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X-ORIGINAL-URL:https://sal.cs.unibuc.ro
X-WR-CALDESC:Events for SECURITY & APPLIED LOGIC
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DTSTART:20170101T000000
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DTSTART;TZID=UTC:20181213T083000
DTEND;TZID=UTC:20181213T100000
DTSTAMP:20260403T204445
CREATED:20181209T060341Z
LAST-MODIFIED:20181209T061334Z
UID:226-1544689800-1544695200@sal.cs.unibuc.ro
SUMMARY:How to find bugs in your (x86) code; RIVER tool - current state and future
DESCRIPTION:Speaker: Ciprian Păduraru \n\nAbstract: \nEven with access to the source code of a program\, it is not easy to reverse engineer a program to find inputs for specific programs. This presentation starts with a practical walkthrough over classic methods for automating software testing\, such as fuzz testing\, symbolic and concolic execution. Then\, a tool named RIVER is presented in its current state\, together with the technical plans for improving it to achieve at least the same features set with similar tools such as KLEE. By using its reversible execution capabilities\, and advanced tracing support\, we think that by putting efforts in the implementation plan described in the presentation\, we can obtain improved test coverage in relation to resources consumed. Research ideas for various parts including RIVER symbolic/concolic execution\, tracers improvements\, and combining these techniques with machine learning will be presented.
URL:https://sal.cs.unibuc.ro/event/how-to-find-bugs-in-your-x86-code-river-tool-current-state-and-future/
LOCATION:Facultatea de Matematica si Informatica\, sala 202
CATEGORIES:Security Seminar,Seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Bucharest:20181206T180000
DTEND;TZID=Europe/Bucharest:20181206T200000
DTSTAMP:20260403T204445
CREATED:20181203T124550Z
LAST-MODIFIED:20181203T124550Z
UID:222-1544119200-1544126400@sal.cs.unibuc.ro
SUMMARY:Logical Foundations: Total and Partial Maps
DESCRIPTION:Speaker: Miriam Costan. \n\nThis week we continue exploring Coq based on the Logical Foundations volume of Software Foundations\, chapter “Total and Partial Maps”
URL:https://sal.cs.unibuc.ro/event/logical-foundations-total-and-partial-maps/
LOCATION:Facultatea de Matematica si Informatica\, sala 202
CATEGORIES:Coq Seminar,Seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Bucharest:20181206T100000
DTEND;TZID=Europe/Bucharest:20181206T120000
DTSTAMP:20260403T204445
CREATED:20181126T110006Z
LAST-MODIFIED:20181201T041129Z
UID:208-1544090400-1544097600@sal.cs.unibuc.ro
SUMMARY:Classical and quantum degrees of truth: a new look at the effects of a Hilbert space
DESCRIPTION:Speaker: Roberto Giuntini (University of Cagliari). \n\nWe investigate certain Brouwer-Zadeh lattices that serve as abstract counterparts of lattices of effects in Hilbert spaces under the spectral ordering. These algebras\, called PBZ∗-lattices\, can also be seen as generalisations of orthomodular lattices and are remarkable for the collapse of three notions of “sharpness” that are distinct in general Brouwer-Zadeh lattices. We investigate the structure theory of PBZ∗-lattices and their reducts; in particular\, we prove some embedding results for PBZ∗-lattices and provide an initial description of the lattice of PBZ∗-varieties.
URL:https://sal.cs.unibuc.ro/event/classical-and-quantum-degrees-of-truth-a-new-look-at-the-effects-of-a-hilbert-space/
LOCATION:Facultatea de Matematica si Informatica\, sala 202
CATEGORIES:Logic Seminar,Seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Bucharest:20181129T083000
DTEND;TZID=Europe/Bucharest:20181129T103000
DTSTAMP:20260403T204445
CREATED:20181126T105140Z
LAST-MODIFIED:20181126T111443Z
UID:200-1543480200-1543487400@sal.cs.unibuc.ro
SUMMARY:Machine Learning Framework for Security Applications
DESCRIPTION:Speaker: Paul Irofti (University of Bucharest). \n\nMachine learning helps us tackle large and apparently intractable optimization problems. Even though neural networks are by far the most popular choice in the field\, we focus on dictionary learning (DL) for sparse representations (SR) instead. Our preference is motivated by the much simpler model that provides faster methods with a solid theoretical background\, understanding and interpretability. \nIn fact it has been recently shown that the forward pass inside neural networks is equivalent to performing sparse representation. Thus performing dictionary learning can be interpreted as a backward pass on a much simpler and smaller model. This relaxation comes with a small performance hit in exchange for the large reduction in algorithm complexity. \nOur talk will focus on adapting DL to Big Data conditions\, DL classification and the problem of malware identification\,  nomaly detection\, online DL and Internet of Things applications.
URL:https://sal.cs.unibuc.ro/event/machine-learning-framework-for-security-applications/
LOCATION:Facultatea de Matematica si Informatica\, sala 202
CATEGORIES:Security Seminar,Seminar
END:VEVENT
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