[PRL] Fwd: [Programming] Talk by Michael Clarkson on Wed Oct 13

[Aaron Turon]

That's correct; I just sent out the announcement.  He'll be talking on
Thursday at 3, during the PhD seminar (tea & cookies) slot.

If you'd like to meet with Michael
(http://www.cs.cornell.edu/people/clarkson/), he'll be available from
1:00-2:30 and from 4:00-5:00 on Thursday.  Please email me to request
a meeting slot.

On Sat, Oct 9, 2010 at 4:48 PM, Mitchell Wand <wand at ccs.neu.edu> wrote:
> According the the pl-seminar wiki, Clarkson is speaking HERE on Thu 10/14;
> his title is "Hyperproperties".  I don't have an abstract, perhaps Aaron
> does.
>
> --Mitch
>
> On Sat, Oct 9, 2010 at 11:51 AM, David Van Horn <dvanhorn at ccs.neu.edu>
> wrote:
>>
>> This talk is at HARVARD 10/13.  -- David
>>
>> -------- Original Message --------
>> Subject:        [Programming] Talk by Michael Clarkson on Wed Oct 13
>> Date:   Thu, 07 Oct 2010 13:22:32 -0400
>> From:   Stephen Chong <chong at seas.harvard.edu>
>> To:     EECS Programming List <programming at eecs.harvard.edu>
>>
>>
>>
>>  Hi all,
>>  Michael Clarkson from Cornell University will be visiting next week.
>> We've arranged a talk on Wednesday Oct 13, at 3pm, in MD 123. Title and
>> abstract are below.
>>
>>  If you're interested in meeting with Michael while he's here, let me
>> know!
>>
>> Cheers,
>> Steve.
>>
>>
>>
>> Title:  Quantification of Integrity
>> Speaker:  Michael Clarkson (Cornell University)
>> (http://www.cs.cornell.edu/people/clarkson/)
>>
>> Abstract:  Methods for quantification of corruption (that is,
>> damage to information integrity) have received little attention
>> to date, whereas quantification of information leakage (damage to
>> confidentiality) has been a topic of research for over twenty
>> years. This talk introduces two kinds of integrity measures:
>> contamination and suppression. Contamination measures how much
>> "bad" information is present in outputs; it generalizes taint
>> analysis and is the dual of leakage. Suppression measures how
>> much "good" information is lost from outputs; it generalizes
>> program correctness but does not have a confidentiality dual.
>> Hence the classic duality between confidentiality and integrity
>> is incomplete. As a case study, database privacy conditions from
>> the literature, including differential privacy, are examined using
>> this theory of quantitative integrity and confidentiality.
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>>
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>
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