AutoPOI: Automated Points Of Interest Selection for Side-channel Analysis

Template attacks~(TAs) are one of the most powerful Side-Channel Analysis~(SCA) attacks. The success of such attacks relies on the effectiveness of the profiling model in modeling the leakage information. A crucial step for TA is to select relevant features from the measured traces, often called Points Of Interest~(POIs), to extract the leakage information. Previous research indicates that properly selecting the input leaking features could significantly increase the attack performance. However, due to the presence of SCA countermeasures and advancements in technology nodes, such features become increasingly difficult to extract with conventional approaches such as Principle Component Analysis (PCA) and the Sum Of Squared pairwise T-differences based method (SOST). This work proposes a framework, AutoPOI, based on proximal policy optimization to automatically find, select, and scale down features. The input raw features are first grouped into small regions. The best candidates selected by the framework are further scaled down with an online-optimized dimensionality reduction neural network. Finally, the framework rewards the performance of these features with the results of TA. Based on the experimental results, the proposed framework can extract features automatically that lead to comparable state-of-the-art performance on several commonly used datasets

Biological Plausibility of Arm Postures Influences the Controllability of Robotic Arm Teleoperation

International audienceObjective: We investigated how participants controlling a humanoid robotic arm's 3D endpoint position by moving their own hand are influenced by the robot's postures. We hypothesized that control would be facilitated (impeded) by biologically plausible (implausible) postures of the robot. Background: Kinematic redundancy, whereby different arm postures achieve the same goal, is such that a robotic arm or prosthesis could theoretically be controlled with less signals than constitutive joints. However, congruency between a robot's motion and our own is known to interfere with movement production. Hence, we expect the human-likeness of a robotic arm's postures during endpoint teleoperation to influence controllability. Method: Twenty-two able-bodied participants performed a target-reaching task with a robotic arm whose endpoint's 3D position was controlled by moving their own hand. They completed a two-condition experiment corresponding to the robot displaying either biologically plausible or implausible postures. Results: Upon initial practice in the experiment's first part, endpoint trajectories were faster and shorter when the robot displayed human-like postures. However, these effects did not persist in the second part, where performance with implausible postures appeared to have benefited from initial practice with plausible ones. Conclusion: Humanoid robotic arm endpoint control is impaired by biologically implausible joint coordinations during initial familiarization but not afterwards, suggesting that the human-likeness of a robot's postures is more critical for control in this initial period. Application: These findings provide insight for the design of robotic arm teleoperation and prosthesis control schemes, in order to favor better familiarization and control from their users

Performance and Usability of Various Robotic Arm Control Modes from Human Force Signals

Elaborating an efficient and usable mapping between input commands and output movements is still a key challenge for the design of robotic arm prostheses. In order to address this issue, we present and compare three different control modes, by assessing them in terms of performance as well as general usability. Using an isometric force transducer as the command device, these modes convert the force input signal into either a position or a velocity vector, whose magnitude is linearly or quadratically related to force input magnitude. With the robotic arm from the open source 3D-printed Poppy Humanoid platform simulating a mobile prosthesis, an experiment was carried out with eighteen able-bodied subjects performing a 3-D target-reaching task using each of the three modes. The subjects were given questionnaires to evaluate the quality of their experience with each mode, providing an assessment of their global usability in the context of the task. According to performance metrics and questionnaire results, velocity control modes were found to perform better than position control mode in terms of accuracy and quality of control as well as user satisfaction and comfort. Subjects also seemed to favor quadratic velocity control over linear (proportional) velocity control, even if these two modes did not clearly distinguish from one another when it comes to performance and usability assessment. These results highlight the need to take into account user experience as one of the key criteria for the design of control modes intended to operate limb prostheses

Biological Plausibility of Arm Postures Influences the Controllability of Robotic Arm Teleoperation

International audienceObjective We investigated how participants controlling a humanoid robotic arm’s 3D endpoint position by moving their own hand are influenced by the robot’s postures. We hypothesized that control would be facilitated (impeded) by biologically plausible (implausible) postures of the robot. Background Kinematic redundancy, whereby different arm postures achieve the same goal, is such that a robotic arm or prosthesis could theoretically be controlled with less signals than constitutive joints. However, congruency between a robot’s motion and our own is known to interfere with movement production. Hence, we expect the human-likeness of a robotic arm’s postures during endpoint teleoperation to influence controllability. Method Twenty-two able-bodied participants performed a target-reaching task with a robotic arm whose endpoint’s 3D position was controlled by moving their own hand. They completed a two-condition experiment corresponding to the robot displaying either biologically plausible or implausible postures. Results Upon initial practice in the experiment’s first part, endpoint trajectories were faster and shorter when the robot displayed human-like postures. However, these effects did not persist in the second part, where performance with implausible postures appeared to have benefited from initial practice with plausible ones. Conclusion Humanoid robotic arm endpoint control is impaired by biologically implausible joint coordinations during initial familiarization but not afterwards, suggesting that the human-likeness of a robot’s postures is more critical for control in this initial period. Application These findings provide insight for the design of robotic arm teleoperation and prosthesis control schemes, in order to favor better familiarization and control from their users

AutoPOI: automated points of interest selection for side-channel analysis

Template attacks (TAs) are one of the most powerful side-channel analysis (SCA) attacks. The success of such attacks relies on the effectiveness of the profiling model in modeling the leakage information. A crucial step for TA is to select relevant features from the measured traces, often called points of interest (POIs), to extract the leakage information. Previous research indicates that properly selecting the input leaking features could significantly increase the attack performance. However, due to the presence of SCA countermeasures and advancements in technology nodes, such features become increasingly difficult to extract with conventional approaches such as principle component analysis (PCA) and the Sum Of Squared pairwise T-difference-based method (SOST). This work proposes a framework, AutoPOI, based on proximal policy optimization to automatically find, select and scale down features. The input raw features are first grouped into small regions. The best candidates selected by the framework are further scaled down with an online-optimized dimensionality reduction neural network. Finally, the framework rewards the performance of these features with the results of TA. Based on the experimental results, the proposed framework can extract features automatically that lead to comparable state-of-the-art performance on several commonly used datasets.Cyber Securit

Induced pluripotent stem cells display a distinct set of MHC I-associated peptides shared by human cancers.

peer reviewedPrevious reports showed that mouse vaccination with pluripotent stem cells (PSCs) induces durable anti-tumor immune responses via T cell recognition of some elusive oncofetal epitopes. We characterize the MHC I-associated peptide (MAP) repertoire of human induced PSCs (iPSCs) using proteogenomics. Our analyses reveal a set of 46 pluripotency-associated MAPs (paMAPs) absent from the transcriptome of normal tissues and adult stem cells but expressed in PSCs and multiple adult cancers. These paMAPs derive from coding and allegedly non-coding (48%) transcripts involved in pluripotency maintenance, and their expression in The Cancer Genome Atlas samples correlates with source gene hypomethylation and genomic aberrations common across cancer types. We find that several of these paMAPs were immunogenic. However, paMAP expression in tumors coincides with activation of pathways instrumental in immune evasion (WNT, TGF-β, and CDK4/6). We propose that currently available inhibitors of these pathways could synergize with immune targeting of paMAPs for the treatment of poorly differentiated cancers

Plankton Planet : ‘seatizen’ oceanography to assess open ocean life at the planetary scale

Abstract In every liter of seawater there are between 10 and 100 billion life forms, mostly invisible, called plankton, which form the largest and most dynamic ecosystem on our planet, at the heart of global ecological and economic processes. While physical and chemical parameters of planktonic ecosystems are fairly well measured and modelled at the planetary scale, but biological data are still scarce due to the extreme cost and relative inflexibility of the classical vessels and instruments used to explore marine biodiversity. Here we introduce ‘ Plankton Planet ’, an initiative whose goal is to merge the creativity of researchers, makers, and mariners to ( i ) develop frugal scientific instrumentation and protocols to assess the genetic and morphological diversity of plankton life, and ( ii ) organize their systematic deployment through fleets of volunteer sailors, fishermen, or cargo-ships to generate comparable and open-access plankton data across global and long-term spatio-temporal scales. As proof-of-concept, we show how 20 crews of sailors (“planktonauts”) were abl to sample plankton biomass from the world surface ocean in a single year, generating the first citizen-based, planetary dataset of plankton biodiversity based on DNA barcodes. The quality of this dataset is comparable to that generated by Tara Oceans and is not biased by the multiplication of samplers. This dataset has unveiled significant genetic novelty and can be used to explore the taxonomic and ecological diversity of plankton at both regional and global scales. This pilot project paves the way for construction of a miniaturized, modular, evolvable, affordable and open-source citizen field-platform that will allow systematic assessment of the eco/morpho/genetic variation of aquatic ecosystems across the dimensions of the Earth system