Editing Baum–Welch algorithm (section)

===Cryptanalysis===
The Baum–Welch algorithm is often used to estimate the parameters of HMMs in deciphering hidden or noisy information and consequently is often used in [[cryptanalysis]]. In data security an observer would like to extract information from a data stream without knowing all the parameters of the transmission. This can involve reverse engineering a [[Coding theory|channel encoder]].<ref>{{cite journal |last1=Dingel |first1=Janis |first2=Joachim |last2=Hagenauer |title=Parameter Estimation of a Convolutional Encoder from Noisy Observations |journal=IEEE International Symposium on Information Theory |date=24 June 2007 }}</ref> HMMs and as a consequence the Baum–Welch algorithm have also been used to identify spoken phrases in encrypted VoIP calls.<ref>{{cite journal |last1=Wright |first1=Charles |first2=Lucas |last2=Ballard |first3=Scott |last3=Coull |first4=Fabian |last4=Monrose |first5=Gerald |last5=Masson |title=Spot me if you can: Uncovering spoken phrases in encrypted VoIP conversations |journal=IEEE International Symposium on Security and Privacy |year=2008 }}</ref> In addition HMM cryptanalysis is an important tool for automated investigations of cache-timing data. It allows for the automatic discovery of critical algorithm state, for example key values.<ref>{{cite book |last1=Brumley |first1=Bob |first2=Risto |last2=Hakala |title=Advances in Cryptology – ASIACRYPT 2009 |chapter=Cache-Timing Template Attacks |year=2009 |volume=5912 |pages=667–684 |doi=10.1007/978-3-642-10366-7_39 |series=Lecture Notes in Computer Science |isbn=978-3-642-10365-0 }}</ref>