2014 Asia-Pacific Conference on Computer Aided System Engineering (APCASE)最新文献_第3页

Improvizmg the public key infrastructure to build trust architecture for VANET by using short-time certificate management and Merkle Signature Scheme 利用短时证书管理和默克尔签名方案对公钥基础设施进行改进，构建VANET的信任体系结构

2014 Asia-Pacific Conference on Computer Aided System Engineering (APCASE) Pub Date : 2014-10-16 DOI: 10.1109/APCASE.2014.6924489

S. Mallissery, M. M. Manohara Pai, A. Smitha, R. Pai, J. Mouzna

引用次数: 4

Digital multimedia archiving based on optimization steganography system 基于优化隐写系统的数字多媒体归档

2014 Asia-Pacific Conference on Computer Aided System Engineering (APCASE) Pub Date : 2014-10-16 DOI: 10.1109/APCASE.2014.6924476

Raniyah Wazirali, Z. Chaczko, Anup Kale

引用次数: 11

Acceptance in the deployment of blended learning as a learning resource in information technology and computer science program, Brawijaya university 在信息技术和计算机科学课程中使用混合学习作为学习资源的接受度，布拉维贾亚大学

2014 Asia-Pacific Conference on Computer Aided System Engineering (APCASE) Pub Date : 2014-10-16 DOI: 10.1109/APCASE.2014.6924486

F. A. Bachtiar, Aditya Rachmadi, F. Pradana

引用次数: 18

Evaluation of traffic generators over a 40Gbps link 评估40Gbps链路上的流量生成器

2014 Asia-Pacific Conference on Computer Aided System Engineering (APCASE) Pub Date : 2014-10-16 DOI: 10.1109/APCASE.2014.6924469

Shalvi Srivastava, Sweta Anmulwar, A. Sapkal, Tarun Batra, A. Gupta, Vinodh Kumar

引用次数: 6

Detecting and preventing DDoS attacks in botnets by the help of self triggered black holes 利用自触发黑洞检测和防范僵尸网络中的DDoS攻击

2014 Asia-Pacific Conference on Computer Aided System Engineering (APCASE) Pub Date : 2014-10-16 DOI: 10.1109/APCASE.2014.6924468

Amirmohammad Sadeghian, M. Zamani

{"title":"Detecting and preventing DDoS attacks in botnets by the help of self triggered black holes","authors":"Amirmohammad Sadeghian, M. Zamani","doi":"10.1109/APCASE.2014.6924468","DOIUrl":"https://doi.org/10.1109/APCASE.2014.6924468","url":null,"abstract":"Among various types of computer threats, botnet is the most serious one against cyber security as they provide several illegal activities such as denial of service attacks, spamming, click fraud and other type of espionage activities. A botnet is a network of infected computers called bots which are under the control of one person known as Botmaster. Botmaster will have full control over the compromised machines from the command and control (C&C) channels, which allow Botmaster to update and add new features to the botnet. Distributed Denial of Service is one of deadliest attacks in history of network security which is take place by botnets. Until now many different solutions against this attack are proposed. One of these techniques is the Remote Triggered black hole filtering for stopping DDoS attacks by botnets. The main drawback of this technique is that the trigger is located at the victim premises and in case of an attack the network between trigger and routers will be saturated by attack traffic. Therefore the trigger cannot effectively communicate with the router to ask them to stop the traffic from the source IP. This paper proposes an improved framework to do the black hole filtering on the edge of internet service provider without need of the trigger (Self Triggered). The most tangible improvements in our framework are stopping DDoS attacks before entering into victim premises, ease of tracking and reporting the compromised machines for further cleanings.","PeriodicalId":118511,"journal":{"name":"2014 Asia-Pacific Conference on Computer Aided System Engineering (APCASE)","volume":"160 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132485385","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: 12

A cloud platform for distributed spectrum sensing 分布式频谱感知云平台

2014 Asia-Pacific Conference on Computer Aided System Engineering (APCASE) Pub Date : 2014-10-16 DOI: 10.1109/APCASE.2014.6924462

Zhenghua Lv, H. Meng, Tianyu Zhang

引用次数: 0

SKOSYN: Simple Knowledge Organization System for synonym search on content management system SKOSYN:用于内容管理系统中同义词搜索的简单知识组织系统

2014 Asia-Pacific Conference on Computer Aided System Engineering (APCASE) Pub Date : 2014-10-16 DOI: 10.1109/APCASE.2014.6924466

Novianti, Hargyo Tri, Nugroho I

引用次数: 1

Simulation-based capacity analysis for a future airport 基于模拟的未来机场容量分析

2014 Asia-Pacific Conference on Computer Aided System Engineering (APCASE) Pub Date : 2014-10-16 DOI: 10.1109/APCASE.2014.6924479

M. Mota, P. Scala, Geert Boosten

引用次数: 8

Audio detection (Audition): Android based sound detection application for hearing-impaired using AdaBoostM1 classifier with REPTree weaklearner 音频检测(Audition):基于Android的听障人士声音检测应用，使用AdaBoostM1分类器和REPTree弱学习器

2014 Asia-Pacific Conference on Computer Aided System Engineering (APCASE) Pub Date : 2014-02-01 DOI: 10.1109/APCASE.2014.6924487

Ayu Indah Shekar Melati Ayu, K. Karyono

{"title":"Audio detection (Audition): Android based sound detection application for hearing-impaired using AdaBoostM1 classifier with REPTree weaklearner","authors":"Ayu Indah Shekar Melati Ayu, K. Karyono","doi":"10.1109/APCASE.2014.6924487","DOIUrl":"https://doi.org/10.1109/APCASE.2014.6924487","url":null,"abstract":"AudiTion is an application that will help the hearing-impaired people to detect sound around them and to recognize the sound. The algorithms used in this application for Machine Learning are AdaBoostM1 functioning as a classifier and REPTree as weak learner, and it's built for Android operating system. Machine Learning is a study of computer algorithms which can improve its learning ability automatically through experience. AdaBoostM1 is one of the algorithms with Boosting method. Boosting uses all instances in each repetition, but keeping the load on any instance in the training set. REPTree is a fast decision tree learner which builds a decision/regression tree using information gain as the splitting criterion and prunes it using reduced-error pruning. Testing processes are done in four environment conditions to determine the sound prediction accuracy level. The four conditions are environments with low and high noise, far and near sound sources. AudiTion has two sound databases, the first database is indoor sounds and the second database is outdoor sounds with a total of 23 sounds. The results show that the average level of accuracy is relatively low at around 26.25% for the detection in the four conditions using both sound databases. Due to the low accuracy, we conducted trials by reducing indoor databases only for five sounds. This trial shows the accuracy of 40%. Since the accuracy results are still less than 50%, we conclude that AudiTion applications need to use another approach.","PeriodicalId":118511,"journal":{"name":"2014 Asia-Pacific Conference on Computer Aided System Engineering (APCASE)","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131001275","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: 7