Search results for "network security"
showing 7 items of 37 documents
Development of Network Security Education
2021
Distance education has grown tremendously over the last decade. Internet technologies have enabled a large-scale dispensation of lectures, exercises, and training. Virtual Learning Management Systems (LMSs) offer a number of tools to realize distance education and distance learning. In this work, we present a virtual system architecture for training cyber security professionals with hands-on skills. The architecture is based on a VirtualBox virtualization environment. Guest machines are installed on an instance of VirtualBox. The installed environment offers a safe and isolated workbench for experiments. After installation and configuration of the environment, students perform a number of i…
Intelligent solutions for real-life data-driven applications
2017
The subject of this thesis belongs to the topic of machine learning or, specifically, to the development of advanced methods for regression analysis, clustering, and anomaly detection. Industry is constantly seeking improved production practices and minimized production time and costs. In connection to this, several industrial case studies are presented in which mathematical models for predicting paper quality were proposed. The most important variables for the prediction models are selected based on information-theoretic measures and regression trees approach. The rest of the original papers are devoted to unsupervised machine learning. The main focus is developing advanced spectral cluster…
Remote Attestation of Software and Execution-Environment in Modern Machines
2015
The research on network security concentrates mainly on securing the communication channels between two endpoints, which is insufficient if the authenticity of one of the endpoints cannot be determined with certainty. Previously presented methods that allow one endpoint, the authentication authority, to authenticate another remote machine. These methods are inadequate for modern machines that have multiple processors, introduce virtualization extensions, have a greater variety of side effects, and suffer from nondeterminism. This paper addresses the advances of modern machines with respect to the method presented by Kennell. The authors describe how a remote attestation procedure, involving…
Adaptive framework for network traffic classification using dimensionality reduction and clustering
2012
Information security has become a very important topic especially during the last years. Web services are becoming more complex and dynamic. This offers new possibilities for attackers to exploit vulnerabilities by inputting malicious queries or code. However, these attack attempts are often recorded in server logs. Analyzing these logs could be a way to detect intrusions either periodically or in real time. We propose a framework that preprocesses and analyzes these log files. HTTP queries are transformed to numerical matrices using n-gram analysis. The dimensionality of these matrices is reduced using principal component analysis and diffusion map methodology. Abnormal log lines can then …
A Network-Based Framework for Mobile Threat Detection
2018
Mobile malware attacks increased three folds in the past few years and continued to expand with the growing number of mobile users. Adversary uses a variety of evasion techniques to avoid detection by traditional systems, which increase the diversity of malicious applications. Thus, there is a need for an intelligent system that copes with this issue. This paper proposes a machine learning (ML) based framework to counter rapid evolution of mobile threats. This model is based on flow-based features, that will work on the network side. This model is designed with adversarial input in mind. The model uses 40 timebased network flow features, extracted from the real-time traffic of malicious and…
Support vector machine integrated with game-theoretic approach and genetic algorithm for the detection and classification of malware
2013
Abstract. —In the modern world, a rapid growth of mali- cious software production has become one of the most signifi- cant threats to the network security. Unfortunately, wides pread signature-based anti-malware strategies can not help to de tect malware unseen previously nor deal with code obfuscation te ch- niques employed by malware designers. In our study, the prob lem of malware detection and classification is solved by applyin g a data-mining-based approach that relies on supervised mach ine- learning. Executable files are presented in the form of byte a nd opcode sequences and n-gram models are employed to extract essential features from these sequences. Feature vectors o btained are…
Unsupervised network intrusion detection systems for zero-day fast-spreading network attacks and botnets
2015
Today, the occurrence of zero-day and complex attacks in high-speed networks is increasingly common due to the high number vulnerabilities in the cyber world. As a result, intrusions become more sophisticated and fast to detrimental the networks and hosts. Due to these reasons real-time monitoring, processing and intrusion detection are now among the key features of NIDS. Traditional types of intrusion detection systems such as signature base IDS are not able detect intrusions with new and complex strategies. Now days, automatic traffic analysis and anomaly intrusion detection became more efficient in field of network security however they suffer from high number of false alarms. Among all …