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This paper explores the use of an artificial immune system (AIS) for network intrusion detection. As one significant component for a complete AIS, static clonal selection with a negative selection operator is developed and the system is described in detail. Two important factors, the detector sample size and the antigen sample size, are investigated in(More)
artificial immune system, intrusion detection, danger theory, apoptosis We present ideas about creating a next generation Intrusion Detection System (IDS) based on the latest immunological theories. The central challenge with computer security is determining the difference between normal and potentially harmful activity. For half a century, developers have(More)
One significant feature of artificial immune systems is their ability to adapt to continuously changing environments, dynamically learning the fluid patterns of 'self' and predicting new patterns of 'non-self'. This paper introduces and investigates the behaviour of dynamiCS, a dynamic clonal selection algorithm, designed to have such properties of(More)
This paper presents a negative selection algorithm with niching by an artificial immune system, for network intrusion detection. The paper starts by introducing the advantages of negative selection algorithm as a novel distributed anomaly detection approach for the development of a network intrusion detection system. After discussing the problems of(More)
In this paper, we present the design and implementation of an Open Computing Language (OpenCL) framework that targets heterogeneous accelerator multicore architectures with local memory. The architecture consists of a general-purpose processor core and multiple accelerator cores that typically do not have any cache. Each accelerator core, instead, has a(More)
The role of T-cells within the immune system is to confirm and assess anomalous situations and then either respond to or tolerate the source of the effect. To illustrate how these mechanisms can be harnessed to solve real-world problems, we present the blueprint of a T-cell inspired algorithm for computer security worm detection. We show how the three(More)
The retail sector often does not possess sufficient knowledge about potential or actual frauds. This requires the retail sector to employ an anomaly detection approach to fraud detection. To detect anomalies in retail transactions, the fraud detection system introduced in this work implements various salient features of the human immune system. This novel(More)
Conversion of analog signals into digital signals is one of the most important functionalities in modern signal processing systems. As the signal frequency increases beyond 10 GHz, the timing jitter from electronic clocks, currently limited at approximately 100 fs, compromises the achievable resolution of analog-to-digital converters (ADCs). Owing to their(More)
There is a list of unique immune features that are currently absent from the existing artificial immune systems and other intelligent paradigms. We argue that some of AIS features can be inherent in an application itself, and thus this type of application would be a more appropriate substrate in which to develop and integrate the benefits brought by AIS. We(More)
This paper reviews and assesses the analogy between the human immune system and network intrusion detection systems. The promising results from a growing number of proposed computer immune models for intrusion detection motivate this work. The paper begins by briefly introducing existing intrusion detection systems (IDS's). A set of general requirements for(More)