Detecting Anomalous Process Behaviour Using Second Generation Artificial Immune Systems
نویسندگان
چکیده
منابع مشابه
Detecting Anomalous Process Behaviour Using Second Generation Artificial Immune Systems
Artificial Immune Systems have been successfully applied to a number of problem domains including fault tolerance and data mining, but have been shown to scale poorly when applied to computer intrusion detection despite the fact that the biological immune system is a very effective anomaly detector. This may be because AIS algorithms have previously been based on the adaptive immune system and ...
متن کاملDetecting Anomalous Behaviour Using Heterogeneous Data
In this paper, we propose a method to detect anomalous behaviour using heterogenous data. This method detects anomalies based on the recently introduced approach known as Recursive Density Estimation (RDE) and the so called eccentricity. This method does not require prior assumptions to be made on the type of the data distribution. A simplified form of the well-known Chebyshev condition (inequa...
متن کاملDetecting Mobile Spam Botnets Using Artificial immune Systems
Malicious software infects large numbers of computers around the world. Once compromised, the computers become part of a botnet and take part in many forms of criminal activity, including the sending of unsolicited commercial email or spam. As mobile devices become tightly integrated with the Internet, associated threats such as botnets have begun to migrate onto the devices. This paper describ...
متن کاملSemantic Preserving Data Reduction using Artificial Immune Systems
Artificial Immune Systems (AIS) can be defined as soft computing systems inspired by immune system of vertebrates. Immune system is an adaptive pattern recognition system. AIS have been used in pattern recognition, machine learning, optimization and clustering. Feature reduction refers to the problem of selecting those input features that are most predictive of a given outcome; a problem encoun...
متن کاملsemantic preserving data reduction using artificial immune systems
artificial immune systems (ais) can be defined as soft computing systems inspired by immune system of vertebrates. immune system is an adaptive pattern recognition system. ais have been used in pattern recognition, machine learning, optimization and clustering. feature reduction refers to the problem of selecting those input features that are most predictive of a given outcome; a problem encoun...
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: SSRN Electronic Journal
سال: 2010
ISSN: 1556-5068
DOI: 10.2139/ssrn.2823358