【24h】

RTP-Miner: A Real-time Security Framework for RTP Fuzzing Attacks

机译:RTP-Miner:针对RTP模糊测试的实时安全框架

获取原文
获取原文并翻译 | 示例

摘要

Real-time Transport Protocol (RTP) is a widely adopted standard for transmission of multimedia traffic in Internet telephony (commonly known as VoIP). Therefore, it is a hot potential target for imposters who can launch different types of Denial of Service (DoS) attacks to disrupt communication; resulting in not only substantive revenue loss to VoIP operators but also undermining the reliability of VoIP infrastructure. The major contribution of this paper is an online framework - RTP-Miner - that detects RTP fuzzing attacks in realtime; as a result, it is not possible to deny access to legitimate users. RTP-Miner can detect both header and payload fuzzing attacks. Fuzzing in the header of RTP packets is detected by combining well known distance measures with a decision tree based classifier. In comparison, pay-load fuzzing is detected through a novel Markov state space model at the receiver. We evaluate RTP-Miner on a real-world RTP traffic dataset. The results show that RTP-Miner detects fuzzing in RTP header with more than 98% accuracy and less than 0.1% false alarm rate even when only 3% fuzzing is introduced. For the same fuzzing rate, it detects payload fuzzing - a significantly more challenging problem -with more than 80% accuracy and less than 2% false alarm rate. RTP-Miner has low memory and processing overheads that makes it well suited for deployment in real world VoIP infrastructure.
机译:实时传输协议(RTP)是在Internet电话(通常称为VoIP)中传输多媒体流量的一种广泛采用的标准。因此,这是冒名顶替者的潜在目标,他们可以发动不同类型的拒绝服务(DoS)攻击来破坏通信。不仅会给VoIP运营商带来实质性的收入损失,还会破坏VoIP基础架构的可靠性。本文的主要贡献是一个在线框架RTP-Miner,它可以实时检测RTP模糊攻击。结果,不可能拒绝对合法用户的访问。 RTP-Miner可以检测标头和有效载荷模糊攻击。通过将众所周知的距离度量与基于决策树的分类器相结合,可以检测RTP数据包报头中的模糊。相比之下,通过接收器处的新型马尔可夫状态空间模型检测到有效载荷模糊。我们在真实的RTP流量数据集上评估RTP-Miner。结果表明,即使仅引入3%的模糊测试,RTP-Miner仍能以超过98%的准确度检测到RTP报头中的模糊测试,而误报率低于0.1%。对于相同的模糊率,它可以检测到有效载荷模糊-一个更具挑战性的问题-准确率超过80%,错误警报率不到2%。 RTP-Miner具有低内存和处理开销,使其非常适合在实际VoIP基础架构中进行部署。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号