Visual Behavior Characterization for Intrusion Detection in Large Scale Systems
نویسنده
چکیده
This work focuses on the visual representation of relations towards aiding the exploration and analysis of network intrusions. Fundamentally, the visual representations aid an analyst in comprehending the activity of individuals incorporated within the data set. Their actions are represented visually using a node and link metaphor. The visualization aids the analyst in identifying the complex interactions intrinsic to identifying the overall goal of an individual, i.e., the individuals true behavior. Such analyses are becoming critical with the continuing growth of the Internet and the corresponding growth of hackers and attempted intrusions. This is complicated by the fact that hackers, in general, will attempt to hide their activities from analysis; thus increasing the complexity of the analysis needed to identify their actions, particularly when a successful intrusion has occurred.
منابع مشابه
Improving Accuracy in Intrusion Detection Systems Using Classifier Ensemble and Clustering
Recently by developing the technology, the number of network-based servicesis increasing, and sensitive information of users is shared through the Internet.Accordingly, large-scale malicious attacks on computer networks could causesevere disruption to network services so cybersecurity turns to a major concern fornetworks. An intrusion detection system (IDS) could be cons...
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 کاملA Survey of Anomaly Detection Approaches in Internet of Things
Internet of Things is an ever-growing network of heterogeneous and constraint nodes which are connected to each other and the Internet. Security plays an important role in such networks. Experience has proved that encryption and authentication are not enough for the security of networks and an Intrusion Detection System is required to detect and to prevent attacks from malicious nodes. In this ...
متن کاملAnomaly Detection Using SVM as Classifier and Decision Tree for Optimizing Feature Vectors
Abstract- With the advancement and development of computer network technologies, the way for intruders has become smoother; therefore, to detect threats and attacks, the importance of intrusion detection systems (IDS) as one of the key elements of security is increasing. One of the challenges of intrusion detection systems is managing of the large amount of network traffic features. Removing un...
متن کاملIntrusion Detection in IOT based Networks Using Double Discriminant Analysis
Intrusion detection is one of the main challenges in wireless systems especially in Internet of things (IOT) based networks. There are various attack types such as probe, denial of service, remote to local and user to root. In addition to known attacks and malicious behaviors, there are various unknown attacks that some of them have similar behavior with respect to each other or mimic the norma...
متن کامل