Zakiya Malek - Academia.edu (original) (raw)

Papers by Zakiya Malek

2020 Fourth World Conference on Smart Trends in Systems, Security and Sustainability (WorldS4), 2020

Computer Networks fights with a continues issues with attackers and intruders. Attacks on distrib... more Computer Networks fights with a continues issues with attackers and intruders. Attacks on distributed systems becoming more powerful and more frequent day by day. Intrusion detection methods are performing main role to detect intruders and attackers. To identify intrusion on computer or computer networks an intrusion detection system methods are used. Network Intrusion Detection System (NIDS) performs an prime role by presenting the network security. It gives a defense layer by monitoring the traffic on network for predefined distrustful activity or pattern. In this paper we have analyze and compare existing signature based and anomaly based algorithm with Openstack private cloud.

2017 IEEE International Conference on Power, Control, Signals and Instrumentation Engineering (ICPCSI)

Today all users depend on the computer in their daily life, for simple tasks such as checking Our... more Today all users depend on the computer in their daily life, for simple tasks such as checking Our studies in this paper describe an approach for identifying an intruder by his/her behavior on GUI based system. Our system introduces logger to collect user log and BIDS detector. BIDS detector is program who create an initial user profile as well as update it if needed. BIDS program also use a t-test for identifying the user behavior deviation. Our system can be efficiently used while intruder pretending to be authorized the user and gives high detection rates with less false positives.

In the era of information systems and internet there is more concern rising towards information s... more In the era of information systems and internet there is more concern rising towards information security in daya to day life, along with the availability of the vulnerability assessment mechanisms to identifying the electronic attacks.Anomaly detection is the process of attempting to identify instances of attacks by comparing current activity against the expected actions of intruder. Machine learning based intrusion detection has the ability to change its execution plan as it obtains new information. The goal of this paper is to provide a comprehensive review of some machine learning based techniques have been applied to AIDS with identifying their main pros and cons. Keywords-anomaly detection; machine learning; intrusion detection I. INTRODUCATION Intrusions and misuse of computer systems are becoming a major concern of our time [3], [2] Traditionally intrusion detection systems (IDS) are classified based on the style of detection they are using: systems relying on misuse detectio...

This paper is a survey of the work, done for making an IDS fault tolerant.Architecture of IDS tha... more This paper is a survey of the work, done for making an IDS fault tolerant.Architecture of IDS that uses mobile Agent provides higher scalability. Mobile Agent uses Platform for detecting Intrusions using filter Agent, co-relater agent, Interpreter agent and rule database. When server (IDS Monitor) goes down, other hosts based on priority takes Ownership. This architecture uses decentralized collection and analysis for identifying Intrusion. Rule sets are fed based on user-behaviour or applicationbehaviour.This paper suggests that intrusion detection system (IDS) must be fault tolerant; otherwise, the intruder may first subvert the IDS then attack the target system at will.

This paper presents an architecture of a distributed intrusion detection system (DIDS) using Mobi... more This paper presents an architecture of a distributed intrusion detection system (DIDS) using Mobile Agent (MA).MA can invoke different agent( viz. Correlator agent, Filter Agent ).MA runs on top of Mobile Agent Platform. To manage uniformity on heterogeneous network, MAP works as virtual Machine. Correlator agent (CA) works as a means for the communication among the hosts and server in the network. MA invokes CA for sending rules that co-ordinate and responsible for determining whether some suspicious activities in different network nodes can be combined to be a distributed intrusion. Our implementation result justifies the architecture of the DIDS.

In this paper we propose rule based intrusion detection for user behavior. The model periodically... more In this paper we propose rule based intrusion detection for user behavior. The model periodically collect the log and BIDS detector to detect normal or abnormal activity.If activity is normal then message is generated and if the activity is abnormal then the rule engine checks rules for intrusion. The malicious activity also stored in database for future IDS. The rules are stored in the rule engine of the system.

Lecture Notes in Computer Science, 2012

ABSTRACT This paper presents an architecture of a distributed intrusion detection system (DIDS) u... more ABSTRACT This paper presents an architecture of a distributed intrusion detection system (DIDS) using Mobile Agent (MA).MA can invoke different agent( viz. Correlator agent, Filter Agent ).MA runs on top of Mobile Agent Platform. To manage uniformity on heterogeneous network, MAP works as virtual Machine. Correlator agent (CA) works as a means for the communication among the hosts and server in the network. MA invokes CA for sending rules that co-ordinate and responsible for determining whether some suspicious activities in different network nodes can be combined to be a distributed intrusion. Our implementation result justifies the architecture of the DIDS.

International Journal

This paper is a survey of the work, done for making an IDS fault tolerant. Architecture of IDS th... more This paper is a survey of the work, done for making an IDS fault tolerant. Architecture of IDS that uses mobile Agent provides higher scalability. Mobile Agent uses Platform for detecting Intrusions using filter Agent, co-relater agent, Interpreter agent and ...

2020 Fourth World Conference on Smart Trends in Systems, Security and Sustainability (WorldS4), 2020

Computer Networks fights with a continues issues with attackers and intruders. Attacks on distrib... more Computer Networks fights with a continues issues with attackers and intruders. Attacks on distributed systems becoming more powerful and more frequent day by day. Intrusion detection methods are performing main role to detect intruders and attackers. To identify intrusion on computer or computer networks an intrusion detection system methods are used. Network Intrusion Detection System (NIDS) performs an prime role by presenting the network security. It gives a defense layer by monitoring the traffic on network for predefined distrustful activity or pattern. In this paper we have analyze and compare existing signature based and anomaly based algorithm with Openstack private cloud.

2017 IEEE International Conference on Power, Control, Signals and Instrumentation Engineering (ICPCSI)

Today all users depend on the computer in their daily life, for simple tasks such as checking Our... more Today all users depend on the computer in their daily life, for simple tasks such as checking Our studies in this paper describe an approach for identifying an intruder by his/her behavior on GUI based system. Our system introduces logger to collect user log and BIDS detector. BIDS detector is program who create an initial user profile as well as update it if needed. BIDS program also use a t-test for identifying the user behavior deviation. Our system can be efficiently used while intruder pretending to be authorized the user and gives high detection rates with less false positives.

In the era of information systems and internet there is more concern rising towards information s... more In the era of information systems and internet there is more concern rising towards information security in daya to day life, along with the availability of the vulnerability assessment mechanisms to identifying the electronic attacks.Anomaly detection is the process of attempting to identify instances of attacks by comparing current activity against the expected actions of intruder. Machine learning based intrusion detection has the ability to change its execution plan as it obtains new information. The goal of this paper is to provide a comprehensive review of some machine learning based techniques have been applied to AIDS with identifying their main pros and cons. Keywords-anomaly detection; machine learning; intrusion detection I. INTRODUCATION Intrusions and misuse of computer systems are becoming a major concern of our time [3], [2] Traditionally intrusion detection systems (IDS) are classified based on the style of detection they are using: systems relying on misuse detectio...

This paper is a survey of the work, done for making an IDS fault tolerant.Architecture of IDS tha... more This paper is a survey of the work, done for making an IDS fault tolerant.Architecture of IDS that uses mobile Agent provides higher scalability. Mobile Agent uses Platform for detecting Intrusions using filter Agent, co-relater agent, Interpreter agent and rule database. When server (IDS Monitor) goes down, other hosts based on priority takes Ownership. This architecture uses decentralized collection and analysis for identifying Intrusion. Rule sets are fed based on user-behaviour or applicationbehaviour.This paper suggests that intrusion detection system (IDS) must be fault tolerant; otherwise, the intruder may first subvert the IDS then attack the target system at will.

This paper presents an architecture of a distributed intrusion detection system (DIDS) using Mobi... more This paper presents an architecture of a distributed intrusion detection system (DIDS) using Mobile Agent (MA).MA can invoke different agent( viz. Correlator agent, Filter Agent ).MA runs on top of Mobile Agent Platform. To manage uniformity on heterogeneous network, MAP works as virtual Machine. Correlator agent (CA) works as a means for the communication among the hosts and server in the network. MA invokes CA for sending rules that co-ordinate and responsible for determining whether some suspicious activities in different network nodes can be combined to be a distributed intrusion. Our implementation result justifies the architecture of the DIDS.

In this paper we propose rule based intrusion detection for user behavior. The model periodically... more In this paper we propose rule based intrusion detection for user behavior. The model periodically collect the log and BIDS detector to detect normal or abnormal activity.If activity is normal then message is generated and if the activity is abnormal then the rule engine checks rules for intrusion. The malicious activity also stored in database for future IDS. The rules are stored in the rule engine of the system.

Lecture Notes in Computer Science, 2012

ABSTRACT This paper presents an architecture of a distributed intrusion detection system (DIDS) u... more ABSTRACT This paper presents an architecture of a distributed intrusion detection system (DIDS) using Mobile Agent (MA).MA can invoke different agent( viz. Correlator agent, Filter Agent ).MA runs on top of Mobile Agent Platform. To manage uniformity on heterogeneous network, MAP works as virtual Machine. Correlator agent (CA) works as a means for the communication among the hosts and server in the network. MA invokes CA for sending rules that co-ordinate and responsible for determining whether some suspicious activities in different network nodes can be combined to be a distributed intrusion. Our implementation result justifies the architecture of the DIDS.

International Journal

This paper is a survey of the work, done for making an IDS fault tolerant. Architecture of IDS th... more This paper is a survey of the work, done for making an IDS fault tolerant. Architecture of IDS that uses mobile Agent provides higher scalability. Mobile Agent uses Platform for detecting Intrusions using filter Agent, co-relater agent, Interpreter agent and ...