Physical memory forensics has grown in popularity in recent years. Since malware typically operate in user space, it is important to reconstruct and track their process behavior. This paper focuses on detecting malware through a comparison of the information in the user space memory data structures. In order to expedite information extraction and ensure accuracy, the data in multiple memory management structures in the user space and the kernel are used concurrently. In the proposed method,using descriptions of memory structures, weextractmalware artifactsrelated to registry changes as well as, calls to library files and operating system functions.The extracted features are then evaluated, and samples are classified according to the selected attributes.The best results include a 98% detection rate and false positive rate of 16%, which indicates the effectiveness of the proposed behavior extraction method.
This paper presents a new algorithm for global path planning to a goal for a mobile robot using GA and fuzzy Algorithms. A genetic algorithm is used to find the optimal path for a mobile robot to move in a dynamic environment expressed by a map with nodes and links. Locations of target and obstacles to find an optimal path are given in an environment that is a 2-D workplace. Each via point (landmark) in the net is a gene which is represented using binary code. The number of genes in one chromosome is function of the number of obstacles in the map. Therefore, we used a fixed length chromosome. The generated robot path is optimal in the sense of the shortest distance. The fitness function of genetic algorithm takes full consideration of three factors: the collision avoidance path, the shortest distance and smoothness of the path. The specific genetic operators are also selected to make the genetic algorithm more effective. The simulation results verify that the genetic algorithm is high effective under various complex dynamic alien environments.
In This paper we proposed a novel fuzzy retrieval system for purchasing cars employing image processing. The car shape is an important factor when selecting a car type. This system aims to support persons who are not good with cars. When we try to purchase a car, they can use this system easily as if they ask casually someone else who knows more about car. Unspecific conditions are expressed by the fuzzy set, and the level matching conditions are expressed by the grade values. To use this more practically, a GUI form with selection menus is developed. This system is designed to change membership function automatically for improving usability of this system. In addition, calculating curvature by the car shape using the image processing, and adding items for selecting a car shape from roundness and sharpness. Furthermore, the effectiveness of applying fuzzy logic to express man's subjectivity when selecting car type.
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