The prosperity of technology worldwide has made the concerns of security tend to increase rapidly... more The prosperity of technology worldwide has made the concerns of security tend to increase rapidly. The enormous usage of internetworking has raised the need of protecting system(s) as well as network(s) from the unauthorized access (intrusion). To tackle the intrusive activities, several countermeasures have been found in literature viz. firewall, antivirus and currently widely preferred Intrusion detection System (IDS). IDS, is a detection mechanism for detecting the intrusive activities hidden among the normal activities. The revolutionary establishment of IDS has attracted analysts to work dedicatedly enabling the system to deal with technological advancements. Hence in this regard, various beneficial schemes and models have been proposed in order to achieve enhanced IDS. This paper proposes a novel hybrid model for intrusion detection. The proposed framework in this paper may be expected as another step towards advancement of IDS. The framework utilizes the crucial data mining classification algorithms beneficial for intrusion detection. The Hybrid framework would henceforth, will lead to effective, adaptive and intelligent intrusion detection.
The increasing counterfeit of the internet usage has raised concerns of the security agencies to ... more The increasing counterfeit of the internet usage has raised concerns of the security agencies to work very hard in order to diminish the presence of the abnormal users from the web. The motive of these illicit users (called intruders) is to harm the system or the network either by gaining access to the system or prohibiting genuine users to access the resources. Hence in order to tackle the abnormalities Intrusion Detection System (IDS) with Data Mining has evolved as the most demanding approach. On the one end IDS aims to detect the intrusions by monitoring a given environment while on the other end Data Mining allows mining of these intrusions hidden among genuine users. In this regard, IDS with Data Mining has been through several revisions in consideration to meet the current requirements with efficient detection of intrusions. Also several models have been proposed for enhancing the system performance. In context to improved performance, the paper presents a new model for intrusion detection. This improved model, named as REP (Reduced Error Pruning) based Intrusion Detection Model results in higher accuracy along with the increased number of correctly classified instances.
The versatility to internet services has lead to an advanced world scenario. With the incremental... more The versatility to internet services has lead to an advanced world scenario. With the incremental usage of internet for human convenience, the advancement has brought up the security concerns. In this regard, various remedies such as firewall and antivirus are introduced to prohibit the illegitimate activities from being performed. But still the need aroused for an improved system that can capably handle the unauthorized access. Thus Intrusion Detection System (IDS) noticed its existence. The aim of IDS is to monitor the network traffic in search of intrusions. In order to meet the requirement of increasing data on web, IDS with Data Mining came into limelight aiding in effective detection outcomes. The appreciable results in IDS with Data Mining were noticed by applying Bayesian Network, K2 algorithm. Hence the paper is the study about the feasibility of K2-based IDS in detecting intrusions.
S ecurity of the computer system and network is at continual risk due the progressive technologic... more S ecurity of the computer system and network is at continual risk due the progressive technological advancements in the field of information security. This concern has brought up the necessity of a system or mechanism which constantly keeps an eye on the illegitimate activities. S everal mechanisms have been proposed for this purpose, namely antivirus, firewall, intrusion detection system etc. In these remedies, Intrusion Detection S ystem is most effective technique which is able to detect both inner and outer attacks. To cope up with the ongoing improvements in the domain there is always a need for revision of the system. This paper presents a comparative study of two influential algorithms of data mining for intrusion detection. The two algorithms TAN and REP form the inventive models framing Intrusion Detection S ystems.
Along with the modernization and widespread usage of Internet, the security of the mankind has be... more Along with the modernization and widespread usage of Internet, the security of the mankind has become one of the major issues today. The threat of human society from the terrorists is the challenge faced dominantly. Advancement in the technology has not only helped the common people for the growth but also these inhuman people to adversely affect the society with sophisticated techniques. In this regard, the law-enforcement agencies are aiming to prevent future attacks. To do so, the terrorist networks are being analyzed and detected. To achieve this, the law enforcement agencies are using data mining techniques as one of the effective solution. One such technique of data mining is Social network analysis which studies terrorist networks for the identification of relationships and associations that may exist between terrorist nodes. Terrorist activities can also be detected by means of analyzing Web traffic content. This paper studies social network analysis, web traffic content and explores various ways for identifying terrorist activities.
In today’s era of hi-tech technologies, criminals are easily fulfilling their inhuman goals again... more In today’s era of hi-tech technologies, criminals are easily fulfilling their inhuman goals against
the mankind. Thus, the security of civilians has significantly become important. In this regard,
the law-enforcement agencies are aiming to prevent future attacks. To do so, the terrorist
networks are being analyzed using data mining techniques. One such technique is Social
network analysis which studies terrorist networks for the identification of relationships and
associations that may exist between terrorist nodes. Terrorist activities can also be detected by
means of analyzing Web traffic content. This paper studies social network analysis, web traffic
content and explores various ways for identifying terrorist activities.
The prosperity of technology worldwide has made the concerns of security tend to increase rapidly... more The prosperity of technology worldwide has made the concerns of security tend to increase rapidly. The enormous usage of internetworking has raised the need of protecting system(s) as well as network(s) from the unauthorized access (intrusion). To tackle the intrusive activities, several countermeasures have been found in literature viz. firewall, antivirus and currently widely preferred Intrusion detection System (IDS). IDS, is a detection mechanism for detecting the intrusive activities hidden among the normal activities. The revolutionary establishment of IDS has attracted analysts to work dedicatedly enabling the system to deal with technological advancements. Hence in this regard, various beneficial schemes and models have been proposed in order to achieve enhanced IDS. This paper proposes a novel hybrid model for intrusion detection. The proposed framework in this paper may be expected as another step towards advancement of IDS. The framework utilizes the crucial data mining classification algorithms beneficial for intrusion detection. The Hybrid framework would henceforth, will lead to effective, adaptive and intelligent intrusion detection.
The increasing counterfeit of the internet usage has raised concerns of the security agencies to ... more The increasing counterfeit of the internet usage has raised concerns of the security agencies to work very hard in order to diminish the presence of the abnormal users from the web. The motive of these illicit users (called intruders) is to harm the system or the network either by gaining access to the system or prohibiting genuine users to access the resources. Hence in order to tackle the abnormalities Intrusion Detection System (IDS) with Data Mining has evolved as the most demanding approach. On the one end IDS aims to detect the intrusions by monitoring a given environment while on the other end Data Mining allows mining of these intrusions hidden among genuine users. In this regard, IDS with Data Mining has been through several revisions in consideration to meet the current requirements with efficient detection of intrusions. Also several models have been proposed for enhancing the system performance. In context to improved performance, the paper presents a new model for intrusion detection. This improved model, named as REP (Reduced Error Pruning) based Intrusion Detection Model results in higher accuracy along with the increased number of correctly classified instances.
The versatility to internet services has lead to an advanced world scenario. With the incremental... more The versatility to internet services has lead to an advanced world scenario. With the incremental usage of internet for human convenience, the advancement has brought up the security concerns. In this regard, various remedies such as firewall and antivirus are introduced to prohibit the illegitimate activities from being performed. But still the need aroused for an improved system that can capably handle the unauthorized access. Thus Intrusion Detection System (IDS) noticed its existence. The aim of IDS is to monitor the network traffic in search of intrusions. In order to meet the requirement of increasing data on web, IDS with Data Mining came into limelight aiding in effective detection outcomes. The appreciable results in IDS with Data Mining were noticed by applying Bayesian Network, K2 algorithm. Hence the paper is the study about the feasibility of K2-based IDS in detecting intrusions.
S ecurity of the computer system and network is at continual risk due the progressive technologic... more S ecurity of the computer system and network is at continual risk due the progressive technological advancements in the field of information security. This concern has brought up the necessity of a system or mechanism which constantly keeps an eye on the illegitimate activities. S everal mechanisms have been proposed for this purpose, namely antivirus, firewall, intrusion detection system etc. In these remedies, Intrusion Detection S ystem is most effective technique which is able to detect both inner and outer attacks. To cope up with the ongoing improvements in the domain there is always a need for revision of the system. This paper presents a comparative study of two influential algorithms of data mining for intrusion detection. The two algorithms TAN and REP form the inventive models framing Intrusion Detection S ystems.
Along with the modernization and widespread usage of Internet, the security of the mankind has be... more Along with the modernization and widespread usage of Internet, the security of the mankind has become one of the major issues today. The threat of human society from the terrorists is the challenge faced dominantly. Advancement in the technology has not only helped the common people for the growth but also these inhuman people to adversely affect the society with sophisticated techniques. In this regard, the law-enforcement agencies are aiming to prevent future attacks. To do so, the terrorist networks are being analyzed and detected. To achieve this, the law enforcement agencies are using data mining techniques as one of the effective solution. One such technique of data mining is Social network analysis which studies terrorist networks for the identification of relationships and associations that may exist between terrorist nodes. Terrorist activities can also be detected by means of analyzing Web traffic content. This paper studies social network analysis, web traffic content and explores various ways for identifying terrorist activities.
In today’s era of hi-tech technologies, criminals are easily fulfilling their inhuman goals again... more In today’s era of hi-tech technologies, criminals are easily fulfilling their inhuman goals against
the mankind. Thus, the security of civilians has significantly become important. In this regard,
the law-enforcement agencies are aiming to prevent future attacks. To do so, the terrorist
networks are being analyzed using data mining techniques. One such technique is Social
network analysis which studies terrorist networks for the identification of relationships and
associations that may exist between terrorist nodes. Terrorist activities can also be detected by
means of analyzing Web traffic content. This paper studies social network analysis, web traffic
content and explores various ways for identifying terrorist activities.
Uploads
Papers by Mradul Dhakar
the mankind. Thus, the security of civilians has significantly become important. In this regard,
the law-enforcement agencies are aiming to prevent future attacks. To do so, the terrorist
networks are being analyzed using data mining techniques. One such technique is Social
network analysis which studies terrorist networks for the identification of relationships and
associations that may exist between terrorist nodes. Terrorist activities can also be detected by
means of analyzing Web traffic content. This paper studies social network analysis, web traffic
content and explores various ways for identifying terrorist activities.
the mankind. Thus, the security of civilians has significantly become important. In this regard,
the law-enforcement agencies are aiming to prevent future attacks. To do so, the terrorist
networks are being analyzed using data mining techniques. One such technique is Social
network analysis which studies terrorist networks for the identification of relationships and
associations that may exist between terrorist nodes. Terrorist activities can also be detected by
means of analyzing Web traffic content. This paper studies social network analysis, web traffic
content and explores various ways for identifying terrorist activities.