scholarly journals Malware Analysis Using Visualized Image Matrices

2014 ◽  
Vol 2014 ◽  
pp. 1-15 ◽  
Author(s):  
KyoungSoo Han ◽  
BooJoong Kang ◽  
Eul Gyu Im
Keyword(s):  
Visual Analysis ◽  
Application Programming Interface ◽  
Malware Analysis ◽  
Analysis Method ◽  
Execution Traces ◽  
Similarity Calculation ◽  
Application Programming ◽  
Representative Image ◽  
Programming Interface

This paper proposes a novel malware visual analysis method that contains not only a visualization method to convert binary files into images, but also a similarity calculation method between these images. The proposed method generates RGB-colored pixels on image matrices using the opcode sequences extracted from malware samples and calculates the similarities for the image matrices. Particularly, our proposed methods are available for packed malware samples by applying them to the execution traces extracted through dynamic analysis. When the images are generated, we can reduce the overheads by extracting the opcode sequences only from the blocks that include the instructions related to staple behaviors such as functions and application programming interface (API) calls. In addition, we propose a technique that generates a representative image for each malware family in order to reduce the number of comparisons for the classification of unknown samples and the colored pixel information in the image matrices is used to calculate the similarities between the images. Our experimental results show that the image matrices of malware can effectively be used to classify malware families both statically and dynamically with accuracy of 0.9896 and 0.9732, respectively.

Sistem Pengawasan Aktifitas Penggunaan Smartphone Android

2018 ◽  
Vol 9 (1) ◽  
pp. 24-31
Author(s):  
Rudianto Rudianto ◽  
Eko Budi Setiawan
Keyword(s):  
Application Programming Interface ◽  
Third Party ◽  
Image Content ◽  
Image File ◽  
Application Programming ◽  
Index Terms ◽  
Programming Interface

Availability the Application Programming Interface (API) for third-party applications on Android devices provides an opportunity to monitor Android devices with each other. This is used to create an application that can facilitate parents in child supervision through Android devices owned. In this study, some features added to the classification of image content on Android devices related to negative content. In this case, researchers using Clarifai API. The result of this research is to produce a system which has feature, give a report of image file contained in target smartphone and can do deletion on the image file, receive browser history report and can directly visit in the application, receive a report of child location and can be directly contacted via this application. This application works well on the Android Lollipop (API Level 22). Index Terms— Application Programming Interface(API), Monitoring, Negative Content, Children, Parent.

scholarly journals GIS-based NNA and Kernel Density Analysis for Identifying Distribution of Restaurant’s Popularity Index in Bandung

2021 ◽  
Vol 940 (1) ◽  
pp. 012012
Author(s):  
S S A’idah ◽  
D Susiloningtyas ◽  
I P A Shidiq
Keyword(s):  
Application Programming Interface ◽  
Distribution Patterns ◽  
Gis Applications ◽  
Information And Communication ◽  
Density Analysis ◽  
Application Programming ◽  
Surrounding Space ◽  
Kernel Density Analysis ◽  
Programming Interface

Abstract With the advancement of information and communication technology, geographic information systems (GIS) also grow. The existence of GIS allows problems to be solved as much as possible by paying attention to the surrounding space. GIS applications have been widely applied in everyday life including in the culinary field. The existence of GIS in the culinary field can make it easier to find location information where a restaurant is located and find out how the restaurant’s popularity index is. This research focuses on using NNA and KDA to analyze distribution patterns formed from each classification of restaurant popularity index in Bandung and the density of the restaurant point. Restaurant data containing restaurant names, restaurant addresses, restaurant types, food types, and restaurant popularity indexes were obtained from Zomato using Zomato’s Application Programming Interface (API). The result of this research are spatial distribution pattern of the high, medium, and low popularity restaurants in Bandung City showing the same characteristics, clustering and has a large density in several sub-districts.

scholarly journals Cross-Method-Based Analysis and Classification of Malicious Behavior by API Calls Extraction

2019 ◽  
Vol 9 (2) ◽  
pp. 239 ◽  
Author(s):  
Bruce Ndibanje ◽  
Ki Kim ◽  
Young Kang ◽  
Hyun Kim ◽  
Tae Kim ◽  
...  
Keyword(s):  
Application Programming Interface ◽  
Machine Learning Algorithms ◽  
Data Driven ◽  
Public Security ◽  
Detection Accuracy ◽  
Malicious Behavior ◽  
Application Programming ◽  
Programming Interface ◽  
Method Show

Data-driven public security networking and computer systems are always under threat from malicious codes known as malware; therefore, a large amount of research and development is taking place to find effective countermeasures. These countermeasures are mainly based on dynamic and statistical analysis. Because of the obfuscation techniques used by the malware authors, security researchers and the anti-virus industry are facing a colossal issue regarding the extraction of hidden payloads within packed executable extraction. Based on this understanding, we first propose a method to de-obfuscate and unpack the malware samples. Additional, cross-method-based big data analysis to dynamically and statistically extract features from malware has been proposed. The Application Programming Interface (API) call sequences that reflect the malware behavior of its code have been used to detect behavior such as network traffic, modifying a file, writing to stderr or stdout, modifying a registry value, creating a process. Furthermore, we include a similarity analysis and machine learning algorithms to profile and classify malware behaviors. The experimental results of the proposed method show that malware detection accuracy is very useful to discover potential threats and can help the decision-maker to deploy appropriate countermeasures.

scholarly journals Advanced soft robot modeling in ChainQueen

Robotica ◽  
2021 ◽  
pp. 1-31
Author(s):  
Andrew Spielberg ◽  
Tao Du ◽  
Yuanming Hu ◽  
Daniela Rus ◽  
Wojciech Matusik
Keyword(s):  
Application Programming Interface ◽  
Material Point ◽  
Soft Robotics ◽  
Soft Robot ◽  
Inference Control ◽  
Simulation And Optimization ◽  
Efficient Simulation ◽  
Application Programming ◽  
Robot Modeling ◽  
Programming Interface

Abstract We present extensions to ChainQueen, an open source, fully differentiable material point method simulator for soft robotics. Previous work established ChainQueen as a powerful tool for inference, control, and co-design for soft robotics. We detail enhancements to ChainQueen, allowing for more efficient simulation and optimization and expressive co-optimization over material properties and geometric parameters. We package our simulator extensions in an easy-to-use, modular application programming interface (API) with predefined observation models, controllers, actuators, optimizers, and geometric processing tools, making it simple to prototype complex experiments in 50 lines or fewer. We demonstrate the power of our simulator extensions in over nine simulated experiments.

A Layered Mapping of Ada 202X to OpenMP

2021 ◽  
Vol 40 (2) ◽  
pp. 55-58
Author(s):  
S. Tucker Taft
Keyword(s):  
Operating System ◽  
Application Programming Interface ◽  
Light Weight ◽  
Main Interest ◽  
Thread Scheduling ◽  
Environment Variables ◽  
Application Programming ◽  
Parallel Loops ◽  
Programming Interface

The OpenMP specification defines a set of compiler directives, library routines, and environment variables that together represent the OpenMP Application Programming Interface, and is currently defined for C, C++, and Fortran. The forthcoming version of Ada, currently dubbed Ada 202X, includes lightweight parallelism features, in particular parallel blocks and parallel loops. All versions of Ada, since its inception in 1983, have included "tasking," which corresponds to what are traditionally considered "heavyweight" parallelism features, or simply "concurrency" features. Ada "tasks" typically map to what are called "kernel threads," in that the operating system manages them and schedules them. However, one of the goals of lightweight parallelism is to reduce overhead by doing more of the management outside the kernel of the operating system, using a light-weight-thread (LWT) scheduler. The OpenMP library routines support both levels of threading, but for Ada 202X, the main interest is in making use of OpenMP for its lightweight thread scheduling capabilities.

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