Analysis and application of node layout algorithms for intrusion detection
نویسندگان
چکیده
The need to monitor today’s networked computer systems for security purposes is a major concern. Our monitoring environment aids system administrators in keeping track of the activities on such systems with much lower time requirements than that of perusing typical log files. With many systems connected to the network the task becomes significantly more difficult. If an attack is identified on one system then all systems have likely been attacked. The ability to correlate activity among multiple machines is critical for complete analysis and monitoring of the environment. Developing an effective organization of the nodes (systems) on the display is a nontrivial task. The organization must clearly show activity on all systems simultaneously while not cluttering the display or unnecessarily distracting the user. This paper discusses the layout techniques we have experimented with and their effectiveness.
منابع مشابه
Intrusion Detection in Wireless Sensor Networks using Genetic Algorithm
Wireless sensor networks, due to the characteristics of sensors such as wireless communication channels, the lack of infrastructure and targeted threats, are very vulnerable to the various attacks. Routing attacks on the networks, where a malicious node from sending data to the base station is perceived. In this article, a method that can be used to transfer the data securely to prevent attacks...
متن کاملA Hybrid Machine Learning Method for Intrusion Detection
Data security is an important area of concern for every computer system owner. An intrusion detection system is a device or software application that monitors a network or systems for malicious activity or policy violations. Already various techniques of artificial intelligence have been used for intrusion detection. The main challenge in this area is the running speed of the available implemen...
متن کاملA Novel Intrusion Detection Systems based on Genetic Algorithms-suggested Features by the Means of Different Permutations of Labels’ Orders
Intrusion detection systems (IDS) by exploiting Machine learning techniques are able to diagnose attack traffics behaviors. Because of relatively large numbers of features in IDS standard benchmark dataset, like KDD CUP 99 and NSL_KDD, features selection methods play an important role. Optimization algorithms like Genetic algorithms (GA) are capable of finding near-optimum combination of the fe...
متن کاملAssessment Methodology for Anomaly-Based Intrusion Detection in Cloud Computing
Cloud computing has become an attractive target for attackers as the mainstream technologies in the cloud, such as the virtualization and multitenancy, permit multiple users to utilize the same physical resource, thereby posing the so-called problem of internal facing security. Moreover, the traditional network-based intrusion detection systems (IDSs) are ineffective to be deployed in the cloud...
متن کاملTwo optimal algorithms for finding bi-directional shortest path design problem in a block layout
In this paper, Shortest Path Design Problem (SPDP) in which the path is incident to all cells is considered. The bi-directional path is one of the known types of configuration of networks for Automated Guided Vehi-cles (AGV).To solve this problem, two algorithms are developed. For each algorithm an Integer Linear Pro-gramming (ILP) is determined. The objective functions of both algorithms are t...
متن کاملتولید خودکار الگوهای نفوذ جدید با استفاده از طبقهبندهای تک کلاسی و روشهای یادگیری استقرایی
In this paper, we propose an approach for automatic generation of novel intrusion signatures. This approach can be used in the signature-based Network Intrusion Detection Systems (NIDSs) and for the automation of the process of intrusion detection in these systems. In the proposed approach, first, by using several one-class classifiers, the profile of the normal network traffic is established. ...
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 2003