting and classifying attacks in a computer network. Existing approaches to intrusion detection include anomaly-based systems, host-based intrusion detection systems (HIDS), and network-based intrusion detection systems (NIDS). A multilayer perceptron (MLP) algorithm is commonly used for intrusion detection but has limitations. The paper proposes a modified apriori algorithm to generate rules for detecting and classifying attacks into categories and types to enable recommending appropriate responses.
Intrusion detection and anomaly detection system using sequential pattern miningeSAT Journals
Abstract
Nowadays the security methods from password protected access up to firewalls which are used to secure the data as well as the networks from attackers. Several times these types of security methods are not enough to protect data. We can consider the use of Intrusion Detection Systems (IDS) is the one way to secure the data on critical systems. Most of the research work is going on the effectiveness and exactness of the intrusion detection, but these attempts are for the detection of the intrusions at the operating system and network level only. It is unable to detect the unexpected behavior of systems due to malicious transactions in databases. The method used for spotting any interferes on the information in the form of database known as database intrusion detection. It relies on enlisting the execution of a transaction. After that, if the recognized pattern is aside from those regular patterns actual is considered as an intrusion. But the identified problem with this process is that the accuracy algorithm which is used may not identify entire patterns. This type of challenges can affect in two ways. 1) Missing of the database with regular patterns. 2) The detection process neglects some new patterns. Therefore we proposed sequential data mining method by using new Modified Apriori Algorithm. The algorithm upturns the accurateness and rate of pattern detection by the process. The Apriori algorithm with modifications is used in the proposed model.
Keywords — Anomaly Detection, Modified Apriori Algorithm, Misuse detection, Sequential Pattern Mining
Report: Study and Implementation of Advance Intrusion Detection and Preventio...Deepak Mishra
This document discusses building an intrusion detection system that combines network-based and log-based detection. It proposes using the Security Onion distribution and its included tools like Snort, Sguil, Squert and OSSEC. It describes configuring Security Onion sensors to monitor network traffic and logs, storing alerts in databases, and using the management consoles to analyze alerts. The goal is to create a comprehensive security monitoring platform through centralized log management and correlation of network and host-based events.
An Assessment of Intrusion Detection System IDS and Data Set Overview A Compr...ijtsrd
Millions of people worldwide have Internet access today. Intrusion detection technology is a modern wave of information technology monitoring devices to deter malicious activities. Malware development malicious software is a vital problem when it comes to designing intrusion detection systems IDS . The key challenge is to recognize unknown and hidden malware, because malware writers use various evasion techniques to mask information to avoid IDS detection. Malicious attacks have become more sophisticated and Furthermore, threats to security have increased, including a zero day attack on internet users. Through the use of IT in our daily lives, computer security has become critical. Cyber threats are becoming more complex and pose growing challenges when it comes to successful intrusion detection. Failure to prevent invading information, such as data privacy, integrity and availability can undermine the credibility of security services. Specific intrusion detection approaches were proposed in the literature to combat computer security threats. This paper consists of a literature survey of the IDS that uses program algorithms to use specific data collection and forensic techniques in real time. Data mining techniques for cyber research are introduced in support of intrusion detection. Mohammed I. Alghamdi "An Assessment of Intrusion Detection System (IDS) and Data-Set Overview: A Comprehensive Review of Recent Works" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-2 , February 2021, URL: https://www.ijtsrd.com/papers/ijtsrd35730.pdf Paper Url: https://www.ijtsrd.com/computer-science/computer-security/35730/an-assessment-of-intrusion-detection-system-ids-and-dataset-overview-a-comprehensive-review-of-recent-works/mohammed-i-alghamdi
Comparative Study on Intrusion Detection Systems for Smartphonesiosrjce
IOSR Journal of Computer Engineering (IOSR-JCE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of computer engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in computer technology. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
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.
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 System (IDS): Anomaly Detection using Outlier Detection A...Drjabez
This document describes a proposed approach for anomaly detection in intrusion detection systems using outlier detection. It begins with background on intrusion detection systems and issues with existing approaches. It then presents the proposed two-stage approach using outlier detection: 1) Training with large normal datasets in a distributed storage environment, and 2) Testing intrusion datasets to compute an error value compared to the trained model. If the error value exceeds a threshold, the test data is flagged as anomalous. Experimental results on network packet datasets demonstrate the approach can effectively identify anomalies.
Analytical survey of active intrusion detection techniques in mobile ad hoc n...eSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
The spread of information networks in communities and organizations have led to a daily huge volume of information exchange between different networks which, of course, has resulted in new threats to the national organizations. It can be said that information security has become today one of the most challenging areas. In other words, defects and disadvantages of computer network security address irreparable damage for enterprises. Therefore, identification of security threats and ways of dealing with them is essential. But the question raised in this regard is that what are the strategies and policies to deal with security threats that must be taken to ensure the security of computer networks? In this context, the present study intends to do a review of the literature by using earlier researches and library approach, to provide security solutions in the face of threats to their computer networks. The results of this research can lead to more understanding of security threats and ways to deal with them and help to implement a secure information platform.
Intrusion detection systems aim to detect unauthorized access or activity in a computer system or network. There are two main types: network-based systems monitor network traffic to detect intrusions, while host-based systems monitor operating system logs and files on individual computers. Effective intrusion detection requires an incident response team to assess damage from intrusions and prevent future vulnerabilities, as well as securely storing logs as potential evidence.
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.
NETWORK INTRUSION DETECTION AND NODE RECOVERY USING DYNAMIC PATH ROUTINGNishanth Gandhidoss
This document describes a project report submitted for the degree of Bachelor of Technology in Information Technology. The report focuses on network intrusion detection and node recovery using dynamic path routing. It was submitted by three students - Nishanth G., Sudharshan N., and Surya Krishnan R. - to Sri Venkateswara College of Engineering in partial fulfillment of their degree requirements. The document includes sections on acknowledgements, abstract, contents, introduction, literature survey, system design, network topology, network intrusion detection and prevention, node recovery, source anonymity, dynamic path routing, results and discussions, and conclusions. It aims to address privacy and security issues in networks through techniques like encryption, evidence collection, risk assessment
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
This document discusses network intrusion detection systems (NIDS) and their ability to handle high-speed traffic. It introduces NIDS and their role in monitoring network traffic. The document presents an experiment that tests the open-source NIDS Snort under high-volume traffic. The experiment shows that Snort drops more packets as traffic speed and volume increases, demonstrating a weakness of NIDS in high-speed environments. It suggests using a parallel NIDS technique to help NIDS better handle high-speed network traffic and reduce packet dropping.
The Next Generation Cognitive Security Operations Center: Network Flow Forens...Konstantinos Demertzis
A Security Operations Center (SOC) can be defined as an organized and highly skilled team that uses advanced computer forensics tools to prevent, detect and respond to cybersecurity incidents of an organization. The fundamental aspects of an effective SOC is related to the ability to examine and analyze the vast number of data flows and to correlate several other types of events from a cybersecurity perception. The supervision and categorization of network flow is an essential process not only for the scheduling, management, and regulation of the network’s services, but also for attacks identification and for the consequent forensics’ investigations. A serious potential disadvantage of the traditional software solutions used today for computer network monitoring, and specifically for the instances of effective categorization of the encrypted or obfuscated network flow, which enforces the rebuilding of messages packets in sophisticated underlying protocols, is the requirements of computational resources. In addition, an additional significant inability of these software packages is they create high false positive rates because they are deprived of accurate predicting mechanisms.
For all the reasons above, in most cases, the traditional software fails completely to recognize unidentified vulnerabilities and zero-day exploitations. This paper proposes a novel intelligence driven Network Flow Forensics Framework (NF3) which uses low utilization of computing power and resources, for the Next Generation Cognitive Computing SOC (NGC2SOC) that rely solely on advanced fully automated intelligence methods. It is an effective and accurate Ensemble Machine Learning forensics tool to Network Traffic Analysis, Demystification of Malware Traffic and Encrypted Traffic Identification.
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.
A Study on Recent Trends and Developments in Intrusion Detection SystemIOSR Journals
This document discusses recent trends and developments in intrusion detection systems. It covers several topics:
- Artificial intelligence and machine learning techniques like neural networks, genetic algorithms, and fuzzy logic can be applied to intrusion detection to improve detection capabilities.
- There are different types of intrusion detection systems, including network-based, host-based, and wireless intrusion detection. Signature-based and anomaly-based detection are also discussed.
- Popular open source intrusion detection tools like Snort are discussed as alternatives to commercial intrusion prevention systems for some organizations.
- Intrusion prevention systems not only detect attacks but can also block attacks in real-time, providing an enhanced level of protection over intrusion
International Journal of Engineering Research and Development (IJERD)IJERD Editor
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Detection of Rogue Access Point in WLAN using Hopfield Neural Network IJECEIAES
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.
Survey on Security Issues of Internet of Things (IoT) DevicesIRJET Journal
This document summarizes security issues with common Internet of Things (IoT) devices. It discusses vulnerabilities in RFID tags, Bluetooth beacons, and Raspberry Pi systems. RFID tags can be cloned or have unauthorized access. Beacons are at risk of piggybacking, cloning, and hijacking attacks. Default credentials on Raspberry Pi leave systems exposed. Overall, the lack of secure authentication and encryption on many IoT devices makes the emerging network of connected objects vulnerable to cyberattacks.
Enhanced method for intrusion detection over kdd cup 99 datasetijctet
This document discusses an enhanced method for intrusion detection using the KDD Cup 99 dataset. It aims to improve the accuracy of the dataset by analyzing the contribution of different attack classes to metrics like true positive rate and precision. The study examines these evaluation metrics for an intrusion detection system to identify which attack classes most impact recall and precision. The goal is to help improve the quality of the KDD Cup 99 dataset to achieve higher accuracy with lower false positives.
This document provides an overview of intrusion detection systems (IDS). It discusses different types of IDS including host-based IDS, which monitor system logs and user behavior on individual hosts, and network-based IDS, which monitor network traffic. It focuses on stateful dynamic signature inspection (SDSI) as an advanced network IDS approach and describes NetProwler as a commercial SDSI system that provides real-time intrusion detection for networks. The document aims to explain everything needed to know about intrusion detection.
IMPROVED IDS USING LAYERED CRFS WITH LOGON RESTRICTIONS AND MOBILE ALERTS BAS...IJNSA Journal
With the ever increasing number and diverse type of attacks, including new and previously unseen attacks, the effectiveness of an Intrusion Detection System is very important. Hence there is high demand to reduce the threat level in networks to ensure the data and services offered by them to be more secure. In this paper we developed an effective test suite for improving the efficiency and accuracy of an intrusion detection system using the layered CRFs. We set up different types of checks at multiple levels in each layer. Our framework examines various attributes at every layer in order to effectively identify any breach of security. Once the attack is detected, it is intimated through mobile phone to the system administrator for safeguarding the server system. We established experimentally that the layered CRFs can thus be more effective in detecting intrusions when compared with the other previously known techniques.
1. Cyber Ethics and Cyber Crime
2. Security in Social Media & Risk of Child Internet
3. Social media in Schools and photo privacy
4. Risk of OSNs and Security, Privacy of Facebook
5. Risk and Security of Social Networking site Facebook and Twitter
6. Risk analysis of Government and Online Transaction
Automatic Intrusion Detection based on Artificial Intelligence Techniques: A ...IRJET Journal
This document provides a literature review on automatic intrusion detection systems based on artificial intelligence techniques. It discusses how machine learning algorithms like neural networks, decision trees, KNN, and SVM have been applied to develop intrusion detection systems. Both supervised and unsupervised learning techniques are investigated. The review finds that the NSL-KDD dataset is commonly used and that accuracy, precision, recall, AUC and F1 score are typical evaluation metrics. However, it notes that a limitation of classification-based approaches is the inability to detect novel or modified attack types. The document recommends future work focus on techniques that can identify anomalous intrusions.
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.
A REVIEW ON INTRUSION DETECTION SYSTEMLaurie Smith
The document provides a review of intrusion detection systems (IDS). It discusses that IDS are used to monitor network traffic and system activities to identify potential threats. There are two main types of IDS - host-based IDS that monitor individual systems, and network-based IDS that monitor entire networks. The document also outlines the common functions of IDS, which include collecting information, analyzing for threats, responding with alerts or blocks, and notifying administrators. Intrusion detection is important for network security as it acts as an additional layer of protection and can help identify intrusions and vulnerabilities.
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 System (IDS): Anomaly Detection using Outlier Detection A...Drjabez
This document describes a proposed approach for anomaly detection in intrusion detection systems using outlier detection. It begins with background on intrusion detection systems and issues with existing approaches. It then presents the proposed two-stage approach using outlier detection: 1) Training with large normal datasets in a distributed storage environment, and 2) Testing intrusion datasets to compute an error value compared to the trained model. If the error value exceeds a threshold, the test data is flagged as anomalous. Experimental results on network packet datasets demonstrate the approach can effectively identify anomalies.
Analytical survey of active intrusion detection techniques in mobile ad hoc n...eSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
The spread of information networks in communities and organizations have led to a daily huge volume of information exchange between different networks which, of course, has resulted in new threats to the national organizations. It can be said that information security has become today one of the most challenging areas. In other words, defects and disadvantages of computer network security address irreparable damage for enterprises. Therefore, identification of security threats and ways of dealing with them is essential. But the question raised in this regard is that what are the strategies and policies to deal with security threats that must be taken to ensure the security of computer networks? In this context, the present study intends to do a review of the literature by using earlier researches and library approach, to provide security solutions in the face of threats to their computer networks. The results of this research can lead to more understanding of security threats and ways to deal with them and help to implement a secure information platform.
Intrusion detection systems aim to detect unauthorized access or activity in a computer system or network. There are two main types: network-based systems monitor network traffic to detect intrusions, while host-based systems monitor operating system logs and files on individual computers. Effective intrusion detection requires an incident response team to assess damage from intrusions and prevent future vulnerabilities, as well as securely storing logs as potential evidence.
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.
NETWORK INTRUSION DETECTION AND NODE RECOVERY USING DYNAMIC PATH ROUTINGNishanth Gandhidoss
This document describes a project report submitted for the degree of Bachelor of Technology in Information Technology. The report focuses on network intrusion detection and node recovery using dynamic path routing. It was submitted by three students - Nishanth G., Sudharshan N., and Surya Krishnan R. - to Sri Venkateswara College of Engineering in partial fulfillment of their degree requirements. The document includes sections on acknowledgements, abstract, contents, introduction, literature survey, system design, network topology, network intrusion detection and prevention, node recovery, source anonymity, dynamic path routing, results and discussions, and conclusions. It aims to address privacy and security issues in networks through techniques like encryption, evidence collection, risk assessment
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
This document discusses network intrusion detection systems (NIDS) and their ability to handle high-speed traffic. It introduces NIDS and their role in monitoring network traffic. The document presents an experiment that tests the open-source NIDS Snort under high-volume traffic. The experiment shows that Snort drops more packets as traffic speed and volume increases, demonstrating a weakness of NIDS in high-speed environments. It suggests using a parallel NIDS technique to help NIDS better handle high-speed network traffic and reduce packet dropping.
The Next Generation Cognitive Security Operations Center: Network Flow Forens...Konstantinos Demertzis
A Security Operations Center (SOC) can be defined as an organized and highly skilled team that uses advanced computer forensics tools to prevent, detect and respond to cybersecurity incidents of an organization. The fundamental aspects of an effective SOC is related to the ability to examine and analyze the vast number of data flows and to correlate several other types of events from a cybersecurity perception. The supervision and categorization of network flow is an essential process not only for the scheduling, management, and regulation of the network’s services, but also for attacks identification and for the consequent forensics’ investigations. A serious potential disadvantage of the traditional software solutions used today for computer network monitoring, and specifically for the instances of effective categorization of the encrypted or obfuscated network flow, which enforces the rebuilding of messages packets in sophisticated underlying protocols, is the requirements of computational resources. In addition, an additional significant inability of these software packages is they create high false positive rates because they are deprived of accurate predicting mechanisms.
For all the reasons above, in most cases, the traditional software fails completely to recognize unidentified vulnerabilities and zero-day exploitations. This paper proposes a novel intelligence driven Network Flow Forensics Framework (NF3) which uses low utilization of computing power and resources, for the Next Generation Cognitive Computing SOC (NGC2SOC) that rely solely on advanced fully automated intelligence methods. It is an effective and accurate Ensemble Machine Learning forensics tool to Network Traffic Analysis, Demystification of Malware Traffic and Encrypted Traffic Identification.
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.
A Study on Recent Trends and Developments in Intrusion Detection SystemIOSR Journals
This document discusses recent trends and developments in intrusion detection systems. It covers several topics:
- Artificial intelligence and machine learning techniques like neural networks, genetic algorithms, and fuzzy logic can be applied to intrusion detection to improve detection capabilities.
- There are different types of intrusion detection systems, including network-based, host-based, and wireless intrusion detection. Signature-based and anomaly-based detection are also discussed.
- Popular open source intrusion detection tools like Snort are discussed as alternatives to commercial intrusion prevention systems for some organizations.
- Intrusion prevention systems not only detect attacks but can also block attacks in real-time, providing an enhanced level of protection over intrusion
International Journal of Engineering Research and Development (IJERD)IJERD Editor
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Detection of Rogue Access Point in WLAN using Hopfield Neural Network IJECEIAES
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.
Survey on Security Issues of Internet of Things (IoT) DevicesIRJET Journal
This document summarizes security issues with common Internet of Things (IoT) devices. It discusses vulnerabilities in RFID tags, Bluetooth beacons, and Raspberry Pi systems. RFID tags can be cloned or have unauthorized access. Beacons are at risk of piggybacking, cloning, and hijacking attacks. Default credentials on Raspberry Pi leave systems exposed. Overall, the lack of secure authentication and encryption on many IoT devices makes the emerging network of connected objects vulnerable to cyberattacks.
Enhanced method for intrusion detection over kdd cup 99 datasetijctet
This document discusses an enhanced method for intrusion detection using the KDD Cup 99 dataset. It aims to improve the accuracy of the dataset by analyzing the contribution of different attack classes to metrics like true positive rate and precision. The study examines these evaluation metrics for an intrusion detection system to identify which attack classes most impact recall and precision. The goal is to help improve the quality of the KDD Cup 99 dataset to achieve higher accuracy with lower false positives.
This document provides an overview of intrusion detection systems (IDS). It discusses different types of IDS including host-based IDS, which monitor system logs and user behavior on individual hosts, and network-based IDS, which monitor network traffic. It focuses on stateful dynamic signature inspection (SDSI) as an advanced network IDS approach and describes NetProwler as a commercial SDSI system that provides real-time intrusion detection for networks. The document aims to explain everything needed to know about intrusion detection.
IMPROVED IDS USING LAYERED CRFS WITH LOGON RESTRICTIONS AND MOBILE ALERTS BAS...IJNSA Journal
With the ever increasing number and diverse type of attacks, including new and previously unseen attacks, the effectiveness of an Intrusion Detection System is very important. Hence there is high demand to reduce the threat level in networks to ensure the data and services offered by them to be more secure. In this paper we developed an effective test suite for improving the efficiency and accuracy of an intrusion detection system using the layered CRFs. We set up different types of checks at multiple levels in each layer. Our framework examines various attributes at every layer in order to effectively identify any breach of security. Once the attack is detected, it is intimated through mobile phone to the system administrator for safeguarding the server system. We established experimentally that the layered CRFs can thus be more effective in detecting intrusions when compared with the other previously known techniques.
1. Cyber Ethics and Cyber Crime
2. Security in Social Media & Risk of Child Internet
3. Social media in Schools and photo privacy
4. Risk of OSNs and Security, Privacy of Facebook
5. Risk and Security of Social Networking site Facebook and Twitter
6. Risk analysis of Government and Online Transaction
Automatic Intrusion Detection based on Artificial Intelligence Techniques: A ...IRJET Journal
This document provides a literature review on automatic intrusion detection systems based on artificial intelligence techniques. It discusses how machine learning algorithms like neural networks, decision trees, KNN, and SVM have been applied to develop intrusion detection systems. Both supervised and unsupervised learning techniques are investigated. The review finds that the NSL-KDD dataset is commonly used and that accuracy, precision, recall, AUC and F1 score are typical evaluation metrics. However, it notes that a limitation of classification-based approaches is the inability to detect novel or modified attack types. The document recommends future work focus on techniques that can identify anomalous intrusions.
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.
A REVIEW ON INTRUSION DETECTION SYSTEMLaurie Smith
The document provides a review of intrusion detection systems (IDS). It discusses that IDS are used to monitor network traffic and system activities to identify potential threats. There are two main types of IDS - host-based IDS that monitor individual systems, and network-based IDS that monitor entire networks. The document also outlines the common functions of IDS, which include collecting information, analyzing for threats, responding with alerts or blocks, and notifying administrators. Intrusion detection is important for network security as it acts as an additional layer of protection and can help identify intrusions and vulnerabilities.
INTRUSION DETECTION SYSTEM USING CUSTOMIZED RULES FOR SNORTIJMIT JOURNAL
This document proposes an intrusion detection system using customized rules for the Snort tool to improve security. The system uses Wireshark to scan network traffic for anomalies, Snort to detect attacks using customized rulesets for faster response times, and Wazuh and Splunk to analyze log files. Rules are created using the Snorpy tool and added to Snort to monitor for specific attacks like ICMP ping impersonation and authentication attempts. When attacks are attempted, the system successfully detects them and logs the alerts. The integration of these tools provides low-cost intrusion detection capabilities with automated threat identification and faster response compared to existing Snort configurations.
Detecting Various Intrusion Attacks using A Fuzzy Triangular Membership FunctionIRJET Journal
This document discusses using a fuzzy triangular membership function to detect various types of intrusion attacks. It begins with an abstract that introduces the topic and importance of intrusion detection with the growth of computer networks and cyber attacks. It then provides background on intrusion detection systems, including how they work, common techniques like supervised learning, and the challenges with techniques like neural networks. The document focuses on using a fuzzy triangular membership function for intrusion detection and normalization of data. It reviews related literature on fuzzy logic approaches to intrusion detection and discusses the KDD dataset often used for testing intrusion detection systems.
Intrusion Detection System using AI and Machine Learning AlgorithmIRJET Journal
This document discusses using artificial intelligence and machine learning algorithms to develop an intrusion detection system (IDS). It begins with an abstract that outlines using AI to act as a virtual analyst to concurrently monitor network traffic and defend against threats. It then provides background on IDS and the need for more effective automated threat detection. The document discusses classifying attacks, different types of IDS (host-based and network-based), and detection methods like signature-based and anomaly-based. It aims to develop an IDS using machine learning algorithms that can learn patterns to provide automatic intrusion detection without extensive manual maintenance.
This document summarizes a proposed network attack alerting system that aims to reduce the large number of alerts generated by intrusion detection systems (IDS). The system uses both network-based and host-based IDS to detect attacks launched using the Backtrack attacking tools on a virtual network lab environment. Well-known open source security tools on the Security Onion Linux distribution are used to generate alerts. The system defines rules to identify important alert types and stores alerts in a database. It aims to eliminate redundant alerts for the same attack by analyzing attributes like source/destination IP and port. Alert severity levels are defined using threshold counts and times to classify alerts and help administrators respond appropriately.
This document summarizes a proposed network attack alerting system that aims to reduce redundant alerts from intrusion detection systems (IDS). The system uses both network-based and host-based IDS to detect attacks launched using the Backtrack penetration testing tool on a virtual network environment. Well-known open source IDS tools from the Security Onion distribution are used to generate alerts. The system builds a database of alerts and defines rules to eliminate duplicate alerts for the same attack based on attributes like source/destination IP and port. It also establishes a severity classification scheme using threshold values of alerts and time to help administrators prioritize responses.
A Review Of Intrusion Detection System In Computer NetworkAudrey Britton
This document provides an overview of intrusion detection systems (IDS) and the techniques used to implement them. It discusses that IDS are used to detect malicious actions on computer networks and protect important files and documents. The document then summarizes that IDS have four main components - sensors to monitor the system, a database to store event information, an analysis module to detect potential threats, and a response module to address detected threats. It also categorizes IDS based on the data source, detection approach, structure, and how intrusions are detected. Finally, the document outlines various techniques used in IDS, including artificial intelligence methods like neural networks, fuzzy logic, genetic algorithms and machine learning approaches.
This document summarizes an international journal on information technology and management information systems. It discusses detecting and classifying attacks in a computer network. Existing approaches to intrusion detection include anomaly-based systems, host-based intrusion detection systems (HIDS), and network-based intrusion detection systems (NIDS). A multilayer perceptron (MLP) algorithm is commonly used for intrusion detection but has limitations. The paper proposes a modified apriori algorithm to generate rules for detecting and classifying attacks into categories and types to enable recommending appropriate responses.
Intrusion detection system: classification, techniques and datasets to implementIRJET Journal
This document discusses intrusion detection systems, including their classification techniques and datasets used to implement them. It first defines intrusion detection and intrusion detection systems, explaining that they monitor networks and systems for malicious activity and policy violations. It then categorizes intrusion detection systems as either network-based, host-based, or physical-based. The document also classifies intrusion detection approaches as either signature-based (misuse detection) or anomaly-based detection. It reviews several data mining techniques used for intrusion detection, including classification methods like decision trees, k-nearest neighbors, naive Bayes, and support vector machines. It also discusses clustering techniques. Finally, it mentions some commonly used intrusion detection datasets.
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.
A Comprehensive Review On Intrusion Detection System And TechniquesKelly Taylor
This document discusses machine learning techniques for intrusion detection systems (IDS). It provides an overview of the research progress using machine learning to improve intrusion detection in networks. Machine learning and data mining techniques have been widely used to automatically detect network traffic anomalies. The goal is to summarize and compare research contributions of IDS using machine learning, define existing challenges, and discuss anticipated solutions. Commonly used machine learning techniques for IDS are reviewed along with some existing machine learning-based IDS proposed by researchers.
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.
Survey on Host and Network Based Intrusion Detection SystemEswar Publications
With invent of new technologies and devices, Intrusion has become an area of concern because of security issues, in the ever growing area of cyber-attack. An intrusion detection system (IDS) is defined as a device or software application which monitors system or network activities for malicious activities or policy violations. It produces reports to a management station [1]. In this paper we are mainly focused on different IDS concepts based on Host and Network systems.
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.
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
Current Studies On Intrusion Detection System, Genetic Algorithm And Fuzzy Logicijdpsjournal
This document summarizes a research paper on current studies of intrusion detection systems using genetic algorithms and fuzzy logic. The paper presents an overview of intrusion detection systems, including different techniques like misuse detection and anomaly detection. It discusses using genetic algorithms to generate fuzzy rules to characterize normal and abnormal network behavior in order to reduce false alarms. The paper also outlines the dataset, genetic algorithm approach, and use of fuzzy logic that are proposed for the intrusion detection system.
Analysis of Artificial Intelligence Techniques for Network Intrusion Detectio...IIJSRJournal
With the rapid advancement of computer technology during the last couple of decades. Computer systems are commonly used in manufacturing, corporate, as well as other aspects of human living. As a result, constructing dependable infrastructures is a major challenge for IT managers. On the contrary side, this same rapid advancement of technology has created numerous difficulties in building reliable networks which are challenging tasks. There seem to be numerous varieties of attacks that affect the accessibility, authenticity, as well as secrecy of communications systems. In this paper, an in-depth and all-inclusive description of artificial intelligence methods used for the detection of network intrusions is discussed in detail.
AN IMPROVED METHOD TO DETECT INTRUSION USING MACHINE LEARNING ALGORITHMSieijjournal
An intrusion detection system detects various malicious behaviors and abnormal activities that might harm
security and trust of computer system. IDS operate either on host or network level via utilizing anomaly
detection or misuse detection. Main problem is to correctly detect intruder attack against computer
network. The key point of successful detection of intrusion is choice of proper features. To resolve the
problems of IDS scheme this research work propose “an improved method to detect intrusion using
machine learning algorithms”. In our paper we use KDDCUP 99 dataset to analyze efficiency of intrusion
detection with different machine learning algorithms like Bayes, NaiveBayes, J48, J48Graft and Random
forest. To identify network based IDS with KDDCUP 99 dataset, experimental results shows that the three
algorithms J48, J48Graft and Random forest gives much better results than other machine learning
algorithms. We use WEKA to check the accuracy of classified dataset via our proposed method. We have
considered all the parameter for computation of result i.e. precision, recall, F – measure and ROC.
Submission Deadline: 30th September 2022
Acceptance Notification: Within Three Days’ time period
Online Publication: Within 24 Hrs. time Period
Expected Date of Dispatch of Printed Journal: 5th October 2022
MODELING AND ANALYSIS OF SURFACE ROUGHNESS AND WHITE LATER THICKNESS IN WIRE-...IAEME Publication
White layer thickness (WLT) formed and surface roughness in wire electric discharge turning (WEDT) of tungsten carbide composite has been made to model through response surface methodology (RSM). A Taguchi’s standard Design of experiments involving five input variables with three levels has been employed to establish a mathematical model between input parameters and responses. Percentage of cobalt content, spindle speed, Pulse on-time, wire feed and pulse off-time were changed during the experimental tests based on the Taguchi’s orthogonal array L27 (3^13). Analysis of variance (ANOVA) revealed that the mathematical models obtained can adequately describe performance within the parameters of the factors considered. There was a good agreement between the experimental and predicted values in this study.
A STUDY ON THE REASONS FOR TRANSGENDER TO BECOME ENTREPRENEURSIAEME Publication
The study explores the reasons for a transgender to become entrepreneurs. In this study transgender entrepreneur was taken as independent variable and reasons to become as dependent variable. Data were collected through a structured questionnaire containing a five point Likert Scale. The study examined the data of 30 transgender entrepreneurs in Salem Municipal Corporation of Tamil Nadu State, India. Simple Random sampling technique was used. Garrett Ranking Technique (Percentile Position, Mean Scores) was used as the analysis for the present study to identify the top 13 stimulus factors for establishment of trans entrepreneurial venture. Economic advancement of a nation is governed upon the upshot of a resolute entrepreneurial doings. The conception of entrepreneurship has stretched and materialized to the socially deflated uncharted sections of transgender community. Presently transgenders have smashed their stereotypes and are making recent headlines of achievements in various fields of our Indian society. The trans-community is gradually being observed in a new light and has been trying to achieve prospective growth in entrepreneurship. The findings of the research revealed that the optimistic changes are taking place to change affirmative societal outlook of the transgender for entrepreneurial ventureship. It also laid emphasis on other transgenders to renovate their traditional living. The paper also highlights that legislators, supervisory body should endorse an impartial canons and reforms in Tamil Nadu Transgender Welfare Board Association.
BROAD UNEXPOSED SKILLS OF TRANSGENDER ENTREPRENEURSIAEME Publication
Since ages gender difference is always a debatable theme whether caused by nature, evolution or environment. The birth of a transgender is dreadful not only for the child but also for their parents. The pain of living in the wrong physique and treated as second class victimized citizen is outrageous and fully harboured with vicious baseless negative scruples. For so long, social exclusion had perpetuated inequality and deprivation experiencing ingrained malign stigma and besieged victims of crime or violence across their life spans. They are pushed into the murky way of life with a source of eternal disgust, bereft sexual potency and perennial fear. Although they are highly visible but very little is known about them. The common public needs to comprehend the ravaged arrogance on these insensitive souls and assist in integrating them into the mainstream by offering equal opportunity, treat with humanity and respect their dignity. Entrepreneurship in the current age is endorsing the gender fairness movement. Unstable careers and economic inadequacy had inclined one of the gender variant people called Transgender to become entrepreneurs. These tiny budding entrepreneurs resulted in economic transition by means of employment, free from the clutches of stereotype jobs, raised standard of living and handful of financial empowerment. Besides all these inhibitions, they were able to witness a platform for skill set development that ignited them to enter into entrepreneurial domain. This paper epitomizes skill sets involved in trans-entrepreneurs of Thoothukudi Municipal Corporation of Tamil Nadu State and is a groundbreaking determination to sightsee various skills incorporated and the impact on entrepreneurship.
DETERMINANTS AFFECTING THE USER'S INTENTION TO USE MOBILE BANKING APPLICATIONSIAEME Publication
The banking and financial services industries are experiencing increased technology penetration. Among them, the banking industry has made technological advancements to better serve the general populace. The economy focused on transforming the banking sector's system into a cashless, paperless, and faceless one. The researcher wants to evaluate the user's intention for utilising a mobile banking application. The study also examines the variables affecting the user's behaviour intention when selecting specific applications for financial transactions. The researcher employed a well-structured questionnaire and a descriptive study methodology to gather the respondents' primary data utilising the snowball sampling technique. The study includes variables like performance expectations, effort expectations, social impact, enabling circumstances, and perceived risk. Each of the aforementioned variables has a major impact on how users utilise mobile banking applications. The outcome will assist the service provider in comprehending the user's history with mobile banking applications.
ANALYSE THE USER PREDILECTION ON GPAY AND PHONEPE FOR DIGITAL TRANSACTIONSIAEME Publication
Technology upgradation in banking sector took the economy to view that payment mode towards online transactions using mobile applications. This system enabled connectivity between banks, Merchant and user in a convenient mode. there are various applications used for online transactions such as Google pay, Paytm, freecharge, mobikiwi, oxygen, phonepe and so on and it also includes mobile banking applications. The study aimed at evaluating the predilection of the user in adopting digital transaction. The study is descriptive in nature. The researcher used random sample techniques to collect the data. The findings reveal that mobile applications differ with the quality of service rendered by Gpay and Phonepe. The researcher suggest the Phonepe application should focus on implementing the application should be user friendly interface and Gpay on motivating the users to feel the importance of request for money and modes of payments in the application.
VOICE BASED ATM FOR VISUALLY IMPAIRED USING ARDUINOIAEME Publication
The prototype of a voice-based ATM for visually impaired using Arduino is to help people who are blind. This uses RFID cards which contain users fingerprint encrypted on it and interacts with the users through voice commands. ATM operates when sensor detects the presence of one person in the cabin. After scanning the RFID card, it will ask to select the mode like –normal or blind. User can select the respective mode through voice input, if blind mode is selected the balance check or cash withdraw can be done through voice input. Normal mode procedure is same as the existing ATM.
IMPACT OF EMOTIONAL INTELLIGENCE ON HUMAN RESOURCE MANAGEMENT PRACTICES AMONG...IAEME Publication
There is increasing acceptability of emotional intelligence as a major factor in personality assessment and effective human resource management. Emotional intelligence as the ability to build capacity, empathize, co-operate, motivate and develop others cannot be divorced from both effective performance and human resource management systems. The human person is crucial in defining organizational leadership and fortunes in terms of challenges and opportunities and walking across both multinational and bilateral relationships. The growing complexity of the business world requires a great deal of self-confidence, integrity, communication, conflict and diversity management to keep the global enterprise within the paths of productivity and sustainability. Using the exploratory research design and 255 participants the result of this original study indicates strong positive correlation between emotional intelligence and effective human resource management. The paper offers suggestions on further studies between emotional intelligence and human capital development and recommends for conflict management as an integral part of effective human resource management.
VISUALISING AGING PARENTS & THEIR CLOSE CARERS LIFE JOURNEY IN AGING ECONOMYIAEME Publication
Our life journey, in general, is closely defined by the way we understand the meaning of why we coexist and deal with its challenges. As we develop the "inspiration economy", we could say that nearly all of the challenges we have faced are opportunities that help us to discover the rest of our journey. In this note paper, we explore how being faced with the opportunity of being a close carer for an aging parent with dementia brought intangible discoveries that changed our insight of the meaning of the rest of our life journey.
A STUDY ON THE IMPACT OF ORGANIZATIONAL CULTURE ON THE EFFECTIVENESS OF PERFO...IAEME Publication
The main objective of this study is to analyze the impact of aspects of Organizational Culture on the Effectiveness of the Performance Management System (PMS) in the Health Care Organization at Thanjavur. Organizational Culture and PMS play a crucial role in present-day organizations in achieving their objectives. PMS needs employees’ cooperation to achieve its intended objectives. Employees' cooperation depends upon the organization’s culture. The present study uses exploratory research to examine the relationship between the Organization's culture and the Effectiveness of the Performance Management System. The study uses a Structured Questionnaire to collect the primary data. For this study, Thirty-six non-clinical employees were selected from twelve randomly selected Health Care organizations at Thanjavur. Thirty-two fully completed questionnaires were received.
Living in 21st century in itself reminds all of us the necessity of police and its administration. As more and more we are entering into the modern society and culture, the more we require the services of the so called ‘Khaki Worthy’ men i.e., the police personnel. Whether we talk of Indian police or the other nation’s police, they all have the same recognition as they have in India. But as already mentioned, their services and requirements are different after the like 26th November, 2008 incidents, where they without saving their own lives has sacrificed themselves without any hitch and without caring about their respective family members and wards. In other words, they are like our heroes and mentors who can guide us from the darkness of fear, militancy, corruption and other dark sides of life and so on. Now the question arises, if Gandhi would have been alive today, what would have been his reaction/opinion to the police and its functioning? Would he have some thing different in his mind now what he had been in his mind before the partition or would he be going to start some Satyagraha in the form of some improvement in the functioning of the police administration? Really these questions or rather night mares can come to any one’s mind, when there is too much confusion is prevailing in our minds, when there is too much corruption in the society and when the polices working is also in the questioning because of one or the other case throughout the India. It is matter of great concern that we have to thing over our administration and our practical approach because the police personals are also like us, they are part and parcel of our society and among one of us, so why we all are pin pointing towards them.
A STUDY ON TALENT MANAGEMENT AND ITS IMPACT ON EMPLOYEE RETENTION IN SELECTED...IAEME Publication
The goal of this study was to see how talent management affected employee retention in the selected IT organizations in Chennai. The fundamental issue was the difficulty to attract, hire, and retain talented personnel who perform well and the gap between supply and demand of talent acquisition and retaining them within the firms. The study's main goals were to determine the impact of talent management on employee retention in IT companies in Chennai, investigate talent management strategies that IT companies could use to improve talent acquisition, performance management, career planning and formulate retention strategies that the IT firms could use. The respondents were given a structured close-ended questionnaire with the 5 Point Likert Scale as part of the study's quantitative research design. The target population consisted of 289 IT professionals. The questionnaires were distributed and collected by the researcher directly. The Statistical Package for Social Sciences (SPSS) was used to collect and analyse the questionnaire responses. Hypotheses that were formulated for the various areas of the study were tested using a variety of statistical tests. The key findings of the study suggested that talent management had an impact on employee retention. The studies also found that there is a clear link between the implementation of talent management and retention measures. Management should provide enough training and development for employees, clarify job responsibilities, provide adequate remuneration packages, and recognise employees for exceptional performance.
ATTRITION IN THE IT INDUSTRY DURING COVID-19 PANDEMIC: LINKING EMOTIONAL INTE...IAEME Publication
Globally, Millions of dollars were spent by the organizations for employing skilled Information Technology (IT) professionals. It is costly to replace unskilled employees with IT professionals possessing technical skills and competencies that aid in interconnecting the business processes. The organization’s employment tactics were forced to alter by globalization along with technological innovations as they consistently diminish to remain lean, outsource to concentrate on core competencies along with restructuring/reallocate personnel to gather efficiency. As other jobs, organizations or professions have become reasonably more appropriate in a shifting employment landscape, the above alterations trigger both involuntary as well as voluntary turnover. The employee view on jobs is also afflicted by the COVID-19 pandemic along with the employee-driven labour market. So, having effective strategies is necessary to tackle the withdrawal rate of employees. By associating Emotional Intelligence (EI) along with Talent Management (TM) in the IT industry, the rise in attrition rate was analyzed in this study. Only 303 respondents were collected out of 350 participants to whom questionnaires were distributed. From the employees of IT organizations located in Bangalore (India), the data were congregated. A simple random sampling methodology was employed to congregate data as of the respondents. Generating the hypothesis along with testing is eventuated. The effect of EI and TM along with regression analysis between TM and EI was analyzed. The outcomes indicated that employee and Organizational Performance (OP) were elevated by effective EI along with TM.
INFLUENCE OF TALENT MANAGEMENT PRACTICES ON ORGANIZATIONAL PERFORMANCE A STUD...IAEME Publication
By implementing talent management strategy, organizations would have the option to retain their skilled professionals while additionally working on their overall performance. It is the course of appropriately utilizing the ideal individuals, setting them up for future top positions, exploring and dealing with their performance, and holding them back from leaving the organization. It is employee performance that determines the success of every organization. The firm quickly obtains an upper hand over its rivals in the event that its employees having particular skills that cannot be duplicated by the competitors. Thus, firms are centred on creating successful talent management practices and processes to deal with the unique human resources. Firms are additionally endeavouring to keep their top/key staff since on the off chance that they leave; the whole store of information leaves the firm's hands. The study's objective was to determine the impact of talent management on organizational performance among the selected IT organizations in Chennai. The study recommends that talent management limitedly affects performance. On the off chance that this talent is appropriately management and implemented properly, organizations might benefit as much as possible from their maintained assets to support development and productivity, both monetarily and non-monetarily.
A STUDY OF VARIOUS TYPES OF LOANS OF SELECTED PUBLIC AND PRIVATE SECTOR BANKS...IAEME Publication
Banking regulations act of India, 1949 defines banking as “acceptance of deposits for the purpose of lending or investment from the public, repayment on demand or otherwise and withdrawable through cheques, drafts order or otherwise”, the major participants of the Indian financial system are commercial banks, the financial institution encompassing term lending institutions. Investments institutions, specialized financial institution and the state level development banks, non banking financial companies (NBFC) and other market intermediaries such has the stock brokers and money lenders are among the oldest of the certain variants of NBFC and the oldest market participants. The asset quality of banks is one of the most important indicators of their financial health. The Indian banking sector has been facing severe problems of increasing Non- Performing Assets (NPAs). The NPAs growth directly and indirectly affects the quality of assets and profitability of banks. It also shows the efficiency of banks credit risk management and the recovery effectiveness. NPA do not generate any income, whereas, the bank is required to make provisions for such as assets that why is a double edge weapon. This paper outlines the concept of quality of bank loans of different types like Housing, Agriculture and MSME loans in state Haryana of selected public and private sector banks. This study is highlighting problems associated with the role of commercial bank in financing Small and Medium Scale Enterprises (SME). The overall objective of the research was to assess the effect of the financing provisions existing for the setting up and operations of MSMEs in the country and to generate recommendations for more robust financing mechanisms for successful operation of the MSMEs, in turn understanding the impact of MSME loans on financial institutions due to NPA. There are many research conducted on the topic of Non- Performing Assets (NPA) Management, concerning particular bank, comparative study of public and private banks etc. In this paper the researcher is considering the aggregate data of selected public sector and private sector banks and attempts to compare the NPA of Housing, Agriculture and MSME loans in state Haryana of public and private sector banks. The tools used in the study are average and Anova test and variance. The findings reveal that NPA is common problem for both public and private sector banks and is associated with all types of loans either that is housing loans, agriculture loans and loans to SMES. NPAs of both public and private sector banks show the increasing trend. In 2010-11 GNPA of public and private sector were at same level it was 2% but after 2010-11 it increased in many fold and at present there is GNPA in some more than 15%. It shows the dark area of Indian banking sector.
EXPERIMENTAL STUDY OF MECHANICAL AND TRIBOLOGICAL RELATION OF NYLON/BaSO4 POL...IAEME Publication
An experiment conducted in this study found that BaSO4 changed Nylon 6's mechanical properties. By changing the weight ratios, BaSO4 was used to make Nylon 6. This Researcher looked into how hard Nylon-6/BaSO4 composites are and how well they wear. Experiments were done based on Taguchi design L9. Nylon-6/BaSO4 composites can be tested for their hardness number using a Rockwell hardness testing apparatus. On Nylon/BaSO4, the wear behavior was measured by a wear monitor, pinon-disc friction by varying reinforcement, sliding speed, and sliding distance, and the microstructure of the crack surfaces was observed by SEM. This study provides significant contributions to ultimate strength by increasing BaSO4 content up to 16% in the composites, and sliding speed contributes 72.45% to the wear rate
ROLE OF SOCIAL ENTREPRENEURSHIP IN RURAL DEVELOPMENT OF INDIA - PROBLEMS AND ...IAEME Publication
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Harnessing WebAssembly for Real-time Stateless Streaming PipelinesChristina Lin
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administration, leaving systems to default configuration [8]. As the internet developing into the
society, new packages like viruses and worms are imported. The malignant so, the users use
different procedures like cracking of password, identifying unencrypted text are used to cause
vulnerabilities to the system. Hence, security is required for the users to secure their system
from the intruders. Firewall technique is one of the widespread protection techniques and it is
used to protect the private network from the public network. IDS are used in network related
activities, medical applications, credit card frauds, Insurance agency [8].
The remaining portion of the paper is structured as follows. Section 2 tells about the history
and the basic concepts of IDS. Section 3 explains the IDS functionality. Section 4 gives the
brief description about the life cycle of IDS. Techniques are described in Section 5. Section 6
describes about IDS tools. Section 7 discusses the needs and challenges. Conclusion is given in
Section 8.
2. HISTORY
The aim of intrusion detection is to monitor the network resources to detect anomalous behavior
and misuse in network [16]. Intrusion detection theory was introduced in early 1980’s after the
evolution of internet with surveillance end monitoring the threat [17]. There was a abrupt rise
in reputation and incorporation in security frame. Since then, several events in IDS technology
have advanced intrusion detection to its current state [16]. James Anderson's wrote a paper for
a government organization and introduced an approach that audit trails contained vital
information that could be valuable in tracking misuse and understanding of user performance
[16].
Then the detection appeared and audit data and its significance led to enormous
improvements in the subsystems of every single operating system [16]. IDS and Host Based
Intrusion Detection System (HIDS) were first defined. In 1983, SRI International and Dorothy
Denning began working on a government project that launched a new effort into intrusion
detection system development [17]. Around 1990s the revenues are generated and intrusion
detection market has been elevated. Real secure is an intrusion detection network developed by
ISS. After a year, Cisco recognized the priority for network intrusion detection and acquired
the Wheel Group for achieving the security solutions [17]. The government actions like Federal
Intrusion Detection Networks (FID Net) were designed under Presidential Decision Directive
63 is also adding impulse to the IDS [17].
3. INTRUSION DETECTION SYSTEM
An IDS is referred as burglar alarm. For example the lock system in the house safeguards the
house from theft. But if somebody breaks the lock system and tries to enter into the house, it is
the burglar alarm that detects that the lock has been broken and warns the owner by raising an
alarm. Moreover, Firewalls do a very good job of filtering the incoming traffic from the Internet
to circumvent the firewall [8]. For example, external users can connect to the Intranet by dialing
through a modem installed in the private network of the organization; this kind of access cannot
be identified by the firewall [8].
An Intrusion Prevention System (IPS) is a network security/threat prevention technology
that audits network traffic streams to detect and prevent vulnerability activities. There are two
types of prevention system they are Network (NIPS) and Host (HIPS). These systems watch
the network traffic and automatically take actions to protect networks and systems. IPS issue is
false positives and negatives. False positive is defined to be an event which produces an alarm
in IDS where there is no attack. False negative is defined to be an event which does not produces
an alarm when there is an attacks takes place. Inline operation can create blockages such as
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single point of failure, signature updates and encrypted traffic. The actions arising in a system
or network is measured by IDS [8].
3.1. Types of IDS
Figure 1 shows the different types of Intrusion detection systems.
• Host based IDS
• Network based IDS
• Application based IDS
Figure 1 Intrusion Detection System – Types
Host based IDS views the sign of intrusion in the local system. For study they use host
system’s logging and other information. Host based handler is specified as sensor. Other
sources, from which a host-based sensor can acquire data, include system logs and other logs
generated by operating system processes and contents of objects not reflected in standard
operating system audit and logging mechanisms [9]. Host based system trust strongly on audit
trail. The information permits the intrusion detection system to spot subtle patterns of misuse
that would not be noticeable at a higher level of abstraction [10]. The elementary principle in
IDS including Network Based Intrusion Detection System (NIDS) initiated from anomaly
HIDS research based on Denning’s pioneering work [11]. A host-based IDS provides much
more appropriate information than Network-based IDS. HIDS are used efficiently for
examining the network attacks, for example, it can occasionally tell exactly what the attacker
did, which commands he used, what files he accessed, rather than just an indefinite accusation
and there is an attempt to execute a dangerous command [12]. It is less risky to configure.
3.1.1. Advantages of Host based Intrusion Detection Systems
• Verifies success or failure of an attack
• Monitors System Activities
• Detects attacks that a network based IDS fail to detect
• Near real time detection and response
• Does not require additional hardware
• Lower entry cost
Network based IDS systems gather information from the network itself relatively from each
separate host [13]. The NIDS audits the network attacks while packets moving across the
network. The network sensors come prepared with attack signatures that are instructions on
what will constitute an attack and most network-based systems allow advanced users to define
their own signatures [13]. Attack on the sensor is based on signature and they are from the
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previous attacks and the operation of the monitors will be translucent to the users and this is
also significant [14].
The transparency of the monitors decreases the likelihood that an opponent will be able to
locate it and invalidate its capabilities without the determinations [10]. Network Node IDS
(NNIDS) agents are installed on every host within the network being protected [2].
3.1.2. Advantages of Network based Intrusion Detection Systems
• Lower Cost of Ownership
• Easier to deploy
• Detect network-based attacks
• Retaining evidence
• Real Time detection and quick response. Detection of failed attacks
Application based IDS (APIDS) will check the active behavior and event of the protocol
[2]. The system or agent is placed between a process and group of servers that monitors and
analyzes the application protocol between devices [2]. Intentional attacks are the malicious
attacks carried out by disgruntled employees to cause harm to the system and Unintentional
attacks causes financial damage to the system by deleting the important data file [2]. There are
many attacks have taken place in OSI layer
Figure 2 Intrusion Detection Attacks
3.2. Denial-of-Service (DOS) Attacks
It tries to deny the legal users from promoting the requested service. An advanced Distributed
Denial of Service occurs in a distributed environment that the attacker sends or floods the server
with many connections that request to knock the target system [2].Types of DOS attacks are
3.2.1. SYN Attack
SYN attack is also defined as Synchronization attack. Here, the attacker sends the flood of SYN
request to the destination to use the resources of the server and to make the system unresponsive.
3.2.2. Ping of Death
In this the intruder sends a ping request to the targeted system which is larger than 65,536 bytes
which causes the system to crash [2]. The formal size must be 56 bytes or 84 bytes in case of
considering Internet protocol header.
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3.3. Eavesdropping Attacks
It is the scheme of interference in communication by the attacker. This attack can be done over
by telephone lines or through email. [2].
3.4. Spoofing Attacks
This attacker interprets as another user to forge the data and take advantages on illegal events
in the network. IP spoofing is a common example where the system communicates with a
trusted user and provides access to the attacker [2].
3.5. Intrusion attacks or User to Root Attack (U2R)
An intruder tries to access the system or route through the network. Buffer overflow attack is a
typical intrusion attack which occurs when a web service receives more data than it has been
programmed to handle which leads to loss of data [2].
3.6. Logon Abuse Attacks
A logon abuse attack would neglect the authentication and access control mechanisms and grant
a user with more advantages [2].
3.7. Application-Level Attacks
The attacker targets the disabilities of application layer. For example, security weakness in the
web server or in faulty controls on the server side [2].
4. FUNCTIONS OF IDS
The IDS consist of four key functions namely, data collection, feature selection, analysis and
action, which is given in Figure 3.
Figure 3 Functionality of IDS
4.1. Data collection
This module passes the data as input to the IDS. The data is recorded into a file and then it is
examined. Network based IDS collects and modifies the data packets and in host based IDS
collects details like usage of the disk and processes of the system.
4.2. Feature Selection
To select the specific feature large data is available in the network and they are frequently
evaluated for intrusion. For example, the Internet Protocol (IP) address of the source and target
system, protocol type, header length and size could be taken as a key for intrusion [15].
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4.3. Analysis
The data is analyzed to find the accuracy. Rule based IDS examine the data where the incoming
traffic is tested against predefined signature or pattern [15]. Another technique is anomaly based
IDS where the system performance is studied and mathematical models are employed to it [15].
4.4. Action
It defines about the attack and reaction of the system. It can either inform the system
administrator with all the obligatory data through email/alarm icons or it can play a dynamic
part in the system by dropping packets so that it does not enter the system or close the ports
[15].
5. IDS LIFE CYCLE
Vendors frequently release new IDS products aggressively and compete for market shares [19].
Estimating the new systems is not a relevant task and product calculation information is
imperfect. Hiring and retaining the workers to administer security and intrusion detection are
the challenging tasks [19]. Faster changes in IT make it challenging for the firm to implement
long term security strategy.
Figure 4 Functionality of IDS
5.1. Evaluation and Selection
If an organization plans to get IDS it should study the resources available for the systems
operation and maintenance [19]. Lifecycle of a product for economic IDS is enhanced. The
third-party evaluation is available and their reports are commonly on the surface [19]. This
process illustrates about the finding of the intruder and the amount of work is necessary for
maintaining the system in the network with traffic and the selection process defines about the
identification of character, approaches, accuracy, usability, and effectiveness.
5.2. Deployment
Deployment phase includes the working of sensors to maximize protection for the serious assets
by configuring the IDS to reflect security policy and installing signatures [19]. Users must
develop rules for handling the alerts and to associate alerts with other systems. The Intrusion
Detection Working Group of the Internet Engineering Task Force (IETF) is developing
common alert format that uses the IDS to alert from different systems and they are reported to
a common display console [19].
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5.3. Operation and use
Organization administers the IDS to monitor the host and to respond the report as an alert. It
establishes the roles and responsibilities for examining and monitoring the results of both
manual and automatic responses [19]. Smart intruders who realize that IDS has been deployed
on a network attack that they force it to provide false report [19].
5.4. Maintenance
Maintenance includes installation of signatures and IDS upgrades. Sensor placement should be
revisited periodically to ensure that system or network changes [19]. An organization must
attract, train and retain qualified technical staff to operate and maintain IDS technologies [19].
6. IDS TECHNIQUES
6.1. ANOMALY BASED INTRUSION DETECTION
Anomaly is indicated as an outlier, peculiarities or exceptions are the data pattern which
performs abnormally. Anomaly detection technique is intended to uncover the patterns that are
far from the normal and others are flagged as an intrusion [2]. Anomaly detections are classified
into static and dynamic detectors.
Static anomaly detector is assumed as a portion of monitored system which remains
constant. The static portion is possessed into two parts, i.e. system code and system data. Static
portions of the system can be represented as a binary bit. If any divergence from its original
form is occurred then the error has been indicated or the burglar has reshaped the portion of the
system.
In dynamic detector the definition of the system behavior is included. The system behavior
is defined as an order of different event. For example, audit records produced by the operating
system are used by IDS to define the events of interest [2]. In this case, the behavior can be
observed only when audit records are created by OS and the events are occurred in strict
sequences [2]. If uncertain behavior is considered as anomalous, then the system administrators
may be alerted by false alarms [3].
Anomaly detection is useful for finding attacks like misuse of protocol and service ports,
DoS based on crafted payloads, DoS based on volume (DDoS), buffer overflow and other
application payload anomaly.
6.2. Techniques used in anomaly detection
There are number of event and event counter are refined and have been implemented in anomaly
detection.
6.2.1. Statistical Models
The statistical model shows the output as a statistical value. There are two types of statistical
models, they are
6.2.1.1. Operational Model (or) Threshold Metric
The actions that occur over a period of time regulate the alarm. This can be visualized in Win2k
lock; a user after n unsuccessful login attempts regulates the alarm. Here lower limit is 0 and
upper limit is n [15].
6.2.1.2. Markov Process or Marker Model
In this model the system is inspected at fixed time intermission. The behavior is detected as
anomaly if the probability of the state is low [15].
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6.2.2. Cognition Models
6.2.2.1. Finite State Machine
A finite state machine (FSM) or finite automation is a model of behavior captured in states,
transitions and actions [15]. A state defines about the past information. An action is a
description of an activity that is to be performed at a given moment and the types of action are
entry action, exit action and transition action [15].
6.2.2.2. Description Scripts
Scripting languages characterize the attacks on computers and networks. All scripting
languages are capable of examining the sequences of specific events [15].
6.2.3. Cognition Based Detection Techniques
Cognition-Based (also called knowledge-based or expert systems) Detection Techniques work
on the audit data [15]. The set of predefined rules for the classes and attributes are identified
from training dataset [15].
6.2.3.1. Boosted Decision Tree or Boosted Tree (BT)
It uses ADA Boost (adaptive boosting) algorithm to generate many Decision Trees classifiers
trained by different sample which is implemented in IDS [15].
6.2.3.2. Support Vector Machine (SVM)
SVM is defined to be the classifiers which are designed for the binary classification. Decision
tree based SVM is a technique which merges the two techniques to solve the problem in an
efficient way. The training and testing time can be decreased by using this method.
6.3. SIGNATURE BASED INTRUSION DETECTION
Signature based intrusion detection is termed as misuse detection. Here, the dataset has number
of instances and every data must be labeled as normal or intrusive. The machine learning
algorithms are used to train the data set according to their label. This technique automatically
retains the signature to detect the intruder. Misuse detection technique is created automatically
and the works are more complicated and precise than manually done [4]. Depending on the
robustness and seriousness of a signature that is activated within the system, some alarm
response or notification should be sent to the right authorities [4].
6.4. Techniques used in misuse detection
6.4.1. Expression matching
Expression matching is the easiest and simplest form in misuse detection. In this it searches for
the stream of events like log entries for the happening of exact pattern.
6.4.2. State transition analysis
This model attacks the state or the transitions in the network. Every event in the network is
applied to finite state machine instances which finally results in transition. An attack will be
occurred when the machine reaches its final state.
6.5. TARGET MONITORING
Target monitoring is a technique which is used to report if any changes or modifications made
in the system. This is usually done through cryptographic algorithm which computes a crypto
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checksum for each targeted file [5].If any changes are made in crypto checksum they are
reported by IDS. Tripwire checksum is an integrity checker which checks for the changes or
modification in the files.
6.6. STEALTH PROBES
A stealth probe is a technique used to collect and associates the data. It tries to find the attacks
which has taken long period of time. Attackers will check for the system errors over a period
of month, and wait for another two months to launch the attacks and they take a wide-area
sampling and attempt to discover any correlating attacks [2].
7. TOOLS IN INTRUSION DETECTION
An intrusion detection product available today addresses a range of organizational security
goals [2].This section discusses about the security tools.
7.1. SNORT
Snort is lightweight and open source software. Snort uses a flexible rule-based language to
define the traffic [6].From an IP address; it records the packet in human readable form. Through
protocol analysis, content searching, and different pre-processors Snort detects thousands of
worms, vulnerability exploit attempts, port scans, and other suspicious behavior [6].
7.2. OSSEC-HIDS
OSSEC (open source security) is free open source software. It will run on major operating
system and uses a Client/Server based architecture. OSSEC has the ability to send OS logs to
the server for analysis and storage. It is used in powerful log analysis engine, ISPs, universities
and data centers. Authentication logs, firewalls are monitored and analyzed by HIDS.
7.3. FRAGROUTE
It is termed as fragmenting router. Here, from the attacker to the frag router the IP packet is sent
and they are then fragmented and transformed to the party.
7.4. HONEYD
Honeyd is a tool that creates virtual hosts on the network [6]. The services are used by the host
Honeyd allows a single host to request multiple addresses on a LAN for networks simulation.
It is possible to knock the virtual machines or to trace route them [6]. Any type of service on
the virtual machine can be simulated according to a simple configuration file [6].
7.5. KISMET
It is a guideline for WIDS (Wireless intrusion detection system).WIDS compromises with
packet payload and happenings of WIDS. It will find the burglar access point.
8. NEEDS AND CHALLENGES
For employing an IPS device there are many challenges. The IPS device is designed to work
inline presenting a potential choke point and single point of failure [18]. Some pursued attacks
are undetected if the passive IDS fails and the network performances are impacted when the
inline device fails. [18]. One of the components of network, the NIPS (Network intrusion
prevention system) device must perform like a network switch. It must meet the network
performance and consistency requirements to organize the challenges. Hence, very few
customers are willing to sacrifice the network performance and consistency for security
purposes [18].
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A NIPS slows down the traffic and the issue of NIPS is dropped packets, they are used to
complete data stream. Most high-end IPS vendors will get this problem by using custom
hardware with advanced FPGAs and ASICs [18]. It is necessary to design the product to operate
as an intrusion detection and prevention device [18]. Every organization needs IDS which is
like a defense tool. There are some challenges the organizations face while deploying an
intrusion detection system [8].
IDS technology itself is undergoing a lot of improvements. From the IDS operation it is
understood that it is important for an organization. IDS technology does not need human
interventions. Today an IDS technology offers some automation like notifying the administrator
in case of detection of a malicious activity, shunning the malicious connection for a
configurable period of time, dynamically changing a router's access control list in order to stop
a malicious connection [8]. For every event occurrence the IDS logs should be monitored.
Monitoring the logs on a daily basis is required to analyze the activities which are detected by
the IDS over a period of time [8].
IDS operation depends on the deployment success. Planning plays a vital role for the design
and operation phase. In most cases, it is desirable to implement a hybrid solution of network
based and host based IDS [8]. The decision can differ between organizations. A network based
IDS is an immediate choice for many organizations because of its ability to monitor multiple
systems and also the fact that it does not require a software to be loaded on a production system
unlike host based IDS [8].
Some of the organizations provide hybrid solution. So, the available resources are needed for
a system before installing a host based sensor [8].
The ratio of sensor manager should be acclaimed. It is very important to design the standard
policy before starting the IDS operation and avoid false positives result. IDS sensor may send
a lot of false positives result to the sensor and the ratio can be insufficient [8].
The IDS technology is still reactive rather than proactive and this technology works on
attack signatures [8]. Signatures are defined as a pattern of attacks which is defined earlier. The
signature database needs to be updated whenever a different kind of attack is detected and they
are fixed in the database and the frequency of signature update differs from vendor to vendor
[8]. 5. Because of collision domains in switched network the traffic in and out port cannot be
seen from any other host port. But in HUB based network in and out can be viewed from any
of the port. NIDS sensor needs to detect traffic in and out of a port and for the malicious traffic
in the switched environment. For achieving this kind they use port mirroring or spanning [8].
9. IDS IN DIFFERENT DOMAINS
An IDS is used in many fields and the performance in each field is described and defines how
they performed.
9.1. IDS in MANET
Manet is defined as mobile adhoc network. It is a self-directed network that is composed
naturally by the combinations of mobile nodes without centralized administration. IDS is used
in Manet. Mobile network is normally needed in the battleground for military people to get
proper network [20]. Normally the messages are split into number of packet and they use a
hardware device like wire and modem to transmit. But, in Manet they are connected wirelessly.
Watchdog and path rater are the two techniques added on the protocol in Adhoc.
A watchdog detects the misbehaving nodes by eavesdropping on the transmission of the
next hop [20]. A path rater then assist to find the routes that do not contain misbehaving nodes
[20]. IDS are used in Manet while transferring the sequence of packets to the destination
through mobile network to find the intruder if any.
11. A Study on Intrusion Detection
http://www.iaeme.com/IJARET/index.asp 153 editor@iaeme.com
9.2. IDS FOR CLOUD COMPUTING
Cloud computing is explained as internet based computing cloud where, virtual shared servers
provide software infrastructure platform devices and other resources and hosting to customer
as a service on pay-as you-use basis [21]. The user of the cloud does not hold any physical
framework instead they lease from the mediator (third party). They pay only for the usage of
the resource. Intrusion detection system plays an vital role in the security and perseverance of
active defense system against intruder hostile attacks for any business and IT organization [24].
In cloud computing the applications are received on the remote server of the provider and they
have the control headed for the usage of the data. IDMEF (Intrusion detection message
exchange format) is the standard used in cloud for the communication purpose [21].
9.3. Cloud computing security issues
• Cloud data confidentiality
• Attacks on remote server
• Cloud security auditing
• Lack of data interoperability
9.4. IDS IN DATA MINING
Data mining is the process of extracting the concealed knowledge from the databases. IDS are
very important in data mining. Intrusion detection includes identifying a set of malicious actions
that compromise the integrity and availability of information resources [22].
Intrusion detection in data mining has two divisions, they are, misuse detection and anomaly
detection. In misuse detection the labeled data are built using anticipating model [23]. In
anomaly detection there is a deviation between models. To use the data first it should be
converted into featured data and the data mining models are applied to it and they are
summarized to produce the result.
9.5. TECHNICAL CHALLENGES
• Large data size
• Higher dimensionality
• Data preprocessing
10. CONCLUSION
The main objective of this paper is to provide an overview of the requirement and utility of
intrusion detection system. This paper gives complete study about various types of IDS, life
cycle, different domains, types of attacks and tools. IDS are becoming essential for day today
security in corporate world and for network users. IPS defines about the preventing measures
for the security. In the lifecycle the phases developed and the stages are illustrated. Still, there
are more challenges to overcome. The techniques of anomaly detection and misuse detection
are precisely illustrated and more techniques can be used. Further Work will be done on
comparative analysis of some popular data mining algorithms applied to IDS and enhancing a
classification based IDS using selective responses.
REFERENCES
[1] Corinne Lawrence- “IPS – The Future of Intrusion Detection”- University of Auckland -
26th October 2004.
[2] Karthikeyan .K.R and A. Indra- “Intrusion Detection Tools and Techniques a Survey”