Comparative Study between Bayesian Network and Possibilistic Network in Intrusion Detection
نویسندگان
چکیده
Nowadays, completely protect a network from attacks is being a very hard task. Even heavily protected networks are sometimes penetrated, and an Intrusion Detection System (IDS) seems to be essential and is a key component in computer and network security. Several researchers worked on comparison between Bayesian Network (BN) and Possibilistic network (PN). But, in this paper we are interested by comparison between BN and PN network in Intrusion Detection. Comparison criteria covered detection rate and false alarms rate. Experimentation process used DARPA’99 experimentation data. Comparison results show a superiority of PN versus BN when detecting intrusion.
منابع مشابه
Hybrid Intrusion Detection and Prediction multiAgent System HIDPAS
This paper proposes an intrusion detection and prediction system based on uncertain and imprecise inference networks and its implementation. Giving a historic of sessions, it is about proposing a method of supervised learning doubled of a classifier permitting to extract the necessary knowledge in order to identify the presence or not of an intrusion in a session and in the positive case to rec...
متن کاملA Review of Intrusion Detection Defense Solutions Based on Software Defined Network
Most networks without fixed infrastructure are based on cloud computing face various challenges. In recent years, different methods have been used to distribute software defined network to address these challenges. This technology, while having many capabilities, faces some vulnerabilities in the face of some common threats and destructive factors such as distributed Denial of Service. A review...
متن کاملBeeID: intrusion detection in AODV-based MANETs using artificial Bee colony and negative selection algorithms
Mobile ad hoc networks (MANETs) are multi-hop wireless networks of mobile nodes constructed dynamically without the use of any fixed network infrastructure. Due to inherent characteristics of these networks, malicious nodes can easily disrupt the routing process. A traditional approach to detect such malicious network activities is to build a profile of the normal network traffic, and then iden...
متن کاملComparative Analysis of Machine Learning Algorithms with Optimization Purposes
The field of optimization and machine learning are increasingly interplayed and optimization in different problems leads to the use of machine learning approaches. Machine learning algorithms work in reasonable computational time for specific classes of problems and have important role in extracting knowledge from large amount of data. In this paper, a methodology has been employed to opt...
متن کاملA New Method for Intrusion Detection Using Genetic Algorithm and Neural Network
The article attempts to have neural network and genetic algorithm techniques present a model for classification on dataset. The goal is design model can the subject acted a firewall in network and this model with compound optimized algorithms create reliability and accuracy and reduce error rate couse of this is article use feedback neural network and compared to previous methods increase a...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2006