2013 43rd Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN)最新文献_第3页

Increasing the trustworthiness of commodity hardware through software 通过软件提高商品硬件的可信度

2013 43rd Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN) Pub Date : 2013-06-24 DOI: 10.1109/DSN.2013.6575328

Kevin Elphinstone, Yanyan Shen

引用次数: 4

Network traffic anomaly detection based on growing hierarchical SOM 基于增长分层SOM的网络流量异常检测

2013 43rd Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN) Pub Date : 2013-06-24 DOI: 10.1109/DSN.2013.6575338

Shin-Ying Huang, Yennun Huang

{"title":"Network traffic anomaly detection based on growing hierarchical SOM","authors":"Shin-Ying Huang, Yennun Huang","doi":"10.1109/DSN.2013.6575338","DOIUrl":"https://doi.org/10.1109/DSN.2013.6575338","url":null,"abstract":"Network anomaly detection aims to detect patterns in a given network traffic data that do not conform to an established normal behavior. Distinguishing different anomaly patterns from large amount of data can be a challenge, let alone visualizing them in a comparative perspective. Recently, the unsupervised learning method such as the K-means [3], self-organizing map (SOM) [2], and growing hierarchical self-organizing map (GHSOM) [1] have been shown to be able to facilitate network anomaly detection [4][5]. However, there is no study addressing both mining and detecting task. This study leverages the advantage of GHSOM to analyze the network traffic data and visualize the distribution of attack patterns with hierarchical relationship. In the mining stage, the geometric distances between each pattern and its descriptive information are revealed in the topological space. The density and the sample size of each node can help to detect anomalous network traffic. In the detecting stage, this study extends the traditional GHSOM and uses the support vector machine (SVM) [6] to classify network traffic data into the predefined categories. The proposed approach achieves (1) help understand the behaviors of anomalous network traffic data (2) provide effective classification rule to facilitate network anomaly detection and (3) accumulate network anomaly detection knowledge for both mining and detecting purpose. The public dataset and the private dataset are used to evaluate the proposed approach. The expected result is to confirm that the proposed approach can help understand network traffic data, and the detecting mechanism is effective for identifying anomalous behavior.","PeriodicalId":163407,"journal":{"name":"2013 43rd Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN)","volume":"119 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123759709","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: 35

Availability study on cloud computing environments: Live migration as a rejuvenation mechanism 云计算环境的可用性研究:动态迁移作为一种恢复机制

2013 43rd Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN) Pub Date : 2013-06-24 DOI: 10.1109/DSN.2013.6575322

M. Melo, P. Maciel, J. Araujo, Rúbens de Souza Matos Júnior, C. Araújo

引用次数: 73

Evasive bots masquerading as human beings on the web 在网络上伪装成人类的逃避机器人

2013 43rd Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN) Pub Date : 2013-06-24 DOI: 10.1109/DSN.2013.6575366

Jinghe Jin, A. Offutt, Nan Zheng, Feng Mao, Aaron Koehl, Haining Wang

{"title":"Evasive bots masquerading as human beings on the web","authors":"Jinghe Jin, A. Offutt, Nan Zheng, Feng Mao, Aaron Koehl, Haining Wang","doi":"10.1109/DSN.2013.6575366","DOIUrl":"https://doi.org/10.1109/DSN.2013.6575366","url":null,"abstract":"Web bots such as crawlers are widely used to automate various online tasks over the Internet. In addition to the conventional approach of human interactive proofs such as CAPTCHAs, a more recent approach of human observational proofs (HOP) has been developed to automatically distinguish web bots from human users. Its design rationale is that web bots behave intrinsically differently from human beings, allowing them to be detected. This paper escalates the battle against web bots by exploring the limits of current HOP-based bot detection systems. We develop an evasive web bot system based on human behavioral patterns. Then we prototype a general web bot framework and a set of flexible de-classifier plugins, primarily based on application-level event evasion. We further abstract and define a set of benchmarks for measuring our system's evasion performance on contemporary web applications, including social network sites. Our results show that the proposed evasive system can effectively mimic human behaviors and evade detectors by achieving high similarities between human users and evasive bots.","PeriodicalId":163407,"journal":{"name":"2013 43rd Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133180092","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: 15

Generative software-based memory error detection and correction for operating system data structures 基于生成软件的操作系统数据结构内存错误检测与校正

2013 43rd Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN) Pub Date : 2013-06-24 DOI: 10.1109/DSN.2013.6575308

C. Borchert, Horst Schirmeier, O. Spinczyk

引用次数: 42

Towards SDN enabled network control delegation in clouds 在云中实现SDN网络控制委派

2013 43rd Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN) Pub Date : 2013-06-24 DOI: 10.1109/DSN.2013.6575320

Muhammad Salman Malik, Mirko Montanari, J. Huh, R. Bobba, R. Campbell

引用次数: 16

Complementing static and dynamic analysis approaches for better network defense 补充静态和动态分析方法，提高网络防御能力

2013 43rd Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN) Pub Date : 2013-06-24 DOI: 10.1109/DSN.2013.6575334

H. Pareek, N. S. C. Babu

引用次数: 0

Addressing memory exhaustion failures in Virtual Machines in a cloud environment 解决云环境中虚拟机的内存耗尽故障

2013 43rd Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN) Pub Date : 2013-06-24 DOI: 10.1109/DSN.2013.6575330

J. A. Molina, Shivakant Mishra

引用次数: 2

Operating SECDED-based caches at ultra-low voltage with FLAIR 使用FLAIR在超低电压下操作基于秒的缓存

2013 43rd Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN) Pub Date : 2013-06-24 DOI: 10.1109/DSN.2013.6575314

Moinuddin K. Qureshi, Zeshan A. Chishti

引用次数: 36

Fitting second-order acyclic Marked Markovian Arrival Processes 二阶无环标记马尔可夫到达过程的拟合

2013 43rd Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN) Pub Date : 2013-06-24 DOI: 10.1109/DSN.2013.6575347

Andrea Sansottera, G. Casale, P. Cremonesi

引用次数: 2