Abstract. Privacy is one of the most important security concerns in radio frequency identification. The publication of hundred RFID-based authentication protocols during the last decade raised the need of designing a dedicated privacy model. An important step has been done with the model of Vaudenay that combines early models into a unified and powerful one. In particular, this model addresses the case where an adversary is able to know whether or not the protocol execution succeeded. This modelizes the fact that the adversary may get information from a side channel about the termination of the protocol, e.g., she notices that the access is granted to the RFID-tag holder. We go one step forward in this paper and stress that the adversary may also have access to a side channel that leaks the computational time of the reader. This modelizes an adversary who measures how long it takes to grant the access. Although this channel could be seen as an implementation flaw, we consider that it is always risky to require the implementation to solve what the design should deal with. This new channel enables to demonstrate that many key-reference protocols are not as privacy-friendly as they claim to be, e.g., WSRE, OSK, C 2 , O-FRAP, O-FRAKE,. . . We then introduce the TIMEFUL oracle in the model of Vaudenay, which allows to analyze the resistance of the protocols to time-based attacks as soon as the design phase. Finally, we suggest some methods that make RFID-based authentication protocols immune to such attacks.

The rise of wireless applications based on RFID has brought up major concerns on privacy. Indeed nowadays, when such an application is deployed, informed customers yearn for guarantees that their privacy will not be threatened. One formal way to perform this task is to assess the privacy level of the RFID application with a model. However, if the chosen model does not reflect the assumptions and requirements of the analyzed application, it may misevaluate its privacy level. Therefore, selecting the most appropriate model among all the existing ones is not an easy task. This paper investigates the eight most well-known RFID privacy models and thoroughly examines their advantages and drawbacks in three steps. Firstly, five RFID authentication protocols are analyzed with these models. This discloses a main worry: although these protocols intuitively ensure different privacy levels, no model is able to accurately distinguish them. Secondly, these models are grouped according to their features (e.g., tag corruption ability). This classification reveals the most appropriate candidate model(s) to be used for a privacy analysis when one of these features is especially required. Furthermore, it points out that none of the models are comprehensive. Hence, some combinations of features may not match any model. Finally, the privacy properties of the eight models are compared in order to provide an overall view of their relations. This part highlights that no model globally outclasses the other ones. Considering the required properties of an application, the thorough study provided in this paper aims to assist system designers to choose the best suited model.

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After more than two decades of research in the field of password strength estimation, one clear conclusion may be drawn: no password strength metric by itself is better than all other metrics for every possible password. Building upon this certainty and also taking advantage of the knowledge gained in the area of information fusion, in this paper, we propose a novel multimodal strength metric that combines several imperfect individual metrics to benefit from their strong points in order to overcome many of their weaknesses. The final multimodal metric comprises different modules based both on heuristics and statistics, which, after their fusion, succeed to provide in real time a realistic and reliable feedback regarding the "guessability" of passwords. The validation protocol and the test results are presented and discussed in a companion paper.

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