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Computer forensics is the crucial technology against computer crimes. However, existing forensics methods or technology are inefficient and their stringencies are poor. This paper proposed a novel dynamic computer forensics model (DAIP) based on artificial immune and real-time network fatalness, which can vivify the crime scene. The definitions of self, non-self, and immunocyte in the network transactions...
The security situation of the Internet of Things (IoT) is serious. IoT encounters security problems more than traditional computer networks does. The attributes of dispersity and mass of IoT require that approaches to IoT security should be dynamic. Inspired by immunology, a novel approach to IoT security is proposed in this paper. Traditional network security models are used for reference and special...
Artificial immune systems (AIS) utilize isolated mechanisms of the immune system to build specific algorithms. However, the immune system functions as a holistic system to protect the human body. In the same way, we propose to integrate independent AIS algorithms to build holistic AIS, namely unified artificial immune system (UAIS). It pushes AIS research to a higher level. We expect to see more powerful...
This paper proposed a model for credit card fraud detection system, which is aimed to improve the current risk management by adding an Artificial Immune System's algorithm to fraud detection system. For achieving to this goal, we parallelize the negative selection algorithm on the cloud platform such as apache hadoop and mapreduce. The algorithm execute with three detectors set. The experiments show...
A network security situation awareness model based on cooperative artificial immune system is discussed in this paper. In this model, efficient memory detectors in different computers can share the differences and improve the coverage and scalability of AIS. These detectors spread in the whole system can be organized by a cooperative channel. The function of the cooperative module is sending and receiving...
There is much comparability between natural immune system and computer security, and the key point is how to distinguish self from other. Based on the principles and structures of artificial immune system, the simulation modeling of network intrusion detection was developed. The model consisted of many nodes that distributed across different locations. The nodes needed not be centralized controlled...
Security is an important issue for building and sustaining trust relationship in cloud computing and in the usage of web-based applications. Consequently, intrusion detectors that adopt allowable and disallowable concepts are used in network forensics. The disallowable policy enforcers alert on events that are known to be bad while the allowable policy enforcers monitor events that deviate from known...
This article refers to a system that combines ZigBee and RFID technologies for monitoring people behavior when moving inside a building. The RFID part of our system consists of a set of detector placed at strategic points. To accomplish this detection goal the visitors of the building have to be provided with a RFID tag either active or passive. The ZigBee wireless subsystem will send the information...
A layered multi-agent detection model for abnormal intrusion, based on danger theory, is presented according to the research on the danger theory and artificial immunity. The model, with three layers in the frame, conducts the real time monitoring and danger judgment on the host computer and network resource before it recognizes the nonself, and then the danger signal activates the immunity recognition...
All runtime management decisions in computer and information systems require immediate detection of relevant changes in the state of their resources. This is accomplished by continuously monitoring the performance/utilization of key system resources and by using appropriate statistical tests to detect the occurance of significant state changes. Unfortunately, the complexity of today systems and applications...
This paper presents a controllable and adaptable computer virus detection model based on immune system, improves the immune mechanism of the model by introducing the thought of variable detector radius, and achieves the detector radius be set and adjusted automatically. The virus detection model has some effects on solving the conflict between the number of detectors and the scope of detection. Thus...
To effectively evaluate and predict network security situation, a quantitative model for network security situation awareness based on artificial immune system and grey theory is proposed. In this model, the formal definitions of self, non-self, antigen and detector is given. According to the relationship between the antibody-concentration of memory detector and the attack intensity of network, network...
Computer virus scanner is a vital approach to deal with computer virus. However, current static scanning techniques for virus detection have serious limitations. Motivated by a recent success in Computer Immune Theory and N-gram text classification method, an immune inspired obfuscated virus detection model is presented, which is referred as IOVDM. In IOVDM, N-gram analysis is applied to automatically...
In this paper we show that it is possible to implement a perfect failure detector P (one that detects all faulty processes if and only if those processes failed) in a non-synchronous distributed system. To realize that, we introduce the partitioned synchronous system (Spa) that is weaker than the conventional synchronous system. From some properties we introduce (such as strong partitioned synchrony)...
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...
Malicious programs are an ever increasing threat to current computer systems. Traditional anti-virus techniques focus typically on detection of the static signatures of worms. In this paper the method for generalization and specialization of attack pattern using inductive learning is proposed, which can be used updating and expanding knowledge database. The attack pattern is established from an example...
In this paper we present a low cost fault-tolerant attitude determination system to a scientific satellite using COTS devices. We related our experience in developing the attitude determination system, where we combine proven fault tolerance techniques to protect the whole system composed only by COTS from the effects produced by transient faults. We detailed the failure cases and the detection, reconfiguration...
The research presented in this paper aims at developing and validating a predictive tool of individual exposure to solar Ultra-Violet (UV). UV exposure depends on ambient irradiation level and individual factors related to activity (position to the sun, clothing, duration of exposure, and other forms of sun protection). We predict exposure levels of body parts on basis of ambient irradiation levels...
Spectrum sensing in the context of wireless microphone (WM) signals is considered in this paper. The spectrum sensing algorithm developed in this study makes use of the property that the bandwidth of the WM signal is narrow compared with the bandwidth of a digital television (DTV) channel. As a result, the power of the WM signal is highly concentrated in the frequency domain and there are apparent...
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...
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