Recent advances in artificial immune systems: models and applications
D Dasgupta, S Yu, F Nino - Applied Soft Computing, 2011 - Elsevier
The immune system is a remarkable information processing and self learning system that
offers inspiration to build artificial immune system (AIS). The field of AIS has obtained a …
offers inspiration to build artificial immune system (AIS). The field of AIS has obtained a …
Local non-negative matrix factorization as a visual representation
Proposes a novel method, called local non-negative matrix factorization (LNMF), for learning
a spatially localized, parts-based subspace representation of visual patterns. An objective …
a spatially localized, parts-based subspace representation of visual patterns. An objective …
Outbreak detection model based on danger theory
In outbreak detection, one of the key issues is the need to deal with the weakness of early
outbreak signals because this causes the detection model to have has less capability in …
outbreak signals because this causes the detection model to have has less capability in …
An immune optimization based deterministic dendritic cell algorithm
W Zhou, Y Liang - Applied Intelligence, 2022 - Springer
Anomaly detection is an important issue, which has been deeply studied in different
research domains and application fields. The dendritic cell algorithm (DCA) is one of the …
research domains and application fields. The dendritic cell algorithm (DCA) is one of the …
Run-time malware detection based on positive selection
Z Fuyong, Q Deyu - Journal in computer virology, 2011 - Springer
This paper presents a supervised methodology that detects malware based on positive
selection. Malware detection is a challenging problem due to the rapid growth of the number …
selection. Malware detection is a challenging problem due to the rapid growth of the number …
Bait a trap: introducing natural killer cells to artificial immune system for spyware detection
J Fu, H Yang, Y Liang, C Tan - … , ICARIS 2012, Taormina, Italy, August 28 …, 2012 - Springer
Abstract Artificial Immune System (AIS) achieved some success in malware detection with its
distributed, diverse and adaptive characteristics. However, in recent years, malware is …
distributed, diverse and adaptive characteristics. However, in recent years, malware is …
Insights into the antigen sampling component of the dendritic cell algorithm
CJ Musselle - International Conference on Artificial Immune Systems, 2010 - Springer
The aim of this paper is to investigate the antigen sampling component of the deterministic
version of the dendritic cell algorithm (dDCA). To achieve this, a model is presented, and …
version of the dendritic cell algorithm (dDCA). To achieve this, a model is presented, and …
Integrated negative selection algorithm and positive selection algorithm for malware detection
F Zhang, Y Ma - 2016 International Conference on Progress in …, 2016 - ieeexplore.ieee.org
Run-time malware detection strategies are efficient and robust, which get more and more
attention. In this paper, we use I/O Request Package (IRP) sequences for malware detection …
attention. In this paper, we use I/O Request Package (IRP) sequences for malware detection …
A Danger‐Theory‐Based Immune Network Optimization Algorithm
R Zhang, T Li, X Xiao, Y Shi - The Scientific World Journal, 2013 - Wiley Online Library
Existing artificial immune optimization algorithms reflect a number of shortcomings, such as
premature convergence and poor local search ability. This paper proposes a danger‐theory …
premature convergence and poor local search ability. This paper proposes a danger‐theory …
Dynamic innate immune system model for malware detection
Malware stand for Malicious Software became a major threat facing the massive amount of
data transmitted through the internet and the systems holding that data. Malware detection is …
data transmitted through the internet and the systems holding that data. Malware detection is …