参考文献拒绝服务攻击及防御技术参考文献整理.doc

cc防御服务  时间:2021-05-04  阅读:()

拒绝服务攻击及防御技术参考文献整理

[1] Gilgor, V. (1983) A note on the Denial-of-Service Problem.Proceedings of Symposium on Security and Privacy (SP'83) , Oakland, CA,USA, 25-27 April, pp. 139{149. IEEE Computer Society, Washington, DC,USA.

[2] Morris, R. T. (1985) A weakness in the 4.2BSD Unix TCP/IPsoftware. Computer Science Technical Report 117. AT&T Bell Labs, MurrayHills, NJ, USA.

[3] Shipley, G. (1999) ISS RealSecure pushes past newer IDS players.Network Computing, 10, 95{111.

[4] Tuncer, T. and Tatar, Y. (2008) Detection SYN ° ooding attacksusing fuzzy logic. Proceedings of International Conference on

Information Security and Assurance (ISA'08) , Washington, DC, USA, 24-26April, pp. 321 {325. IEEE Computer Society, New York, NY, USA.

[5] Mirkovic, J. and Reiher, P. (2005) D-WARD: A source-end defenseagainst ° ooding denial-of-service attacks. IEEE Transactions onDependable and Secure Computing, 2, 216{232.

[6] Asosheh, A. , Dr. and Ramezani, N. (2008) A comprehensivetaxonomy of DDoS attacks and defense mechanism applying in a smartclassi ˉ cation. WSEAS Transactions on Computers, 7, 281 {290.

[7] Mirkovic, J. , Dietrich, S. , Dittrich, D. , and Reiher, P. (2004)Internet Denial of Service Attack and Defense Mechanisms, 1st edition.Prentice Hall PTR, New Jersey, USA.

[8] Paxson, V. (2001) An analysis of using re° ectors fordistributed denial-of-service attacks. ACM SIGCOMM Computer

Communication Review, 31, 38{47.

[9] Moore, D. , Paxson, V. , Savage, S. , Shannon, C. , Staniford, S. ,andWeaver, N. (2003) Inside the slammer worm. IEEE Security and Privacy,1, 33{39.

[10] Hemenway, K. and Calishain, T. (2003) Spidering Hacks.

O'Reilly & Associates, Inc. , Sebastopol, CA, USA.

[11] Goucher, W. (2009) The tipping point. Computer Fraud &Security, 1, 11 {13.

[12] Lesk, M. (2007) The new front line: Estonia under cyberassault.IEEE Security and Privacy, 5, 76{79.

[13] Jalili, R. , Imani-Mehr, F. , Amini, M. , and Shahriari, H.-R.

(2005) Detection of distributed denial of service attacks usingstatistical pre-processor and unsupervised neural networks. LectureNotes in Computer Science, 3439, 192{203.

[14] Gavrilis, D. and Dermatas, E. (2005) Real-time detection ofdistributed denial-of-service attacks using RBF networks and statisticalfeatures. Computer Networks and ISDN Systems, 48, 235{245.

[15] Gavrilis, D. , Tsoulos, I. , and Dermatas, E. (2004) Featureselection for robust detection of distributed denial-of-service attacksusing genetic algorithms. Lecture Notes in Arti ˉ cial Intelligence, 3025,276{281.

[16] Ng, W. , Chan, A. , Yeung, D. , and Tsang, E. (2006) Constructionof high precision RBFNN with low false alarm for detecting ° oodingbased denial of service attacks using stochastic sensitivity measure.Lecture Notes in Arti ˉ cial Intelligence, 3930, 851 {860.

[17] Chan, A. , Ng, W. , D.S, Yeung, and Tsang, E. (2005) Multipleclassi ˉ er system with feature grouping for intrusion detection: Mutualinformation approach. Lecture Notes in Arti ˉ cial Intelligence, 3683,141 {148.

[18] Chan, A. , Yeung, D. , Tsang, E. , and Ng, W. (2006) Empiricalstudy on fusion methods usingensemble of RBFNN for network intrusion detection. Lecture Notes inArti ˉcial Intelligence, 3930, 682{690.

[19] Giacinto, G. , Roli, F. , and Didaci, L. (2003) Fusion ofmultiple classi ˉ ers for intrusion detection in computer networks.Pattern Recognition Letters, 24, 1795{1803.

[20] Mukkamala, S. , Sung, A. H. , and Abraham, A. (2005) Intrusiondetection using an ensemble of intelligent paradigms. Journal of Networkand Computer Applications, 28, 167{182.

[21] Noh, S. , Lee, C. , Choi, K. , and Jung, G. (2003) Detectingdistributed denial of service (DDoS) attacks through inductive learning.Lecture Notes in Computer Science, 2690, 286{295.

[22] ?Oke, G. and Loukas, G. (2007) A denial of service detectorbased on maximum likelihood detection and the random neural network.Computer Journal, 50, 717{727.

[23] Kim, M. , Na, H. , Chae, K. , Bang, H. , and Na, J. (2004) Acombined data mining approach for DDoS attack detection. Lecture Notesin Computer Science, 3090, 943{950.

[24] Siaterlis, C. and Maglaris, B. (2004) Towards multisensor datafusion for DoS detection. Proceedings of symposium on Applied computing(SAC'04) , Nicosia, Cyprus, 14-17 March, pp. 439{446. ACM, New York, NY,USA.

[25] He, H. , Luo, X. , and Liu, B. (2005) Detecting anomalousnetwork tra±c with combined fuzzy-based approaches. Lecture Notes inComputer Science, 3645, 433{442.

[26] Lee, S. , Kim, Y. , Lee, B. , Kang, S. , and Youn, C. (2005) Aprobe detection model using the analysis of the fuzzy cognitive maps.Lecture Notes in Computer Science, 3480, 320{328.

[27] Wei, W. , Dong, Y. , Lu, D. , and Jin, G. (2006) Combining cross-correlation and fuzzy classi ˉ cation to detect distributed denial-of-service attacks. Lecture Notes in Computer Science, 3994, 57{64.

[28] Mukkamala, S. and Sung, A. H. (2004) Computational intelligenttechniques for detecting denial of service attacks. Proceedings ofconference on Innovations in Applied Arti ˉ cial Intelligence

(IEA/AIE'04) , Ottawa, Canada, 17-20 May, pp. 616{624. Springer Verlag,Berlin, Germany.

[29] Sung, A. and Mukkamala, S. (2004) The feature selection andintrusion detection problems. Lecture Notes in Computer Science, 3321,468{482.

[30] Mukkamala, S. , Xu, D. , and Sung, A. (2006) Intrusion detectionbased on behaviour mining and machine learning techniques. Lecture Notesin Arti ˉ cial Intelligence, 4031, 619{628.

[31] Uhlig, S. and Bonaventure, O. (2001) Understanding the long-term self-similarity of internet tra±c. Lecture Notes in ComputerScience, 2156, 286{298.

[32] Xiang, Y. , Lin, Y. , Lei, W. , and Huang, S. (2004) DetectingDDOS attack based on network self- similarity. IEE Proceedings

Communications, 151, 292{295.

[33] Feinstein, L. , Schnackenberg, D. , Balupari, R. , and Kindred, D.

(2003) Statistical approaches to DDoS attack detection and response.Proceedings of Information Survivability Conference and Exposition(DISCEX-III) , Washington, DC, 22-24 April, pp. 303{314. DARPA, Arlington,VA, USA.

[34] Li, M. , Chi, C.-H. , and Long, D. (2004) Fractional gaussiannoise: A tool for characterizing tra±c for detection purpose. LectureNotes in Computer Science, 3309, 94{103.

[35] Li, M. (2004) An approach to reliably identifying signs ofDDOS ° ood attacks based on LRD tra±c pattern recognition. Computersand Security, 23, 549{558.

[36] Tsybakov, B. and Georganas, N. (1998) Self-similar processesin communications networks. IEEE Transactions on Information Theory, 44,1713{1725.

[37] Wang, H. , Zhang, D. , and Shin, K. (2002) Detecting

SYN ° ooding attacks. Proceedings of INFOCOM'02, New York, NY, USA, 23-27 June, pp. 1530{1539. IEEE Communications Society, New York, NY, USA.

[38] Siris, V. and Papagalou, F. (2004) Application of anomalydetection algorithms for detecting syn ° ooding attacks. Proceedings ofGLOBECOM'04, Dallas, TX, USA, 29 November - 3 December, pp. 2050{2054.

[39] Leu, F. and Yang, W. (2005) Intrusion detection with CUSUM forTCP-based DDoS. Lecture Notes in Computer Science, 3823, 1255{1264.

[40] Gu, R. , Yan, P. , Zou, T. , and Guo, C. (2005) An automatic andgeneric early-bird system for internet backbone based on tra±c anomalydetection. Lecture Notes in Computer Science, 3420, 740{748.

[41] Kulkarni, A. and Bush, S. (2006) Detecting distributed denialof service attacks using kolmogorov complexity metrics. Journal ofNetwork and Systems Management, 14(1) , 69{80. [42] Furuya, F. , Matsuzaki,

T. , and Matsuura, K. (2005) Detection of unknown DoS attacks by

Kolmogorov- complexity ° uctuation. Lecture Notes in Computer Science,3822, 395{406. [43] Lee, K. , Kim, J. , Kwon, K. H. , Han, Y. , and Kim, S.

(2008) DDoS attack detection method using cluster analysis. ExpertSystems with Applications, 34, 1659{ 1665.

[44] Li, L. and Lee, G. (2005) DDoS attack detection and wavelets.Telecommunication Systems, 28(3) , 435{451.

[45] Yang, X. , Liu, Y. , Zeng, M. , and Shi, Y. (2004) A novel DDoSattack detecting algorithm based on the continu- ous wavelet transform.Proceedings of Advanced Work- shop on Content Computing (AWCC'04) ,ZhenJiang, JiangSu, China, 15-17 November, pp. 173{181.

[46] Lu, W. and Ghorbani, A. A. (2009) Network anomaly detectionbased on wavelet analysis. EURASIP Journal On Advances In SignalProcessing, 2009, 1 {16.

[47] Kim, S. S. and Reddy, A. L. N. (2008) Statistical techniquesfor detecting tra±c anomalies through packet header data. IEEE/ACMTransactions on Networking, 16, 562{575.

[48] Peng, T. , Leckie, C. , and Ramamohanarao, K. (2003) Detectingdistributed denial of service attacks by sharing distributed belief.Lecture Notes in Computer Science, 2727, 214{225.

[49] Cetnarowicz, K. and Rojek, G. (2004) Behavior based detectionof unfavourable resource. Lecture Notes in Computer Science, 3038,607{614.

[50] Seo, H. S. and Cho, T. H. (2002) Modeling and simulation fordetecting a distributed denial of service attack. Proceedings ofAustralian Joint Conference on Arti ˉ cial Intelligence (AI'02) , 16-21September.

[51] Gelenbe, E. (1993) Learning in the recurrent random neuralnetwork. Neural Computation, 5, 154{164.

[52] Hussain, A. , Heidemann, J. , and Papadopoulos, C. (2003) Aframework for classifying denial of ser- vice attacks. Proceedings ofconference on Appli- cations, technologies, architectures, and protocolsfor computer communications (SIGCOMM'03) , Karlsruhe, Germany, 25-29August, pp. 99{110. ACM, New York, NY, USA.

[53] Gelenbe, E. , Lent, R. , and Nunez, A. (2004) Self-awarenetworks and QoS. Proceedings of the IEEE, 92, 1478{ 1489.

[54] Jing, S. , Wang, H. , and Shin, K. (2003) Hop-count ˉ ltering ane?ective defense against spoofed tra±c. Proceedings of InternationalConference on Computer and Communications Security (CCS'03) , Washington,DC, USA, 27-30 October, pp. 30{41. ACM, New York, NY,

USA.

[55] Kim, Y. , Lau, W. , Chuah, M. , and Chao, H. (2006) PacketScore:A statistics-based packet ˉ ltering scheme against distributed denial-of-service attacks. IEEE Transactions on Dependable and Secure Computing,3(2) , 141 {155.

[56] Ayres, P. , Sun, H. , Chao, H. , and Lau, W. (2006) ALPi: a DDoSdefence system for high-speed networks. IEEE Journal of Selected Areasin Communications, 24(10) , 1864{1876. [57] Sisalem, D. , Kuthan, J. , andEhlert, S. (2006) Denial of service attacks targeting a sip voipinfrastructure: attack scenarios and prevention mechanisms. IEEE Network,20, 26{31.

[58] Jung, J. , Krishnamurthy, B. , and Rabinovich, M. (2002) Flashcrowds and denial of service attacks: characterization and implications

for CDNs and web sites. Proceedings of conference on World Wide Web(WWW'02) , Honolulu, Hawai i, USA, 7-11 May, pp. 553{561. ACM, New York,NY, USA.

[59] Morein, W. G. , Stavrou, A. , Cook, D. L. , Keromytis, A. D. ,Misra, V. , and Rubenstein, D. (2003) Using graphic turing tests tocounter automated DDoS attacks against web servers. Proceedings ofConference on Computer and Communications Security (CCS'03) , Washington,DC, USA, 27-30 October, pp. 8{19. ACM, New York, NY, USA.

[60] Kandula, S. , Katabi, D. , Jacob, M. , and Berger, A. (2005)Botz-4-sale: surviving organized DDoS attacks that mimic ° ash crowds.Proceedings of Symposium on Networked Systems Design & Implementation(NDSI'05) , Houston, TX, USA, 4-6 April, pp. 287{300. USENIX Association,Berkeley, CA, USA.

[61] Mori, G. and Malik, J. (2003) Recognizing objects inadversarial clutter - breaking a visual captcha. Proceedings of

Conference on Computer Vision and Pattern Recognition (CVPR'03) , Madison,Wisconsin, USA, 16-22 June, pp. 134{141.

[62] Gao, Z. and Ansari, N. (2006) Di?erentiating malicious DDoSattack tra±c from normal TCP ° ows by proactive tests. CommunicationLetters, 10(11) , 793{ 795.

[63] Thomas, R. , Mark, B. , Johnson, T. , and Croall, J. (2003)Netbouncer: client-legitimacy-based high-performance DDoS ˉ ltering.Proceedings of Information Survivability Conference and Exposition(DISCEX-III) , Washington, DC, USA, 22-24 April, pp. 14{25. DARPA,Arlington, VA, USA.

NameCheap 2021年新年首次活动 域名 域名邮局 SSL证书等

NameCheap商家如今发布促销活动也是有不小套路的,比如会在提前一周+的时间告诉你他们未来的活,比如这次2021年的首次活动就有在一周之前看到,但是这不等到他们中午一点左右的时候才有正式开始,而且我确实是有需要注册域名,等着看看是否有真的折扣,但是实际上.COM域名力度也就一般需要51元左右,其他地方也就55元左右。当然,这次新年的首次活动不管如何肯定是比平时便宜一点点的。有新注册域名、企业域...

ZJI:台湾CN2/香港高主频服务器7折每月595元起,其他全场8折

ZJI原名维翔主机,是原来Wordpress圈知名主机商家,成立于2011年,2018年9月更名为ZJI,提供香港、日本、美国独立服务器(自营/数据中心直营)租用及VDS、虚拟主机空间、域名注册业务。ZJI今年全新上架了台湾CN2线路服务器,本月针对香港高主频服务器和台湾CN2服务器提供7折优惠码,其他机房及产品提供8折优惠码,优惠后台湾CN2线路E5服务器月付595元起。台湾一型CPU:Inte...

PacificRack(年付低至19美元),夏季促销PR-M系列和多IP站群VPS主机

这几天有几个网友询问到是否有Windows VPS主机便宜的VPS主机商。原本他们是在Linode、Vultr主机商挂载DD安装Windows系统的,有的商家支持自定义WIN镜像,但是这些操作起来特别效率低下,每次安装一个Windows系统需要一两个小时,所以如果能找到比较合适的自带Windows系统的服务器那最好不过。这不看到PacificRack商家有提供夏季促销活动,其中包括年付便宜套餐的P...

cc防御服务为你推荐
parameterdirection麻烦分析这段c#调用存储过程的代码,请详细点!参考手册NDXS和ND5XS网络音频播放器中文目录includingandroid2.3ios5xp如何关闭445端口系统怎么关闭445端口win10关闭445端口如何进入注册表修改关闭445端口tcpip上的netbiostcpip上的netbios是什么用的,有安全隐患吗?开启还是关上win7如何关闭445端口如何彻底永久取消win7粘滞键功能重庆电信宽带管家如何才能以正确的流程在重庆电信安装上宽带联通iphone4联通iphone4跟苹果的iphone4有什么不一样? 比如少了什么功能? 还是什么的?
踢楼 便宜服务器 圣迭戈 ibrs 个人域名 宁波服务器 南通服务器 免费高速空间 什么是web服务器 lamp兄弟连 美国迈阿密 卡巴斯基官网下载 阿里云邮箱个人版 netvigator nnt .htaccess 建站论坛 wannacry勒索病毒 asp简介 赵荣博客 更多