A Cooperative Negative Selection Algorithm for Anomaly Detection
نویسندگان
چکیده
منابع مشابه
A Cooperative Negative Selection Algorithm for Anomaly Detection
Artificial Immune System (AIS) is a convoluted and complex arrangement derived from biological immune system (BIS). It possesses the abilities of self-adapting, self-learning and self-configuration. It has the basic function to distinguish self and non-self. Negative Selection Algorithm (NSA) over the years has shown to be competent for anomaly detection problems. In the past decade internet ha...
متن کاملNegative selection algorithm with constant detectors for anomaly detection
In the paper, two novel negative selection algorithms (NSAs) were proposed: FB-NSA and FFB-NSA. FBNSA has two types of detectors: constant-sized detector (CFB-NSA) and variable-sized detector (VFBNSA). The detectors of traditional NSA are generated randomly. Even for the same training samples, the position, size, and quantity of the detectors generated in each time are different. In order to el...
متن کاملDynamically Real-time Anomaly Detection Algorithm with Immune Negative Selection
Network anomaly detection has become the promising aspect of intrusion detection. The existing anomaly detection models depict the detection profiles with a static way, which lack good adaptability and interoperability. Furthermore, the detection rate is low, so they are difficult to be deployed the realtime detection under the high-speed network environment. In this paper, the excellent mechan...
متن کاملHybrid Negative Selection Approach for Anomaly Detection
This paper describes b-v model which is enhanced version of the negative selection algorithm (NSA). In contrast to formerly presented approaches, binary and real-valued detectors are incorporated. The reason behind developing this hybrid is willingness to overcome the scalability problems, which are a key problem, when only one type of detectors is used. Although high-dimensional datasets are a...
متن کاملAnomaly Detection Using Neighborhood Negative Selection
Negative Selection Algorithms (NSAs) have been widely used in anomaly detection. As the security issue becomes more complex, more and more anomaly detection schemes involve high-dimension data. NSAs however perform poorly on effectiveness and efficiency when dealing with high-dimension data. To address these issues, we propose a Neighborhood Negative Selection (NNS) algorithm in this paper. Ins...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: International Journal of Computer Applications
سال: 2014
ISSN: 0975-8887
DOI: 10.5120/16688-6809