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2018 International Conference on Software Security and Assurance (ICSSA) Pub Date : 2018-07-01 DOI: 10.1109/icssa45270.2018.00003
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引用次数: 0
[Title page i] [标题页i]
2018 International Conference on Software Security and Assurance (ICSSA) Pub Date : 2018-07-01 DOI: 10.1109/icssa45270.2018.00001
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引用次数: 0
An Attack Vector for IoT Networks 物联网网络的攻击媒介
2018 International Conference on Software Security and Assurance (ICSSA) Pub Date : 2018-07-01 DOI: 10.1109/ICSSA45270.2018.00019
Syed S. Rizvi, Ryan Pipetti, Nicholas McIntyre, Jonathan Todd
{"title":"An Attack Vector for IoT Networks","authors":"Syed S. Rizvi, Ryan Pipetti, Nicholas McIntyre, Jonathan Todd","doi":"10.1109/ICSSA45270.2018.00019","DOIUrl":"https://doi.org/10.1109/ICSSA45270.2018.00019","url":null,"abstract":"The advent of the twenty-first century has seen a myriad of amazing technological advancements. The Internet of Things (IoT) is a prime example of technological capabilities at its finest. The IoT is a series of interconnected devices capable of sending and receiving data over existing network infrastructure, but why does this matter? Technology is becoming a conventional commodity, while the uses are endless, technological advancement constitutes a very serious risk. Any device that is connected to the Internet poses a heightened security risk. These risks have the potential of compromising the device and its users. Therefore, the understanding of device-level security is critical to protect the users from various security threats. To provide a holistic view of IoT security, the investigated devices are broken down with respect to different domains (e.g., healthcare, commerce, and home). Specifically, this paper presents a survey of frequently used devices with a common vulnerability scoring system (CVSS) for each investigated IoT domain. This will be an attempt to identify the pivotal device vulnerabilities and determine which attack vectors are predominately exploited in IoT networks.","PeriodicalId":223442,"journal":{"name":"2018 International Conference on Software Security and Assurance (ICSSA)","volume":"2013 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132075757","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}
引用次数: 2
Preventing Bitcoin Selfish Mining Using Transaction Creation Time 利用交易创建时间防止比特币自私挖矿
2018 International Conference on Software Security and Assurance (ICSSA) Pub Date : 2018-07-01 DOI: 10.1109/ICSSA45270.2018.00014
Jihye Lee, Yoonjeong Kim
{"title":"Preventing Bitcoin Selfish Mining Using Transaction Creation Time","authors":"Jihye Lee, Yoonjeong Kim","doi":"10.1109/ICSSA45270.2018.00014","DOIUrl":"https://doi.org/10.1109/ICSSA45270.2018.00014","url":null,"abstract":"Bitcoin is a cryptocurrency that is based on a blockchain technology. All transactions in bitcoin recorded in the blockchain and the transactions are validated through mining. When mining, honest miners are rewarded in proportion to their computing power. However, it has been proven that selfish mining can get more mining rewards beyond computing power. Selfish mining intentionally makes block fork of the blockchain and wastes the computing power of honest miners. In this paper, we analyze selfish mining and existing countermeasures, and propose a new method to prevent selfish mining by adding the transaction creation time to the transaction data structure. The proposed method is the highest threshold compared to existing methods, which is 33% threshold required for successful selfish mining. The threshold is also the most optimized result with the probability of an honest miner mining in selfish mining pools to zero.","PeriodicalId":223442,"journal":{"name":"2018 International Conference on Software Security and Assurance (ICSSA)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132943283","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}
引用次数: 5
Android Malware Detection Using Feature Selections and Random Forest Android恶意软件检测使用特征选择和随机森林
2018 International Conference on Software Security and Assurance (ICSSA) Pub Date : 2018-07-01 DOI: 10.1109/ICSSA45270.2018.00023
Taehoon Eom, Heesu Kim, SeongMo An, Jong Sou Park, Dong Seong Kim
{"title":"Android Malware Detection Using Feature Selections and Random Forest","authors":"Taehoon Eom, Heesu Kim, SeongMo An, Jong Sou Park, Dong Seong Kim","doi":"10.1109/ICSSA45270.2018.00023","DOIUrl":"https://doi.org/10.1109/ICSSA45270.2018.00023","url":null,"abstract":"Malicious software (Malware) applications in Android ecosystem is one of the critical issues. Manual detection of malware is not cost-effective and cannot keep up with the fast evolution of malware development in Android. A machine learning based malware detection has attempted to automate the detection of malware in Android. In this paper, we present new Android malware detection methods. The main idea of our proposed approach is to use three different feature selection methods before malware detection model using a machine learning algorithm is constructed. We used both Malware Genome Project dataset and our own crawled dataset to show the effectiveness of the proposed methods.","PeriodicalId":223442,"journal":{"name":"2018 International Conference on Software Security and Assurance (ICSSA)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127073345","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}
引用次数: 0
A Case Study: BDA Model for Standalone Radar System (Work-in-Progress) 案例研究:独立雷达系统的BDA模型(在研)
2018 International Conference on Software Security and Assurance (ICSSA) Pub Date : 2018-07-01 DOI: 10.1109/ICSSA45270.2018.00020
Seungcheol Choi, Y. Kim, Donghwa Kim, Oh-Jin Kwon, Joonhyung Cho
{"title":"A Case Study: BDA Model for Standalone Radar System (Work-in-Progress)","authors":"Seungcheol Choi, Y. Kim, Donghwa Kim, Oh-Jin Kwon, Joonhyung Cho","doi":"10.1109/ICSSA45270.2018.00020","DOIUrl":"https://doi.org/10.1109/ICSSA45270.2018.00020","url":null,"abstract":"In this paper, we propose a basic battlefield damage assessment (BDA) model for evaluating the damage to electronic warfare systems in cyber warfare and study a case which applies the proposed BDA model through a scenario assuming enemy cyber-attacks against a standalone Radar system.","PeriodicalId":223442,"journal":{"name":"2018 International Conference on Software Security and Assurance (ICSSA)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123644885","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}
引用次数: 1
The Image Forensics Analysis of JPEG Image Manipulation (Lightning Talk) JPEG图像处理的图像取证分析(闪电讲座)
2018 International Conference on Software Security and Assurance (ICSSA) Pub Date : 2018-07-01 DOI: 10.1109/ICSSA45270.2018.00029
Seung-Ju Cha, Uijeong Kang, Eun-Jung Choi
{"title":"The Image Forensics Analysis of JPEG Image Manipulation (Lightning Talk)","authors":"Seung-Ju Cha, Uijeong Kang, Eun-Jung Choi","doi":"10.1109/ICSSA45270.2018.00029","DOIUrl":"https://doi.org/10.1109/ICSSA45270.2018.00029","url":null,"abstract":"We use pictures as evidence. It is increasingly important to detect the manipulated areas of digital images. But we also face fabricated photographs to distort it. As the days go by, the fabricated image becomes more sophisticated and invisible. Many people have tried to improve image forensics technology to distinguish this fabricated images. In this paper, We investigate how to detect manipulated areas of a digital image like JPEG image format that used lossy compression. We use the features of the lossy compression to detect the manipulated image by the error level analysis(ELA) that is the analysis digital data such as JPEG format. And we're going to show that the Error Level Analysis(ELA) can work as image forensics. Through this analysis, we will be able to better judge manipulated images.","PeriodicalId":223442,"journal":{"name":"2018 International Conference on Software Security and Assurance (ICSSA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128847454","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}
引用次数: 1
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