Layered Approach Using Conditional Random Fields For Intrusion Detection Under the Guidance of V.Rajashekhar M.Tech Assistant Professor Presenting By N.L.Prasanna(13FF1A0503) V.Anjali(14FF5A0501) V.Harish(13FF1A0508) Y.Saikrishna(13FF1A0509)

Abstract List Of Contents Introduction Literature survey Existing System & disadvantages Proposed System & advantages Modules S/w & H/w requirements

Abstract An intrusion detection system must reliably detect malicious activities in a network and as well as must perform efficiently with the large amount of network traffic. In my project, I address two issues of Accuracy and Efficiency using Conditional Random Fields and Layered Approach. I demonstrate that high attack detection accuracy can be achieved by using LCRF.

Intrusion detection system. Introduction Now a days it’s becoming a great challenge to administrators to find out real time counters by the Intruders. Intrusion detection system. Responsible for finding the malicious activities in a n/w Today, intrusion detection is one of the high priority and challenging tasks for network administrators and security professionals.

Literature survey Intrusion Detection It is becoming a great challenge to detect intruders. Anomaly Detection Intruders creating false data and use the system Network Traffic Today organizations we are having so many connections so controlling such kind of connections are very difficult(traffic)

Existing System Existing system uses techniques like Association Rules, Clustering, Naive Bayes classifier, artificial neural networks etc. Not integrated with the Layered Approach.

disadvantages Low efficient and accurate less analomous detection No blocking of intruder No layered approach(the intruder easily entered into our system)

Proposed System Using techniques CRF and LA. In the Layered Approach, an attack can be blocked at the layer where it is detected Integrating both(CRF and LA). Improving Efficiency and Accuracy.

advantages Low power consumption Easily detect intruder Number of security checks are performed one after the other in a sequence. Integrate the Layered Approach with the CRFs to gain the benefits of computational efficiency and high accuracy of detection in a single system If the Client Host is not registered with the Admin. It will be treated as System level Intruder

Modules Conditional Random Fields. Layered Approach. Integrating Layered Approach with Conditional Random Fields

Layered Approach For Intrusion Detection Layer-based Intrusion Detection System (LIDS) draws its motivation from Airport Security model, where a number of security checks are performed one after the other in a sequence. Fig2. Layered representation

Conditional Random Fields For Intrusion Detection Conditional models are used to model the conditional distribution over a set of random variables.

System Requirements Specification Software Requirements: Operating System : Windows XP Family. Programming Language : Java 1.6, Swings, RMI. Database : ms-access Hardware Requirements: Processor : Intel Pentium IV or above RAM : 512 MB Hard Disk : 80 GB Input device : Standard Keyboard and Mouse. Output device : High Resolution Monitor.

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