Knowledge Flow Analysis for Security Protocols

Knowledge flow analysis offers a simple and flexible way to find flaws in security protocols. A protocol is described by a collection of rules constraining the propagation of knowledge amongst principals. Because this characterization corresponds closely to informal descriptions of protocols, it allows a succinct and natural formalization; because it abstracts away message ordering, and handles communications between principals and applications of cryptographic primitives uniformly, it is readily represented in a standard logic. A generic framework in the Alloy modelling language is presented, and instantiated for two standard protocols, and a new key management scheme.Comment: 20 page

Au large de Fos-sur-Mer – Anse Saint-Gervais, navalia

Tout d’abord, il faut rappeler l’importance indéniable du port de Fos à l’époque romaine. En effet, le port de Fossae Marianae, qui doit son nom au canal de Marius, permettait la liaison du littoral avec la partie navigable du Rhône et constituait de ce fait un des courants commerciaux les plus actifs du monde romain. Cet avant-port d’Arles, un peu comparable à Ostie pour Rome, était traversé par l’axe Rhône-Saône-Rhin, desservant les Gaules, les Germanies et la Bretagne. Ce dynamisme commerc..

Classic but unexpected: a case of Jefferson fracture.

A man was found lying dead next to a ladder, with only a laceration surrounded by an abrasion visible upon external examination. No skull fractures were palpable. A CT scan and MRI showed a Jefferson fracture of the atlas, associated to a posterior displacement of the skull, a fracture of the dens of the axis, and fractures of the bodies of C5 and C6. Jefferson fractures typically result from a blow to the apex of the skull. In such cases, forensic pathologists should suspect the existence of a Jefferson fracture, particularly when no severe injuries are visible externally

Learning biophysically-motivated parameters for alpha helix prediction

Background: Our goal is to develop a state-of-the-art protein secondary structure predictor, with an intuitive and biophysically-motivated energy model. We treat structure prediction as an optimization problem, using parameterizable cost functions representing biological “pseudo-energies. ” Machine learning methods are applied to estimate the values of the parameters to correctly predict known protein structures. Results: Focusing on the prediction of alpha helices in proteins, we show that a model with 302 parameters can achieve a Qα value of 77.6 % and an SOVα value of 73.4%. Such performance numbers are among the best for techniques that do not rely on external databases (such as multiple sequence alignments). Further, it is easier to extract biological significance from a model with so few parameters. Conclusions: The method presented shows promise for the prediction of protein secondary structure. Biophysically-motivated elementary free-energies can be learned using SVM techniques to construct an energy cost function whose predictive performance rivals state-of-the-art. This method is general and can be extended beyond the all-alpha case described here. 1 Backgroun

Cleaning deteriorated elements of ammunition: Development of a procedure applied to cartridge cases from the Second World War.

Deteriorated elements of ammunition can be found while investigating different types of events. Exposure to adverse environmental conditions may lead to metal alteration (corrosion) or organic material deposition (contaminations) on the exposed elements of ammunition. From a forensic perspective, both types of deterioration pose challenges when observing marks left by the firearms used to discharge the corresponding ammunition (e.g. firing pin, extractor). The longer the time of exposure to the adverse environmental conditions, the more challenging the observation of such marks. A literature review highlighted three previously published restorative methods used to clean deteriorated elements of ammunition. The aim of this research is to develop a cleaning procedure applicable to cartridge cases exposed to adverse environmental conditions, while avoiding the degradation of marks left by the firearms used to discharge the corresponding ammunition. A first batch of 21 brass cartridge cases dating back to the Second World War (WWII) was used to develop a cleaning sequence involving the three methods. The efficiency of each restorative method was qualitatively assessed using optical macroscopy and the Evofinder® ballistic identification system. The developed sequence relies on successive applications of Tickopur® TR 7 (a diluted soft metal cleaner), sulfuric acid and finally Aqua Regia (HCl 37% and HNO <sub>3</sub> 75%), all of them involving ultrasonic baths. The resulting cleaning sequence was subsequently applied to three batches of Second World War cartridge cases discovered in France and Russia. This sequential procedure allows the effective cleaning of WWII brass cartridge cases while highlighting different marks left by firing pins, extractors, ejectors, and breech faces. Applying a forensic analysis and comparison process to the marks highlighted on these elements of ammunition can support the verification of historical facts when reconstructing events which took place more than seventy years ago

Physical random functions

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2003.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Includes bibliographical references (p. 87-89).In general, secure protocols assume that participants are able to maintain secret key information. In practice, this assumption is often incorrect as an increasing number of devices are vulnerable to physical attacks. Typical examples of vulnerable devices are smartcards and Automated Teller Machines. To address this issue, Physical Random Functions are introduced. These are Random Functions that are physically tied to a particular device. To show that Physical Random Functions solve the initial problem, it must be shown that they can be made, and that it is possible to use them to provide secret keys for higher level protocols. Experiments with Field Programmable Gate Arrays are used to evaluate the feasibility of Physical Random Functions in silicon.by Blaise L.P. Gassend.S.M

Greater Expectations?

Physically Unclonable Functions (PUFs) are key tools in the construction of lightweight authentication and key exchange protocols. So far, all existing PUF-based authentication protocols follow the same paradigm: A resource-constrained prover, holding a PUF, wants to authenticate to a resource-rich verifier, who has access to a database of pre-measured PUF challenge-response pairs (CRPs). In this paper we consider application scenarios where all previous PUF-based authentication schemes fail to work: The verifier is resource-constrained (and holds a PUF), while the prover is resource-rich (and holds a CRP-database). We construct the first and efficient PUF-based authentication protocol for this setting, which we call converse PUF-based authentication. We provide an extensive security analysis against passive adversaries, show that a minor modification also allows for authenticated key exchange and propose a concrete instantiation using controlled Arbiter PUFs