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A Receding-Horizon MDP Approach for Performance Evaluation of Moving Target Defense in Networks

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A Receding-Horizon MDP Approach for Performance Evaluation o...

Control Technology and Applications (CCTA),

作者： Zhentian Qian Jie Fu Quanyan Zhu Robotics Engineering Program Worcester Polytechnic Institute Worcester MA USA New York University USA

ISBN: (数字)9781728171401

ISBN: (纸本)9781728171418

In this paper we study the problem of assessing the effectiveness of a proactive defense-by-detection policy with a network-based moving target defense. We model the network system using a probabilistic attack graph-a graphical security model. Given a network system with a proactive defense strategy an intelligent attacker needs to perform reconnaissance repeatedly to learn about the locations of intrusion detection systems and re- plan optimally to reach the target while avoiding detection. To compute the attacker's strategy for security evaluation we develop a receding-horizon planning algorithm using a risk-sensitive Markov decision process with a time-varying reward function. Finally we implement both defense and attack strategies in a synthetic network and analyze how the frequency of network randomization and the number of detection systems can influence the success rate of the attacker. This study provides insights for designing proactive defense strategies against online and multi-stage attacks by a resourceful attacker.

关键词： Security Probabilistic logic Planning Performance evaluation Computational modeling Uncertainty Games

Modelling Companion Animals' Well-being based on Activity Recognition and Biological Rhythms Monitoring

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Modelling Companion Animals' Well-being based on Activity Re...

International Conference on Computational Science and Computational Intelligence (CSCI)

作者： Hazar Zilelioglu Ioana Ocnarescu Ghazaleh Khodabandelou Abdelghani Chibani Clément Bataille Jérôme Mlynarczyk Yacine Amirat Solène Le Bars LISSI Laboratory University of Paris Est-Créteil (UPEC) Capgemini Engineering Paris France Robotics by Design Lab Strate School of Design Paris France Frog Lab Frog Design Paris France BNP Paribas Cardif Cardif Lab Paris France Future of Healthcare Program Capgemini Engineering Paris France

Human-animal companionship is a particular relationship where the well-being of a companion animal entirely depends on their human partner's care. However, proper care of an animal companion can become challenging with aging due to autonomy loss (i.e., motor or cognitive disabilities). In this regard, this very early-stage study proposes a data collection protocol centered on pet dogs, over several days in the context of an elderly-pet relationship. The goals of this study include dog activity recognition (e.g., resting, running, eating, etc.) and behaviour modelling. In order to do so, machine learning techniques will be used and daily behaviour patterns will be modeled over several days using Markov models. This research consolidates a data base on animal behaviour while bringing insights on how to measure the well-being of animals at home.

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Engineering a Wide Range Band-Gap of Anatase TiO2 Via Easy-Controlled Solvothermal Method

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SSRN

SSRN 2024年

作者： Mulyanti, Budi Anshar, Aghisna Nuthfah Hasanah, Lilik Wulandari, Chandra Pawinanto, Roer Eka Hamidah, Ida Berhanuddin, Dilla D. Rusydi, Andrivo Study Program of Electrical Engineering Universitas Pendidikan Indonesia Jl. Dr. Setiabudhi 229 Jawa Barat Bandung40154 Indonesia TVET Research Center Universitas Pendidikan Indonesia Jl. Dr. Setiabudhi 229 Jawa Barat Bandung40154 Indonesia Study Program of Physics Universitas Pendidikan Indonesia Jl. Dr. Setiabudhi 229 Jawa Barat Bandung40154 Indonesia Study Program of Industrial Automation and Robotics Engineering Education Universitas Pendidikan Indonesia Jl. Dr..Setiabudhi 229 Jawa Barat Bandung40154 Indonesia Study Program of Automotive Engineering Education Universitas Pendidikan Indonesia Jl. Dr. Setiabudhi 229 Jawa Barat Bandung40154 Indonesia Research Complex Universiti Kebangsaan Malaysia Level 4 Selangor Bangi43600 Malaysia Department of Physics National University of Singapore 2 Science Drive 3 Singapore117542 Singapore Singapore Synchrotron Light Source National University of Singapore 5 Research Link Singapore117603 Singapore

Titanium dioxide (TiO2) is a semiconductor material with many applications, such as surface-enhanced Raman spectroscopy (SERS), photocatalysts, water treatment, and photoelectrochemicals. Controlling the properties of anatase TiO2 is typically challenging during TiO2 synthesis. Generally, achieving this control necessitates intricate conditions and processes. The solvothermal method is expected to be easier to control the formation of TiO2 with well-defined morphology and good crystallinity, hence, the band gap can be tuned well. However, there has been a lack of research on the effect of solvents in the solvothermal method of TiO2 synthesis on the optical band gap. Herewith, we report an easy-controlled solvothermal method by varying the type and composition of the solvent to modify the band gap of anatase TiO2. Interestingly, ultraviolet-visible (UV-Vis) analysis reveals an anatase TiO2 optical band gap between 1.66 to 3.60 eV, indicating that TiO2 obtained can be operated in the UV to visible light region. The solvents utilized for the titanium (IV) isopropoxide (TTIP) precursor in TiO2 synthesis are isopropanol (IPA), methanol (META), and ethanol (ETA). X-ray diffraction, Raman spectroscopy, and scanning electron microscopy show anatase TiO2 single crystalline phases synthesized by IPA and ETA solvents and the combination of polycrystalline and amorphous morphology TiO2 synthesized by META solvent. Anatase single crystalline phases are achieved for the solvent mixture with a composition ratio of IPA:ETA solvents of 1:2, 1:1, and 2:1. Our result shows that the optical band gap of single crystalline phase TiO2 can be engineered in a wide range via solvothermal method for green and sustainable material. © 2024, The Authors. All rights reserved.

关键词： Titanium dioxide

Balanced depth completion between dense depth inference and sparse range measurements via KISS-GP

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arXiv 2020年

作者： Yoon, Sungho Kim, Ayoung Robotics Program KAIST Daejeon Korea Republic of Department of Civil and Environmental Engineering KAIST Daejeon Korea Republic of

Estimating a dense and accurate depth map is the key requirement for autonomous driving and robotics. Recent advances in deep learning have allowed depth estimation in full resolution from a single image. Despite this impressive result, many deep-learning-based monocular depth estimation (MDE) algorithms have failed to keep their accuracy yielding a meter-level estimation error. In many robotics applications, accurate but sparse measurements are readily available from Light Detection and Ranging (LiDAR). Although they are highly accurate, the sparsity limits full resolution depth map reconstruction. Targeting the problem of dense and accurate depth map recovery, this paper introduces the fusion of these two modalities as a depth completion (DC) problem by dividing the role of depth inference and depth regression. Utilizing the state-of-the-art MDE and our Gaussian process (GP) based depth-regression method, we propose a general solution that can flexibly work with various MDE modules by enhancing its depth with sparse range measurements. To overcome the major limitation of GP, we adopt Kernel Interpolation for Scalable Structured (KISS)-GP and mitigate the computational complexity from O(N3) to O(N). Our experiments demonstrate that the accuracy and robustness of our method outperform state-of-the-art unsupervised methods for sparse and biased measurements. Copyright © 2020, The Authors. All rights reserved.

关键词： Optical radar

A theory of hypergames on graphs for synthesizing dynamic cyber defense with deception

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arXiv 2020年

作者： Kulkarni, Abhishek N. Fu, Jie Robotics Engineering Program Worcester Polytechnic Institute 100 Institute Rd. WorcesterMA United States Dept. of Electrical and Computer Engineering Robotics Engineering Program Worcester Polytechnic Institute 100 Institute Rd. WorcesterMA United States

In this chapter, we present an approach using formal methods to synthesize reactive defense strategy in a cyber network, equipped with a set of decoy systems. We first generalize formal graphical security models–attack graphs–to incorporate defender’s countermeasures in a game-theoretic model, called an attack-defend game on graph. This game captures the dynamic interactions between the defender and the attacker and their defense/attack objectives in formal logic. Then, we introduce a class of hypergames to model asymmetric information created by decoys in the attacker-defender interactions. Given qualitative security specifications in formal logic, we show that the solution concepts from hypergames and reactive synthesis in formal methods can be extended to synthesize effective dynamic defense strategy using cyber deception. The strategy takes the advantages of the misperception of the attacker to ensure security specification is satisfied, which may not be satisfiable when the information is symmetric. Copyright © 2020, The Authors. All rights reserved.

关键词： Network security

Sensing accident-prone features in urban scenes for proactive driving and accident prevention

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arXiv 2022年

作者： Mishra, Sumit Rajendran, Praveen Kumar Vecchietti, Luiz Felipe Har, Dongsoo The Robotics Program Korea Advanced Institute of Science and Technology Daejeon Korea Republic of Division of Future Vehicle Korea Advanced Institute of Science and Technology Daejeon Korea Republic of Data Science Group Institute for Basic Science Daejeon Korea Republic of The CCS Graduate School of Green Transportation Korea Advanced Institute of Science and Technology Daejeon Korea Republic of

In urban cities, visual information on and along roadways is likely to distract drivers and lead to missing traffic signs and other accident-prone (AP) features. To avoid accidents due to missing these visual cues, this paper proposes a visual notification of AP-features to drivers based on real-time images obtained via dashcam. For this purpose, Google Street View images around accident hotspots (areas of dense accident occurrence) identified by a real-accident dataset are used to train a novel attention module to classify a given urban scene into an accident hotspot or a non-hotspot (area of sparse accident occurrence). The proposed module leverages channel, point, and spatial-wise attention learning on top of different CNN backbones. This leads to better classification results and more certain AP-features with better contextual knowledge when compared with CNN backbones alone. Our proposed module achieves up to 92% classification accuracy. The capability of detecting AP-features by the proposed model were analyzed by a comparative study of three different class activation map (CAM) methods, which were used to inspect specific AP-features causing the classification decision. Outputs of CAM methods were processed by an image processing pipeline to extract only the AP-features that are explainable to drivers and notified using a visual notification system. Range of experiments was performed to prove the efficacy and AP-features of the system. Ablation of the AP-features taking 9.61%, on average, of the total area in each image increased the chance of a given area to be classified as a non-hotspot by up to 21.8%. © 2022, CC BY.

关键词： Accidents

PrimA6D: Rotational Primitive Reconstruction for Enhanced and Robust 6D Pose Estimation

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arXiv 2020年

作者： Jeon, Myung-Hwan Kim, Ayoung Department of the Robotics Program KAIST Daejeon Korea Republic of Department of Civil and Environmental Engineering KAIST Daejeon Korea Republic of

— In this paper, we introduce a rotational primitive prediction based 6D object pose estimation using a single image as an input. We solve for the 6D object pose of a known object relative to the camera using a single image with occlusion. Many recent state-of-the-art (SOTA) two-step approaches have exploited image keypoints extraction followed by PnP regression for pose estimation. Instead of relying on bounding box or keypoints on the object, we propose to learn orientation-induced primitive so as to achieve the pose estimation accuracy regardless of the object size. We leverage a Variational AutoEncoder (VAE) to learn this underlying primitive and its associated keypoints. The keypoints inferred from the reconstructed primitive image are then used to regress the rotation using PnP. Lastly, we compute the translation in a separate localization module to complete the entire 6D pose estimation. When evaluated over public datasets, the proposed method yields a notable improvement over the LINEMOD, the Occlusion LINEMOD, and the YCB-Video dataset. We further provide a synthetic-only trained case presenting comparable performance to the existing methods which require real images in the training phase. Copyright © 2020, The Authors. All rights reserved.

关键词： Machine learning

Evaluation of usability and user interface design on Vokasiku mobile application using think aloud

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AIP Conference Proceedings 2024年第1期3047卷

作者： Andhini Rahma Santoso Meida Cahyo Untoro Sri Karnila Yutika Amelia Effendi Program Studi Teknik Informatika Institut Teknologi Sumatera Lampung Indonesia Institut Informatika dan Bisnis Darmajaya Lampung Indonesia Robotics and Artificial Intelligence Engineering Faculty of Advanced Technology and Multidiscipline Universitas Airlangga Surabaya Indonesia

The Vokasiku is a mobile application that provides certification test services, online courses, and information about scholarships and job vacancies. The Vokasiku application was released on April 27, 2020. The users are still few and still need improvement. One of the important aspects of software is usability. Usability describes the perception of user experience related to effectiveness, ease, and satisfaction in using the product. The usability evaluation of the Vokasiku application is carried out using a user approach in the test, namely the Think Aloud method. Measuring the level of user satisfaction is done by using the Questionnaire for User Interaction Satisfaction (QUIS). After testing by the user, there are several errors in the application, so it is necessary to design a user interface to solve the problems experienced by the user. The user interface made is a high-fidelity prototype and front-end application. The design results will be re-evaluated until the usability value increases and no major problems are found.

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Multi-legged matter transport: A framework for locomotion on noisy landscapes

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arXiv 2023年

作者： Chong, Baxi He, Juntao Soto, Daniel Wang, Tianyu Irvine, Daniel Blekherman, Grigoriy Goldman, Daniel I. Interdisciplinary Graduate Program in Quantitative Biosciences Georgia Institute of Technology North Avenue AtlantaGA30332 United States School of Physics Georgia Institute of Technology 837 State St NW AtlantaGA30332 United States Institute for Robotics and Intelligent Machines Georgia Institute of Technology 801 Atlantic Dr NW AtlantaGA30332 United States School of Mathematics Georgia Institute of Technology 686 Cherry St NW AtlantaGA30332 United States

While the transport of matter by wheeled vehicles or legged robots can be guaranteed in engineered landscapes like roads or rails, locomotion prediction in complex environments like collapsed buildings or crop fields remains challenging. Inspired by principles of information transmission which allow signals to be reliably transmitted over noisy channels, we develop a "matter transport" framework demonstrating that non-inertial locomotion can be provably generated over "noisy" rugose landscapes (heterogeneities on the scale of locomotor dimensions). Experiments confirm that sufficient spatial redundancy in the form of serially-connected legged robots leads to reliable transport on such terrain without requiring sensing and control. Further analogies from communication theory coupled to advances in gaits (coding) and sensor-based feedback control (error detection/correction) can lead to agile locomotion in complex terradynamic regimes. © 2023, CC BY.

关键词： Information theory