2018 International Conference on Software Security and Assurance (ICSSA)最新文献_第2页

Ignore the Noise: Using Autoencoders against Adversarial Attacks in Reinforcement Learning (Lightning Talk) 忽略噪音:在强化学习中使用自编码器对抗对抗性攻击(闪电演讲)

2018 International Conference on Software Security and Assurance (ICSSA) Pub Date : 2018-07-01 DOI: 10.1109/ICSSA45270.2018.00028

William Aiken, Hyoungshick Kim

引用次数: 0

Dynamic Internet of Things Malware Detection Using Machine Learning (Work-in-Progress) 使用机器学习的动态物联网恶意软件检测(正在进行中)

2018 International Conference on Software Security and Assurance (ICSSA) Pub Date : 2018-07-01 DOI: 10.1109/ICSSA45270.2018.00025

Jonathan Myers, T. Oh, William B. Crowe, Ohan Filbach, W. McDonnell, T. Ajmera, Young Ho Kim, J. Kim

引用次数: 1

Conference Organizers 会议组织者

2018 International Conference on Software Security and Assurance (ICSSA) Pub Date : 2018-07-01 DOI: 10.1109/icssa45270.2018.00007

引用次数: 0

Towards Eliciting and Analyzing Security Requirements Using Ontologies through Use Case Scenarios (Work-in-Progress) 通过用例场景使用本体来引出和分析安全需求(正在进行中)

2018 International Conference on Software Security and Assurance (ICSSA) Pub Date : 2018-07-01 DOI: 10.1109/ICSSA45270.2018.00011

Omar Ochoa, Jessica Steinmann, Yevgeniy Lischuk

引用次数: 2

A Comparison of Online JavaScript Obfuscators 在线JavaScript混淆器的比较

2018 International Conference on Software Security and Assurance (ICSSA) Pub Date : 2018-07-01 DOI: 10.1109/ICSSA45270.2018.00012

Sampsa Rauti, V. Leppänen

引用次数: 1

Detecting Cryptography through IR Visualization 通过红外可视化检测密码

2018 International Conference on Software Security and Assurance (ICSSA) Pub Date : 2018-07-01 DOI: 10.1109/ICSSA45270.2018.00015

Patrick Kochberger, Florian Seitl

引用次数: 0

[Title page iii] [标题页iii]

2018 International Conference on Software Security and Assurance (ICSSA) Pub Date : 2018-07-01 DOI: 10.1109/icssa45270.2018.00002

引用次数: 0

Integrating Security in Cloud Application Development Cycle 在云应用开发周期中集成安全

2018 International Conference on Software Security and Assurance (ICSSA) Pub Date : 2018-07-01 DOI: 10.1109/ICSSA45270.2018.00013

Marwa A. Elsayed, Mohammad Zulkernine

{"title":"Integrating Security in Cloud Application Development Cycle","authors":"Marwa A. Elsayed, Mohammad Zulkernine","doi":"10.1109/ICSSA45270.2018.00013","DOIUrl":"https://doi.org/10.1109/ICSSA45270.2018.00013","url":null,"abstract":"Nowadays, more and more business and individuals tune to Software-as-a-Service (SaaS) applications to rapidly access various software capabilities through the Internet. The more SaaS adoption evolves, the more software service providers compete for fast development to cope with the market pace. This trend pushes security after functionality-needs in the priority list. This, in turn, results in delivering applications with potential security risk. The risk is further elevated due to the lack of visibility, control, and regulatory enforcements over consumers' data associated with such applications. Motivated by the raised necessity to consider security-needs at the same priority as functionality-needs, this paper proposes a comprehensive platform to interweave security activities and services from inception through deployment and beyond. Such activities and services are based on information flow control. The platform specifically envisions these activities to devote security into every phase of the development lifecycle of SaaS applications and offer different style of defenses as security services. It promotes for shared security responsibility to gain twofold benefits: a) it helps service providers to protect their SaaS applications from prevalent security threats; b) it enables SaaS consumers to choose a protected application to process their sensitive data with a trust in its security.","PeriodicalId":223442,"journal":{"name":"2018 International Conference on Software Security and Assurance (ICSSA)","volume":"78 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":"115762825","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

HNF Implementation Strategy Analysis for Lattice Cryptography (Lightning Talk) 格密码学的HNF实现策略分析(闪电演讲)

2018 International Conference on Software Security and Assurance (ICSSA) Pub Date : 2018-07-01 DOI: 10.1109/ICSSA45270.2018.00018

Yoonjeong Kim, Hye-Jung Yun, Seongan Lim

引用次数: 0

An Adaptive Dataset for the Evaluation of Android Malware Detection Techniques 一种评估Android恶意软件检测技术的自适应数据集

2018 International Conference on Software Security and Assurance (ICSSA) Pub Date : 2018-07-01 DOI: 10.1109/ICSSA45270.2018.00024

Omar Hreirati, Shahrear Iqbal, Mohammad Zulkernine

{"title":"An Adaptive Dataset for the Evaluation of Android Malware Detection Techniques","authors":"Omar Hreirati, Shahrear Iqbal, Mohammad Zulkernine","doi":"10.1109/ICSSA45270.2018.00024","DOIUrl":"https://doi.org/10.1109/ICSSA45270.2018.00024","url":null,"abstract":"Android is currently the leading mobile operating system in the world. The huge number of Android devices attracts developers to create applications for it. However, it also attracts attackers that collect sensitive data or make money. This problem has led many researchers to propose malware detection systems and custom versions of Android that can help users against malicious activities. Evaluating these systems is a crucial part of malware prevention research. However, recent datasets that cover different kinds of benign and malicious applications to evaluate the malware detection techniques are often not available. With thousands of newly released applications every day and different new malicious activities discovered, it is difficult to keep malicious application datasets up to date. This paper introduces a recent and adaptive dataset that includes 5,000 applications from different malware categories that can be used by the research community. The applications are selected from more than 5 million applications. To show how the dataset can be used, we deploy a popular malware analysis platform and generate detailed reports on all the applications in an automated way. We also provide the steps to update the dataset and perform the analysis automatically on the updated set of samples. We believe that the adaptiveness of the dataset and the automatic analysis process will help researchers save time in preparing their datasets and focus more on the detection techniques.","PeriodicalId":223442,"journal":{"name":"2018 International Conference on Software Security and Assurance (ICSSA)","volume":"42 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":"114700426","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