Uncovering Spoken Phrases in Encrypted Voice over IP Conversations
Uncovering Spoken Phrases in Encrypted Voice over IP Conversations
复制标题
揭示加密 IP 语音对话中的口语短语
DOI：
10.1145/1880022.1880029
复制
发表时间：
2010
期刊：
影响因子：
--
通讯作者：
G. Masson
中科院分区：
文献类型：
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作者：
C. V. Wright;L. Ballard;Scott E. Coull;F. Monrose;G. Masson
虽然IP语音（VoIP）正在迅速被采用，但其安全影响尚未得到充分理解。由于VoIP呼叫可能会穿越不受信任的网络，因此应加密数据包以确保机密性。然而，我们表明，它是可能的，以识别加密的VoIP通话中所说的短语时，音频编码使用可变比特率编解码器。要做到这一点，我们只使用单词的语音发音的知识来训练隐马尔可夫模型，例如由字典提供的那些，并搜索指定短语的实例的数据包序列。我们的方法不需要说话者声音的例子，甚至不需要组成目标短语的单词的例子录音。我们评估我们的技术标准的语音识别语料库，包含超过2,000语音丰富的短语，由630个不同的扬声器来自美国大陆。我们的研究结果表明，我们可以识别加密通话中的短语，平均准确率为50%，某些短语的准确率超过90%。显然，这种攻击对当前VoIP加密标准的有效性提出了质疑。此外，我们还研究了底层音频的各种功能对性能的影响，并讨论了缓解方法。
Although Voice over IP (VoIP) is rapidly being adopted, its security implications are not yet fully understood. Since VoIP calls may traverse untrusted networks, packets should be encrypted to ensure confidentiality. However, we show that it is possible to identify the phrases spoken within encrypted VoIP calls when the audio is encoded using variable bit rate codecs. To do so, we train a hidden Markov model using only knowledge of the phonetic pronunciations of words, such as those provided by a dictionary, and search packet sequences for instances of specified phrases. Our approach does not require examples of the speaker’s voice, or even example recordings of the words that make up the target phrase. We evaluate our techniques on a standard speech recognition corpus containing over 2,000 phonetically rich phrases spoken by 630 distinct speakers from across the continental United States. Our results indicate that we can identify phrases within encrypted calls with an average accuracy of 50%, and with accuracy greater than 90% for some phrases. Clearly, such an attack calls into question the efficacy of current VoIP encryption standards. In addition, we examine the impact of various features of the underlying audio on our performance and discuss methods for mitigation.
DOI：
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发表时间：
1995
期刊：
Proceedings. International Conference on Intelligent Systems for Molecular Biology
影响因子：
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作者：
S. Eddy
通讯作者：
S. Eddy
影响因子：
5.6
作者：
KROGH, A;BROWN, M;HAUSSLER, D
通讯作者：
HAUSSLER, D