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A novel IDS model based on Bayesian fusion approach is studied in this paper. The model comprises several parts such as the pixel level fusion, feature level fusion, decision-making level fusion and so on. Experiments show that the model could result in a better recognition of attacks through processing procedures including noise reduction, feature extraction, inference and decision-making.
Malicious software is one of the most popular security threats of computer networks. It is difficult for traditional solutions to deal with dynamical and variable behaviors against malicious software. Danger model theory is a hypothesis of artificial immune systems. This hypothesis explains what is malicious from the trend of behaviors in a computer system. This paper presented a novel idea that malicious...
Under intrusion or abnormal attack, how to autonomously supply service, without being degraded, to users is the ultimate goal of network security technology. Based on Martingale Difference Approximation principle, a System Service Optimization Model (MDAO) is proposed. According to the prior self optimizing knowledge and parameter information of inner environment, MDAO searches the convergence trend...
Computer networks are one of those unique gifts of modern science which enriched human life with the blessing of global connectivity. But as the network advanced, intrusions and misuses followed. Consequently, network security has come into issue. Now-a-days intrusion detection systems have become a standard component in security infrastructures. Intrusions typically start with intruders infiltrating...
File sharing is a common practice since the introduction of computer networks. It involves using technology that allows network users to share files that are stored on their individual computers. Peer-to-peer or simply P2P applications, such as those used to share multimedia files, are some of the most common forms of file-sharing technology. However, P2P applications are vulnerable to security risks...
With the progression of time, we have been blessed with the gifts of science. Computer networks are one of those gifts. But as the network proceeded, intrusions and misuses followed. Consequently, network security has come to the fore front and has become one of the most important issues. Now-a-days intrusion detection systems have become a standard component in security infrastructures. Intrusions...
An artificial immune system (ARTIS) enlightened by the biological immune system is emerging as a new field of computation intelligence research. At present, it showed us many properties after the research to the immune system, including distributed computation, self-organization and lightweight, which were discovered to meet the requests of ARTIS. So the Immunology applied to the intrusion detection...
The rapid development of computer network sets off a global wave of enterprise informatization. Enterprisespsila cross-regional telecommuting and internal information sharing platform are more and more dependent on the networks. However, the Internetpsilas open communication protocol and the limitations of the original design lead to increasingly serious problem of Internet security, and it caused...
Advances in Digital Technology have presented new challenges to both Industry and Law. Technology security experts are enhancing platforms security to protect enterprise and government from intrusions, whereas legal experts are adopting new techniques to investigate ldquoillegalrdquo breaches to systems and networks. This paper provides an overview of Digital Forensics methodologies, computer and...
The aim of the contribution is to present an attempt to utilize some data about network topology and performance to increase capabilities of intrusion detection system. Some simple example presents an approach to design topology (location and the needed number of intrusion detection devices) which allows efficiently detecting intrusions and limiting the overall overhead caused by intrusion detection...
The rapid proliferation of computer networks has changed the prospect of network security. An easy accessibility condition cause computer networkpsilas vulnerable against several threats from hackers. Threats to networks are numerous and potentially devastating. Up to the moment, researchers have developed Intrusion Detection Systems (IDS) capable of detecting attacks in several available environments...
Recently network intrusion detection is one of the hottest research topics. Existing network-based Intrusion Detection System (IDS) has drawbacks in many aspects, among of which the two outstanding problems are the high ratio of false alarms and the lack of self-adaptation. The powerful information processing capabilities of the biological immune system, such as feature extraction, pattern recognition,...
With the rapid development of network technologies and deteriorating of network environment, traditional single-net security system can't satisfy the security requirement. The excellent security performance of biological systems impels the bio-inspired network security theory to be a hot research area currently. Based on BMNSM (bio-inspired multidimensional network security model) we have put forward,...
Recent security incidents and analysis have demonstrated that current intrusion detection systems (1DS) to some attacks are no longer feasible. Implementing an effective intrusion detection capability is an elusive goal, not solved easily or with a single mechanism. However, we argue that "SoftMan" (SM) technology goes a long way toward realizing the ideal behavior desired in an intrusion...
As an important method to analyze the security status of computer network, generating of network attack graph is a hot topic in this domain. After analyzing network security attributes including the host, user privilege, connection relation, etc., the model of computer network security status space is built. The node of attack graph expresses the network security status, and the directed-line expresses...
The 3 most important issues for anomaly detection based intrusion detection systems by using data mining methods are: feature selection, data value normalization, and the choice of data mining algorithms. In this paper, we study primarily the feature selection of network traffic and its impact on the detection rates. We use KDD CUP 1999 dataset as the sample for the study. We group the features of...
In this paper, we study the problem of anomaly detection in high-dimensional network streams. We have developed a new technique, called Stream Projected Outlier deTector (SPOT), to deal with the problem of anomaly detection from high-dimensional data streams. We conduct a case study of SPOT in this paper by deploying it on 1999 KDD Intrusion Detection application. Innovative approaches for training...
An immune method for real-time computer network security risk evaluation is proposed. The concepts of self, nonself, antigen and immunocyte of computer immune system are defined. The dynamic model of self, marrow model, clone selection, learning scheme, life span of immunocyte are built. A computational model of risk evaluation based on the antibody concentration of memory immunocytes for network...
Computer system security evaluation by using mean time-to-compromise criteria is presented in this paper. The outcome of the attack highly depends on the attacker skill level. The attacker skill level distribution must be estimated, normal skill level distribution in the skill group is suggested in the model. The article concludes with simulation results and evaluation of the chosen attacker skill...
While a considerable amount of research has been done for detecting the binary worms exploiting the vulnerability of buffer overflow, very little effort has been spent in detecting worms that consist of only text, Le., printable ASCII characters. We show that the existing worm detectors often either do not examine the ASCII stream or are not well suited to efficiently detect worms in the ASCII stream...
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