A new method of fuzzy patches construction in Neuro-Fuzzy for malware detection
نویسندگان
چکیده
Soft Computing is being widely used in Information Security applications. Particularly, Neuro-Fuzzy approach provides a classification with humanunderstandable rules, yet the accuracy may not be sufficiently high. In this paper we seek for an optimal fuzzy patch configuration that uses elliptic fuzzy patches to automatically extract parameters for the Mamdami-type rules. We proposed a new method based on χ2 test of data to estimate rotatable patch configuration together with Gaussian membership function. This method has been tested on the automated malware analysis with accuracy up to 92%. Further on, it can find an application in Digital Forensics.
منابع مشابه
Time Prediction Using a Neuro-Fuzzy Model for Projects in the Construction Industry
This paper presents a prediction model based on a new neuro-fuzzy algorithm for estimating time in construction projects. The output of the proposed prediction model, which is employed based on a locally linear neuro-fuzzy (LLNF) model, is useful for assessing a project status at different time horizons. Being trained by a locally linear model tree (LOLIMOT) learning algorithm, the model is int...
متن کاملApplication of Adaptive Neuro-Fuzzy Inference System for Information Secuirty
Problem statement: Computer networks are expanding at very fast rate and the number of network users is increasing day by day, for full utilization of networks it need to be secured against many threats including malware, which is harmful software with the capability to damage data and systems. Fuzzy rule based classification systems considered as an active research area in recent years, due to...
متن کاملIntelligent Hybrid Approach for Android Malware Detection based on Permissions and API Calls
Android malware is rapidly becoming a potential threat to users. The number of Android malware is growing exponentially; they become significantly sophisticated and cause potential financial and information losses for users. Hence, there is a need for effective and efficient techniques to detect the Android malware applications. This paper proposes an intelligent hybrid approach for Android mal...
متن کاملA NEURO-FUZZY TECHNIQUE FOR DISCRIMINATION BETWEEN INTERNAL FAULTS AND MAGNETIZING INRUSH CURRENTS IN TRANSFORMERS
This paper presents the application of the fuzzy-neuro method toinvestigate transformer inrush current. Recently, the frequency environment ofpower systems has been made more complicated and the magnitude of the secondharmonic in inrush current has been decreased because of the improvement of caststeel. Therefore, traditional approaches will likely mal-operate in the case ofmagnetizing inrush w...
متن کاملA New Structure for Direct Measurement of Temperature Based on Negative Temperature Coefficient Thermistor and Adaptive Neuro-fuzzy Inference System
Thermistors are very commonly used for narrow temperature-range high-resolution applications, such as in medicine, calorimetry, and near ambient temperature measurements. In particular, Negative Temperature Coefficient (NTC) thermistor is very inexpensive and highly sensitive, whose sensing temperature range and sensitivity are highly limited due to the intrinsic nonlinearity and self-heating p...
متن کامل