2018 International Conference on Cyber Security and Protection of Digital Services (Cyber Security)最新文献_第2页

OWASP Top 10 - Do Startups Care? OWASP前十名——创业公司关心吗?

2018 International Conference on Cyber Security and Protection of Digital Services (Cyber Security) Pub Date : 2018-06-01 DOI: 10.1109/CyberSecPODS.2018.8560666

H. Sohoel, M. Jaatun, C. Boyd

引用次数: 8

Combined and Robust SNOW-ZUC Algorithm Based on Chaotic System 基于混沌系统的组合鲁棒SNOW-ZUC算法

2018 International Conference on Cyber Security and Protection of Digital Services (Cyber Security) Pub Date : 2018-06-01 DOI: 10.1109/CyberSecPODS.2018.8560677

Mahdi Madani, C. Tanougast

引用次数: 9

Cloud-based Real-time Network Intrusion Detection Using Deep Learning 基于深度学习的云实时网络入侵检测

2018 International Conference on Cyber Security and Protection of Digital Services (Cyber Security) Pub Date : 2018-06-01 DOI: 10.1109/CyberSecPODS.2018.8560674

Santhosh Parampottupadam, Arghir-Nicolae Moldovan

引用次数: 19

Infection, Self-reproduction and Overinfection in Ransomware: The Case of TeslaCrypt 勒索软件的感染、自我复制和过度感染:以TeslaCrypt为例

2018 International Conference on Cyber Security and Protection of Digital Services (Cyber Security) Pub Date : 2018-06-01 DOI: 10.1109/CyberSecPODS.2018.8560670

Yassine Lemmou, E. M. Souidi

引用次数: 8

Searching for crime on the web: Legal and Ethical perspectives 在网上搜索犯罪:法律和伦理的观点

2018 International Conference on Cyber Security and Protection of Digital Services (Cyber Security) Pub Date : 2018-06-01 DOI: 10.1109/CyberSecPODS.2018.8560689

Dimitrios Kavallieros, Christina Chalanouli, Georgios Kokkinis, Anastasios Panathanasiou, Efthimios Lissaris, G. Leventakis, G. Giataganas, Georgios Germanos

引用次数: 1

Lightweight Distributed Attack Detection and Prevention for the Safe Internet of Things 面向安全物联网的轻量级分布式攻击检测与防范

2018 International Conference on Cyber Security and Protection of Digital Services (Cyber Security) Pub Date : 2018-06-01 DOI: 10.1109/CyberSecPODS.2018.8560679

V. Eliseev, O. Eliseeva

引用次数: 0

An Approach to Detect and Prevent Cybercrime in Large Complex Networks 大型复杂网络中网络犯罪的检测与预防方法

2018 International Conference on Cyber Security and Protection of Digital Services (Cyber Security) Pub Date : 2018-06-01 DOI: 10.1109/CyberSecPODS.2018.8560687

André Sørensen, Maxime Jérôme Remy, Nicolaj Kjettrup, R. Mahmoud, J. Pedersen

{"title":"An Approach to Detect and Prevent Cybercrime in Large Complex Networks","authors":"André Sørensen, Maxime Jérôme Remy, Nicolaj Kjettrup, R. Mahmoud, J. Pedersen","doi":"10.1109/CyberSecPODS.2018.8560687","DOIUrl":"https://doi.org/10.1109/CyberSecPODS.2018.8560687","url":null,"abstract":"Recently, the Danish defense department announced that research institutions are prominent targets for cybercrime. To better protect these organizations, an approach to prevent and detect cybercrime in large complex computer networks is needed. This paper contributes by a proof of concept of such an approach, based on a combination of Penetration test (Pen test) and Domain Name System (DNS) analysis. Pen test is a method to assess a network's current security state, by detecting vulnerabilities and misconfigurations before they are being abused. On the other hand, DNS traffic analysis can be used to detect ongoing cybercriminal/suspicious activities. The combination of the Pen test and DNS analysis can give an administrator a crucial overview of the vulnerabilities present in the system as well as already compromised parts. The methods were tested on the network of Aalborg University, and they were both able to identify ongoing cybercrime or vulnerabilities. While the feasibility was demonstrated, further developments are needed before it can be implemented on a larger scale.","PeriodicalId":387054,"journal":{"name":"2018 International Conference on Cyber Security and Protection of Digital Services (Cyber Security)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115869974","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

Dynamic Opcode Analysis of Ransomware 勒索软件的动态操作码分析

2018 International Conference on Cyber Security and Protection of Digital Services (Cyber Security) Pub Date : 2018-06-01 DOI: 10.1109/CyberSecPODS.2018.8560667

Domhnall Carlin, Philip O'Kane, S. Sezer

{"title":"Dynamic Opcode Analysis of Ransomware","authors":"Domhnall Carlin, Philip O'Kane, S. Sezer","doi":"10.1109/CyberSecPODS.2018.8560667","DOIUrl":"https://doi.org/10.1109/CyberSecPODS.2018.8560667","url":null,"abstract":"The explosion of ransomware in recent years has served as a costly reminder that the malware threatscape has moved from that of socially-inept hobbyists to career criminals. This paper investigates the efficacy of dynamic opcode analysis in distinguishing cryptographic ransomware from benignware, and presents several novel contributions. Firstly, a new dataset of cryptoransomware dynamic run-traces, the largest of its kind in the literature. We release this to the wider research community to foster further research in the field. Our second novel contribution demonstrates that a short runlength of 32k opcodes can provide highly accurate detection of ransomware (99.56%) compared to benign software. Third, our model offers a distinct advantage over other models in the literature, in that it can detect a form of benign encryption (i.e. file zipping) with 100% accuracy against not only ransomware, but also the non-encrypting benignware in our dataset. The research presented here demonstrates that dynamic opcode tracing is capable of detecting ransomware in comparable times to static analysis, without being thwarted by obfuscation tactics.","PeriodicalId":387054,"journal":{"name":"2018 International Conference on Cyber Security and Protection of Digital Services (Cyber Security)","volume":"1368 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121064829","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

Unsupervised Approach for Detecting Low Rate Attacks on Network Traffic with Autoencoder 基于自编码器的网络流量低速率攻击无监督检测方法

2018 International Conference on Cyber Security and Protection of Digital Services (Cyber Security) Pub Date : 2018-06-01 DOI: 10.1109/CyberSecPODS.2018.8560678

B. Pratomo, P. Burnap, George Theodorakopoulos

{"title":"Unsupervised Approach for Detecting Low Rate Attacks on Network Traffic with Autoencoder","authors":"B. Pratomo, P. Burnap, George Theodorakopoulos","doi":"10.1109/CyberSecPODS.2018.8560678","DOIUrl":"https://doi.org/10.1109/CyberSecPODS.2018.8560678","url":null,"abstract":"Most approaches to network intrusion detection look only at the header part of network packets. These approaches are able to detect high-rate attacks, such as Denial of Service or probing, with high degrees of accuracy. However, it remains to be seen whether they are also able to detect more subtle attacks, such as when adversaries try to exploit a vulnerability or plant a backdoor. In these cases, the attributes of network packets are usually very similar to the legitimate traffic which presents a limitation for header-only intrusion detection methods. Such attacks present an increasing problem to network security, especially given the rise of Internet of Things (IoT) and the rapidly increasing number of devices that can be exploited through low-intensity attacks. To address this problem we propose the use of the Autoencoder method for network intrusion detection. Autoencoder is a deep learning architecture that has the capability to identify outliers in a dataset. Thus it does not need labelled datasets which contain both legitimate and malicious traffic for training purposes. Through our experiments, we show that the proposed approach was able to detect 100% of low rate attack traffic with an average false positive rate of 8.01%. To demonstrate the improvement over the state of the art we have compared our results to a number of other similar works and our proposed method gave at least 32.81% better in detection rate.","PeriodicalId":387054,"journal":{"name":"2018 International Conference on Cyber Security and Protection of Digital Services (Cyber Security)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121328521","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: 20

A Systems Security Approach for Requirements Analysis of Complex Cyber-Physical Systems 复杂信息物理系统需求分析的系统安全方法

2018 International Conference on Cyber Security and Protection of Digital Services (Cyber Security) Pub Date : 2018-06-01 DOI: 10.1109/CyberSecPODS.2018.8560682

M. Span, L. Mailloux, M. Grimaila, William Young

{"title":"A Systems Security Approach for Requirements Analysis of Complex Cyber-Physical Systems","authors":"M. Span, L. Mailloux, M. Grimaila, William Young","doi":"10.1109/CyberSecPODS.2018.8560682","DOIUrl":"https://doi.org/10.1109/CyberSecPODS.2018.8560682","url":null,"abstract":"Today's highly interconnected and technology reliant environment places greater emphasis on the need for dependably secure systems. This work addresses this problem by detailing a systems security analysis approach for understanding and eliciting security requirements for complex cyber-physical systems. First, a readily understandable description of key architectural analysis definitions and desirable characteristics is provided along with a survey of commonly used security architecture analysis approaches. Next, a tailored version of the System-Theoretic Process Analysis approach for Security (STPA-Sec) is detailed in three phases which supports the development of functional-level security requirements, architectural-level engineering considerations, and design-level security criteria. In particular, these three phases are aligned with the systems and software engineering processes defined in the security processes of NIST SP 800–160. Lastly, this work is important for advancing the science of systems security by providing a viable systems security analysis approach for eliciting, defining, and analyzing traceable security, safety, and resiliency requirements which support evaluation criteria that can be designed-for, built-to, and verified with confidence.","PeriodicalId":387054,"journal":{"name":"2018 International Conference on Cyber Security and Protection of Digital Services (Cyber Security)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129561853","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