Pub Date : 2017-10-31DOI: 10.21512/commit.v11i2.2282
Rosalina, Lita Yusnita, N. Hadisukmana, R. B. Wahyu, Rusdianto Roestam, Yuyu Wahyu
Sign language is a language that requires the combination of hand gesture, orientation, movement of the hands, arms, body, and facial to simultaneously express the thoughts of the speaker. This paper implements static hand gesture recognition in recognizing the alphabetical sign from “A” to “Z”, number from “0” to “9”, and additional punctuation mark such as “Period”, “Question Mark”, and “Space”in Sistem Isyarat Bahasa Indonesia (SIBI). Hand gestures are obtained by evaluating the contour representation from image segmentation of the glove wore by user and then is classified using Artificial Neural Network based on the training model previously built from 100 images for each gesture. The accuracy rate of hand gesture translation is calculated to be 90%. Speech translation recognized NATO phonetic letter as the speech input for translation.
{"title":"Implementation of real-time static hand gesture recognition using artificial neural network","authors":"Rosalina, Lita Yusnita, N. Hadisukmana, R. B. Wahyu, Rusdianto Roestam, Yuyu Wahyu","doi":"10.21512/commit.v11i2.2282","DOIUrl":"https://doi.org/10.21512/commit.v11i2.2282","url":null,"abstract":"Sign language is a language that requires the combination of hand gesture, orientation, movement of the hands, arms, body, and facial to simultaneously express the thoughts of the speaker. This paper implements static hand gesture recognition in recognizing the alphabetical sign from “A” to “Z”, number from “0” to “9”, and additional punctuation mark such as “Period”, “Question Mark”, and “Space”in Sistem Isyarat Bahasa Indonesia (SIBI). Hand gestures are obtained by evaluating the contour representation from image segmentation of the glove wore by user and then is classified using Artificial Neural Network based on the training model previously built from 100 images for each gesture. The accuracy rate of hand gesture translation is calculated to be 90%. Speech translation recognized NATO phonetic letter as the speech input for translation.","PeriodicalId":351075,"journal":{"name":"2017 4th International Conference on Computer Applications and Information Processing Technology (CAIPT)","volume":"175 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133903352","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-08-08DOI: 10.1109/CAIPT.2017.8320699
I. Kurniastuti
In this paper we proposed a method to create application of baby's nutrition status using Macromedia Flash. The anthropometry is used as input of application. The anthropometry like age, gender, weight, height and head circumference. The proposed method consists of stage of literature study as a preparation stage, stage of making application as a crucial stage in this research, data retrieval stage to get data as input in application, and stage of application testing as a stage in which application was tested using data from data retrieval stage. Output of the application was normal, below normal or above normal. It can be said normal if input is in around standard of nutrition status, it can be said below normal if input is below standard of nutrition status and it can be said above normal if input is above standard of nutrition status. The accuracy of program was 100% based on similarity between output of application and standard of nutrition status from ministry of health.
{"title":"Application of baby's nutrition status using Macromedia Flash","authors":"I. Kurniastuti","doi":"10.1109/CAIPT.2017.8320699","DOIUrl":"https://doi.org/10.1109/CAIPT.2017.8320699","url":null,"abstract":"In this paper we proposed a method to create application of baby's nutrition status using Macromedia Flash. The anthropometry is used as input of application. The anthropometry like age, gender, weight, height and head circumference. The proposed method consists of stage of literature study as a preparation stage, stage of making application as a crucial stage in this research, data retrieval stage to get data as input in application, and stage of application testing as a stage in which application was tested using data from data retrieval stage. Output of the application was normal, below normal or above normal. It can be said normal if input is in around standard of nutrition status, it can be said below normal if input is below standard of nutrition status and it can be said above normal if input is above standard of nutrition status. The accuracy of program was 100% based on similarity between output of application and standard of nutrition status from ministry of health.","PeriodicalId":351075,"journal":{"name":"2017 4th International Conference on Computer Applications and Information Processing Technology (CAIPT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114927221","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-08-01DOI: 10.1109/CAIPT.2017.8320687
S. Eun, E. Jung, Dong-Kyun Park, T. Whangbo
In high-field magnetic resonance imaging (MRI), water-fat separation in the presence of B0 field inhomogeneity is important research. Various field map estimation techniques that use three-point multi-echo acquisitions have been developed for reliable water fat separation. Among the numerous techniques, iterative decomposition of water and fat with echo asymmetry and least squares estimation (IDEAL) has gained considerable popularity as an iterative method for acquiring high-quality water and fat images. However, due to the worsened B0 in homogeneity at high-field, IDEAL cannot adjust for meaningful field map estimation, particularly for a large field of view. Previously, to improve the robustness of this estimation, a region-growing (RG) technique was developed to take advantage of the 2D linear extrapolation procedure through the seed point set by the median value in the target object. There are some limitations with this approach, such as the dependence on the initial seed point, such as a number, intensity, and position of the seed point. In this work, we introduce a effective method called the improved Grid-fit method that does not need to consider parameters related with accuracy. As a result of the proposed method, we obtained a effective fat quantification result that can be applied in high-fields, with an average water residual rate of 7.2% higher than the existing method.
{"title":"Fat separation using grid fit method at high-field MRI","authors":"S. Eun, E. Jung, Dong-Kyun Park, T. Whangbo","doi":"10.1109/CAIPT.2017.8320687","DOIUrl":"https://doi.org/10.1109/CAIPT.2017.8320687","url":null,"abstract":"In high-field magnetic resonance imaging (MRI), water-fat separation in the presence of B0 field inhomogeneity is important research. Various field map estimation techniques that use three-point multi-echo acquisitions have been developed for reliable water fat separation. Among the numerous techniques, iterative decomposition of water and fat with echo asymmetry and least squares estimation (IDEAL) has gained considerable popularity as an iterative method for acquiring high-quality water and fat images. However, due to the worsened B0 in homogeneity at high-field, IDEAL cannot adjust for meaningful field map estimation, particularly for a large field of view. Previously, to improve the robustness of this estimation, a region-growing (RG) technique was developed to take advantage of the 2D linear extrapolation procedure through the seed point set by the median value in the target object. There are some limitations with this approach, such as the dependence on the initial seed point, such as a number, intensity, and position of the seed point. In this work, we introduce a effective method called the improved Grid-fit method that does not need to consider parameters related with accuracy. As a result of the proposed method, we obtained a effective fat quantification result that can be applied in high-fields, with an average water residual rate of 7.2% higher than the existing method.","PeriodicalId":351075,"journal":{"name":"2017 4th International Conference on Computer Applications and Information Processing Technology (CAIPT)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121091384","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-08-01DOI: 10.1109/CAIPT.2017.8320702
Aulia Essra, O. S. Sitompul, Benny Benyamin Nasution, R. Rahmat
Hierarchical Graph Neuron (HGN) is an extension of network-centric algorithm called Graph Neuron (GN), which is used to perform parallel distributed pattern recognition. In this research, HGN scheme is used to classify intrusion attacks in computer networks. Patterns of intrusion attacks are preprocessed in three steps: selecting attributes using information gain attribute evaluation, discretizing the selected attributes using entropy-based discretization supervised method, and selecting the training data using K-Means clustering algorithm. After the preprocessing stage, the HGN scheme is then deployed to classify intrusion attack using the KDD Cup 99 dataset. The results of the classification are measured in terms of accuracy rate, detection rate, false positive rate and true negative rate. The test result shows that the HGN scheme is promising and stable in classifying the intrusion attack patterns with accuracy rate reaches 96.27%, detection rate reaches 99.20%, true negative rate below 15.73%, and false positive rate as low as 0.80%.
分层图神经元(HGN)是对以网络为中心的图神经元(GN)算法的扩展，用于并行分布式模式识别。在本研究中，采用HGN方案对计算机网络中的入侵攻击进行分类。入侵攻击模式的预处理分为三个步骤:利用信息增益属性评估选择属性，利用基于熵的离散化监督方法对选择的属性进行离散化，利用K-Means聚类算法选择训练数据。预处理后，利用KDD Cup 99数据集部署HGN方案对入侵攻击进行分类。分类结果以准确率、检出率、假阳性率和真阴性率来衡量。测试结果表明，HGN方案在入侵攻击模式分类方面具有良好的前景和稳定性，准确率达到96.27%，检测率达到99.20%，真阴性率低于15.73%，假阳性率低至0.80%。
{"title":"Hierarchical graph neuron scheme in classifying intrusion attack","authors":"Aulia Essra, O. S. Sitompul, Benny Benyamin Nasution, R. Rahmat","doi":"10.1109/CAIPT.2017.8320702","DOIUrl":"https://doi.org/10.1109/CAIPT.2017.8320702","url":null,"abstract":"Hierarchical Graph Neuron (HGN) is an extension of network-centric algorithm called Graph Neuron (GN), which is used to perform parallel distributed pattern recognition. In this research, HGN scheme is used to classify intrusion attacks in computer networks. Patterns of intrusion attacks are preprocessed in three steps: selecting attributes using information gain attribute evaluation, discretizing the selected attributes using entropy-based discretization supervised method, and selecting the training data using K-Means clustering algorithm. After the preprocessing stage, the HGN scheme is then deployed to classify intrusion attack using the KDD Cup 99 dataset. The results of the classification are measured in terms of accuracy rate, detection rate, false positive rate and true negative rate. The test result shows that the HGN scheme is promising and stable in classifying the intrusion attack patterns with accuracy rate reaches 96.27%, detection rate reaches 99.20%, true negative rate below 15.73%, and false positive rate as low as 0.80%.","PeriodicalId":351075,"journal":{"name":"2017 4th International Conference on Computer Applications and Information Processing Technology (CAIPT)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122935709","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-08-01DOI: 10.1109/CAIPT.2017.8320680
A. E. Budianto, E. P. A. Yunus
In this paper, we try to optimize the best goats by using expert system. A farm to always be competitive in the face of market competition, is required to be able to provide effective and efficient services through the selection process and selection of livestock quickly but still do not rule out the accuracy of the best criteria of livestock to consumers. The purpose of this researcher is to build the best goat selection decision support system with topsis method as an option to determine some criteria with ideal solution. Technological developments can be utilized in the best selection of livestock, by building expert systems capable of handling livestock selection automatically and can save time and cost in selecting livestock. Based on the test results, the application of decision support system is useful to help and facilitate the selection of livestock, so that consumers can easily choice on the best livestock according to expectations based on predetermined criteria.
{"title":"Expert system to optimize the best goat selection using topsis: Decision support system","authors":"A. E. Budianto, E. P. A. Yunus","doi":"10.1109/CAIPT.2017.8320680","DOIUrl":"https://doi.org/10.1109/CAIPT.2017.8320680","url":null,"abstract":"In this paper, we try to optimize the best goats by using expert system. A farm to always be competitive in the face of market competition, is required to be able to provide effective and efficient services through the selection process and selection of livestock quickly but still do not rule out the accuracy of the best criteria of livestock to consumers. The purpose of this researcher is to build the best goat selection decision support system with topsis method as an option to determine some criteria with ideal solution. Technological developments can be utilized in the best selection of livestock, by building expert systems capable of handling livestock selection automatically and can save time and cost in selecting livestock. Based on the test results, the application of decision support system is useful to help and facilitate the selection of livestock, so that consumers can easily choice on the best livestock according to expectations based on predetermined criteria.","PeriodicalId":351075,"journal":{"name":"2017 4th International Conference on Computer Applications and Information Processing Technology (CAIPT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114455859","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-08-01DOI: 10.1109/CAIPT.2017.8320677
Yong-Ho Shin, Kuk-jin Yoon
When computing a depth map sequence of a stereo image sequence, the temporal consistency of computed depth maps is a very important factor along with the accuracy. In this paper, we propose a new similarity measure for spatiotemporal stereo matching aiming at producing temporally consistent depth maps from a stereo image sequence. To enforce the temporal consistency in a spatiotemporal similarity measure, we assign adaptive support weights to pixels in a spatiotemporal window and define the four-dimensional support region in consideration of the motion and depth variation along the time. In addition, we model the support weight to be less sensitive to illumination variation. The similarity is computed simply by comparing two support regions with computed support weights. The proposed similarity measure truly improves the performance of stereo matching both in the accuracy and in the consistency aspects.
{"title":"Adaptive spatiotemporal similarity measure for a consistent depth maps","authors":"Yong-Ho Shin, Kuk-jin Yoon","doi":"10.1109/CAIPT.2017.8320677","DOIUrl":"https://doi.org/10.1109/CAIPT.2017.8320677","url":null,"abstract":"When computing a depth map sequence of a stereo image sequence, the temporal consistency of computed depth maps is a very important factor along with the accuracy. In this paper, we propose a new similarity measure for spatiotemporal stereo matching aiming at producing temporally consistent depth maps from a stereo image sequence. To enforce the temporal consistency in a spatiotemporal similarity measure, we assign adaptive support weights to pixels in a spatiotemporal window and define the four-dimensional support region in consideration of the motion and depth variation along the time. In addition, we model the support weight to be less sensitive to illumination variation. The similarity is computed simply by comparing two support regions with computed support weights. The proposed similarity measure truly improves the performance of stereo matching both in the accuracy and in the consistency aspects.","PeriodicalId":351075,"journal":{"name":"2017 4th International Conference on Computer Applications and Information Processing Technology (CAIPT)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129012586","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-08-01DOI: 10.1109/CAIPT.2017.8320658
Woo-Seok Yang, M. Chun, Gun-Woo Jang, Jong-Hwan Baek, Sang-Hoon Kim
In this research, we developed a smart drone system based on quad copter with integrated object tracking algorithm for scene analysis. We tool advantage of theory of quad rotor flight and PID control for not only stable hovering but also stable image acquisition. For object tracking, we integrated color information and optical flow with nonlinear matched filter of spatial frequency domain. Furthermore, we proposed a solution for safer experiment environment configuration.
{"title":"A study on smart drone using quadcopter and object tracking techniques","authors":"Woo-Seok Yang, M. Chun, Gun-Woo Jang, Jong-Hwan Baek, Sang-Hoon Kim","doi":"10.1109/CAIPT.2017.8320658","DOIUrl":"https://doi.org/10.1109/CAIPT.2017.8320658","url":null,"abstract":"In this research, we developed a smart drone system based on quad copter with integrated object tracking algorithm for scene analysis. We tool advantage of theory of quad rotor flight and PID control for not only stable hovering but also stable image acquisition. For object tracking, we integrated color information and optical flow with nonlinear matched filter of spatial frequency domain. Furthermore, we proposed a solution for safer experiment environment configuration.","PeriodicalId":351075,"journal":{"name":"2017 4th International Conference on Computer Applications and Information Processing Technology (CAIPT)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124131421","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-08-01DOI: 10.1109/CAIPT.2017.8320673
Agung Cokro Prabowo, Rosmiati, I. S. Windiarti
Indonesian IT engineers need to have both hard and soft skills to be ready in global market competition in term of work force. Hard skills are the technical expertise related to their field of work. On the other hand, soft skills are also the important part of the engineers' capability including communication, creativity, adaptability, collaboration and leadership. The purpose of this paper is to develop theoretical review of how to educate Indonesian IT engineers to be ready to face global job market competition by the use of cross-cultural training program in the university in Indonesia. This study reports the results of a web-based survey of Indonesian expatriate engineers addressing their knowledge, experience and perceptions of working in multicultural working environment in some engineering projects. The output of this paper is a framework of cross-cultural training as the supplementary material in the university curriculum in engineering education in Indonesia.
{"title":"Cross-cultural training as part of policy and business strategies to prepare Indonesian IT engineers in global job market competition","authors":"Agung Cokro Prabowo, Rosmiati, I. S. Windiarti","doi":"10.1109/CAIPT.2017.8320673","DOIUrl":"https://doi.org/10.1109/CAIPT.2017.8320673","url":null,"abstract":"Indonesian IT engineers need to have both hard and soft skills to be ready in global market competition in term of work force. Hard skills are the technical expertise related to their field of work. On the other hand, soft skills are also the important part of the engineers' capability including communication, creativity, adaptability, collaboration and leadership. The purpose of this paper is to develop theoretical review of how to educate Indonesian IT engineers to be ready to face global job market competition by the use of cross-cultural training program in the university in Indonesia. This study reports the results of a web-based survey of Indonesian expatriate engineers addressing their knowledge, experience and perceptions of working in multicultural working environment in some engineering projects. The output of this paper is a framework of cross-cultural training as the supplementary material in the university curriculum in engineering education in Indonesia.","PeriodicalId":351075,"journal":{"name":"2017 4th International Conference on Computer Applications and Information Processing Technology (CAIPT)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126456117","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-08-01DOI: 10.1109/CAIPT.2017.8320747
Jun Yi, Ikjune Yoon, D. Noh
Recently, the use of wireless sensor networks to collect video data for environmental observation or monitoring has been increasing, but they are not suitable for transmitting large video data due to the limitation of node energy. Energy-harvesting node could be used to overcome this limitation, but the harvested energy is also limited. Therefore, an efficient energy utilization method is required to transmit a large amount of video data. This paper proposes a scheme to reduce the number of blackout nodes and increase the amount of collected data by selecting an appropriate video encoding method according to energy condition of the node in a solar-powered wireless sensor network. To collect data continuously regardless of day or night, this scheme allocates the amount of energy that can be used by time, and selects a coding with a high-compression ratio if the allocated amount is large, or a coding with a low-compression ratio if it is small. In this way, the blackouts of relay nodes are reduced and data can be transmitted continuously, which increases the amount of data arriving at the sink node. The simulation results verified confirmed that the proposed scheme prevented the energy exhaustion of the relay nodes and collected more data compared to using one coding only.
{"title":"Adaptive video coding selection scheme for solar-powered wireless video sensor networks","authors":"Jun Yi, Ikjune Yoon, D. Noh","doi":"10.1109/CAIPT.2017.8320747","DOIUrl":"https://doi.org/10.1109/CAIPT.2017.8320747","url":null,"abstract":"Recently, the use of wireless sensor networks to collect video data for environmental observation or monitoring has been increasing, but they are not suitable for transmitting large video data due to the limitation of node energy. Energy-harvesting node could be used to overcome this limitation, but the harvested energy is also limited. Therefore, an efficient energy utilization method is required to transmit a large amount of video data. This paper proposes a scheme to reduce the number of blackout nodes and increase the amount of collected data by selecting an appropriate video encoding method according to energy condition of the node in a solar-powered wireless sensor network. To collect data continuously regardless of day or night, this scheme allocates the amount of energy that can be used by time, and selects a coding with a high-compression ratio if the allocated amount is large, or a coding with a low-compression ratio if it is small. In this way, the blackouts of relay nodes are reduced and data can be transmitted continuously, which increases the amount of data arriving at the sink node. The simulation results verified confirmed that the proposed scheme prevented the energy exhaustion of the relay nodes and collected more data compared to using one coding only.","PeriodicalId":351075,"journal":{"name":"2017 4th International Conference on Computer Applications and Information Processing Technology (CAIPT)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127948738","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-08-01DOI: 10.1109/CAIPT.2017.8320724
Jihun Kim, Jonghee M. Youn
The rapidly increasing malware goes beyond personal security threats and has a negative effect on criminal society. To prevent these security threats, many anti-virus vendors and analysts are starving to more efficiently distinguish malicious behavior. In order to contribute to this, in this study, we try to detect malicious behavior by tracking the execution flow of binary code. Our method of tracking the execution flow of the binary code utilizing the BFS(Breath-First Search)algorithm advances static analysis based on binary code, but it can be a method combining the advantage of static analysis and the advantage of dynamic analysis. In addition to visualizing malicious behavior as a graph image based on APIs, it is possible to analyze more obviously malicious behavior.
{"title":"Malware behavior analysis using binary code tracking","authors":"Jihun Kim, Jonghee M. Youn","doi":"10.1109/CAIPT.2017.8320724","DOIUrl":"https://doi.org/10.1109/CAIPT.2017.8320724","url":null,"abstract":"The rapidly increasing malware goes beyond personal security threats and has a negative effect on criminal society. To prevent these security threats, many anti-virus vendors and analysts are starving to more efficiently distinguish malicious behavior. In order to contribute to this, in this study, we try to detect malicious behavior by tracking the execution flow of binary code. Our method of tracking the execution flow of the binary code utilizing the BFS(Breath-First Search)algorithm advances static analysis based on binary code, but it can be a method combining the advantage of static analysis and the advantage of dynamic analysis. In addition to visualizing malicious behavior as a graph image based on APIs, it is possible to analyze more obviously malicious behavior.","PeriodicalId":351075,"journal":{"name":"2017 4th International Conference on Computer Applications and Information Processing Technology (CAIPT)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132129209","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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