A Digg discussion regarding this post:
http://www.digg.com/security/Can_you_prove_non-repudiation_in_eCommerce_Apps_
On 6/1/06, Craig Wright <cwright@bdosyd.com.au> wrote:>> Hello,> Firstly there is no way to prove non-repudiation. There is no valid means to prove encryption. For those who do not agree, please read up on computational mathematics and the N vs NP problem (also see computational
theory in general). Micheal Sipser (from MIT) has some excellent papers on the topic.>> Next lets get to prove. Prove is a mathematical determination of a rule. Even in the case of a discovered and somehow proven encryption algorithm there is no way to prove non-repudiation.>> What
does this mean? It comes down to a likelihood determination. This is a probabilistic determination of the Cumulative distribution function (CDF) associated with the survival and hazard functions of the plot of time against likelihood of compromise.>> Even in cases of a perfect algorithm
there is an associated hazard function associated with a brute force compromise of the key. In most cases this Probability density Function (PDF) correlates to a Poisson distribution.>> So what you are looking at in reality is a survival function that will be acceptable in a court of law
that will not be readily repudiable by the opposing party.>> To do this you need to look at proof beyond reasonable doubt. This is due to the criminal standard of proof being used for deceit. As you wish to prove against a person who may be lying this is the necessary level of proof. In
common law courts this is generally (though not exclusively) held at a determined confidence level (CI) of 99%. That is an alpha set at 1%.>> Now the determination needs to be complete in a cumulative manner which includes the totality of the systems. In this you need to determine the
individual hazard function for each of the components. This is than extrapolated into the total Survival function estimate for the system.>> One property of the exponential distribution and hence the Poisson process is that it is memory-less (This is the number of incidents occurring in
any bounded interval of time after time t is independent of the number of arrivals occurring before time t).>> Now this means that you are attempting to determine the lambda function λ(t) associated with each hazard occurrence (being the likelihood of brute force or other key
compromise). The number of expected key compromises for each component is than the integral of λ(t) for the period from 0 (start time) to a determined safe time (i.e. promised non-repudiation of 5 years, 25 years etc).>> So yes there are ways to achieve what you are asking. What you
are looking at is the expected "safe" time of your system.>> Regards,> Craig>> -----Original Message-----> From: Joe [mailto:bitshield@gmail.com]> Sent: Friday, 2 June 2006 4:32 AM> To: security-basics@securityfocus.com> Subject: Proving non-repudiation in
e-Commerce App>> Dear List-Members>> I'm currently dealing with a review of an e-Commerce Application. One> goal is to prove that this application properly implements a> non-repudiation mechanism throughout the whole process-flow. This flow> starts at the user
authentication, communication over the web to the> server component, then processing of the client requests and finally> logging.>> The non-repudiation has similarities with e-Banking which points me to> the following keywords: digital signature, signed logging and time> stamp
protocols. Using Google I also found various sources discussing> most of those points individually. However I'm looking for a more> general, broad and complete approach.>> Do you guys have interesting sources and experiences about verifying> non-repudiation? Are there standards,
defined processes, work-flows,> and implementation- or audit guidelines?>> Thanks for your feedback> Joe>>> Liability limited by a scheme approved under Professional Standards Legislation in respect of matters arising within those States and Territories of Australia where
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