Safe and Secure Support for Public Safety Networks

International audienceAs explained by Tanzi et al. in the first volume of this book, communicating and autonomous devices will surely have a role to play in the future Public Safety Networks. The “communicating” feature comes from the fact that the information should be delivered in a fast way to rescuers. The “autonomous” characteristic comes from the fact that rescuers should not have to concern themselves about these objects: they should perform their mission autonomously so as not to delay the intervention of the rescuers, but rather to assist them efficiently and reliably.</p

Unsupervised clustering of file dialects according to monotonic decompositions of mixtures

This paper proposes an unsupervised classification method that partitions a set of files into non-overlapping dialects based upon their behaviors, determined by messages produced by a collection of programs that consume them. The pattern of messages can be used as the signature of a particular kind of behavior, with the understanding that some messages are likely to co-occur, while others are not. Patterns of messages can be used to classify files into dialects. A dialect is defined by a subset of messages, called the required messages. Once files are conditioned upon dialect and its required messages, the remaining messages are statistically independent. With this definition of dialect in hand, we present a greedy algorithm that deduces candidate dialects from a dataset consisting of a matrix of file-message data, demonstrate its performance on several file formats, and prove conditions under which it is optimal. We show that an analyst needs to consider fewer dialects than distinct message patterns, which reduces their cognitive load when studying a complex format

A large peptidome dataset improves HLA class I epitope prediction across most of the human population

Published in final edited form as: Nat Biotechnol. 2020 February ; 38(2): 199–209. doi:10.1038/s41587-019-0322-9.Prediction of HLA epitopes is important for the development of cancer immunotherapies and vaccines. However, current prediction algorithms have limited predictive power, in part because they were not trained on high-quality epitope datasets covering a broad range of HLA alleles. To enable prediction of endogenous HLA class I-associated peptides across a large fraction of the human population, we used mass spectrometry to profile >185,000 peptides eluted from 95 HLA-A, -B, -C and -G mono-allelic cell lines. We identified canonical peptide motifs per HLA allele, unique and shared binding submotifs across alleles and distinct motifs associated with different peptide lengths. By integrating these data with transcript abundance and peptide processing, we developed HLAthena, providing allele-and-length-specific and pan-allele-pan-length prediction models for endogenous peptide presentation. These models predicted endogenous HLA class I-associated ligands with 1.5-fold improvement in positive predictive value compared with existing tools and correctly identified >75% of HLA-bound peptides that were observed experimentally in 11 patient-derived tumor cell lines.P01 CA229092 - NCI NIH HHS; P50 CA101942 - NCI NIH HHS; T32 HG002295 - NHGRI NIH HHS; T32 CA009172 - NCI NIH HHS; U24 CA224331 - NCI NIH HHS; R21 CA216772 - NCI NIH HHS; R01 CA155010 - NCI NIH HHS; U01 CA214125 - NCI NIH HHS; T32 CA207021 - NCI NIH HHS; R01 HL103532 - NHLBI NIH HHS; U24 CA210986 - NCI NIH HHSAccepted manuscrip

Harmonizing Safety, Security and Performance Requirements in Embedded Systems

International audience<p> Connected embedded systems have added new conveniences and safety measures to our daily lives --monitoring, automation, entertainment, etc--, but many of them interact with their users in ways where flaws will have grave impacts on personal health, property, privacy, etc, such as systems in the domains of healthcare,<br/>automotives, avionics, and other personal devices with access to sensitive information. Designing these systems with a comprehensive model-driven design process, from requirement elicitation to iterative design, can help detect issues, or incongruities within the requirements themselves earlier. This paper discusses<br/>how safety, security, and performance requirements should be assured with a systematic design process, and how these properties can support or conflict with each other as detected during the verification process.</p

Sécurite des véhicules connectés et/ou autonomes

National audience<p>L'antivirus de votre véhicule est-il bien à jour&#160;? Son pare-feu est-il bien configuré&#160;? Si cela est pour l'instant de l'ordre de la science fiction, l'on commence à voir apparaître des attaques sophistiquées sur les systèmes embarqués des véhicules. Cet article présente les architectures actuelles, les attaques qu'elles peuvent subir, et les solutions de sécurité actuelles. Il explique aussi en quoi ces solutions devront évoluer pour sécuriser aussi les véhicules communicants et/ou autonomes.</p

Hardware-assisted memory tracing on new SoCs embedding FPGA fabrics

International audienceThe FPGA world recently experienced significant changes with the introduction of new SoCs embedding high-end microprocessors and programmable logic on the same integrated circuit. The architecture of these SoCs can be exploited to offer an unprecedented level of monitoring of the memory accesses of running software components, a key element of safety and security analysis. This paper presents the hardware / software implementation of such a memory tracing tool on one of these SoCs. It also proposes example applications in the security field and two attacks - a pass-phrase retrieval and an access control bypass - to demonstrate the power of hardware-assisted memory tracing.</p