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arXiv 2019年

作者： Fernando, Praveen Wei, Jin Department of Computer and Information Technology Purdue University West LafayetteIN United States

— Cloud architecture has become a valuable solution for different applications, such as big data analytics, due to its high-degree of availability, scalability and strategic value. However, there still remain challenges in managing cloud architecture, in areas such as cloud security. In this paper, we exploit software-defined networking (SDN) and blockchain technologies to secure cloud management platforms from a networking perspective. We develop a blockchain-powered SDN-enabled networking infrastructure in which the integration between blockchain-based security and autonomy management layer and multi-controller SDN networking layer is defined to enhance the integrity of the control and management messages. Furthermore, our proposed networking infrastructure also enables the autonomous bandwidth provisioning to enhance the availability of cloud architecture. In the simulation section, we evaluate the performance of our proposed blockchain-powered SDN-enabled networking infrastructure by considering different scenarios. Copyright © 2019, The Authors. All rights reserved.

关键词： Software defined networking

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A Performance Evaluation of CAN Encryption

A Performance Evaluation of CAN Encryption

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IEEE International Conference on Trust, Privacy and Security in Intelligent Systems and Applications (TPS-ISA)

作者： Hanlin Chen Baijian Yang Dept. of Computer and Information Technology Purdue University West Lafayette IN USA

ISBN: (数字)9781728167411

ISBN: (纸本)9781728167428

Recent research on vehicular cybersecurity has highlighted the known vulnerabilities and exploits that plague in-vehicular networks; in particular, the communication protocol governing the in-vehicular network, the Control Area Network (CAN), has been a frequent and often fruitful target of related attacks. Accordingly, the focus of this project is to investigate the application of encryption algorithms to the in-vehicular network and evaluate the performance characteristics of said algorithms when used in this context. This current paper includes examination of a) the maximum acceptable latency based on the vehicular requirements as well as b) the latency in communication when employing various encryption algorithms. In Hardware-In-the-Loop (HIL) simulations, our work suggests that in-vehicular networks can absorb the latencies introduced by select encryption approaches and still satisfy the real-time requirements needed by the intra-vehicular communication system to avoid collisions and the like.

关键词： Encryption computer security Protocols Vehicles Safety Accidents

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Slow electron-phonon relaxation controls the dynamics of the superconducting resistive transition

arXiv

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arXiv 2022年

作者： Baeva, E.M. Kolbatova, A.I. Titova, N.A. Saha, S. Boltasseva, A. Bogdanov, S. Shalaev, V.M. Semenov, A.V. Levchenko, A. Goltsman, G.N. Khrapai, Vadim S. Moscow Pedagogical State University Moscow119435 Russia National Research University Higher School of Economics 20 Myasnitskaya Street Moscow101000 Russia Laboratory of Photonic Gas University of Science and Technology MISIS Moscow119049 Russia Birck Nanotechnology Center Elmore Family School of Electrical and Computer Engineering Purdue University West LafayetteIN47907 United States Department of Electrical and Computer Engineering University of Illinois at Urbana-Champaign UrbanaIL61801 United States Holonyak Micro and Nanotechnology Lab University of Illinois at Urbana-Champaign UrbanaIL61801 United States Illinois Quantum Information Science and Technology Center University of Illinois at Urbana-Champaign UrbanaIL61801 United States Moscow Institute of Physics and Technology Dolgoprudny141701 Russia Department of Physics University of Wisconsin-Madison Madison Wisconsin MadisonWI53706 United States Russian Quantum Center Moscow Russia Osipyan Institute of Solid State Physics Russian Academy of Sciences Chernogolovka Russia

We investigate the temporal and spatial scales of resistance fluctuations (R-fluctuations) at the superconducting resistive transition accessed through voltage fluctuations measurements in thin epitaxial TiN films. This material is characterized by a slow electron-phonon relaxation, which puts it far beyond the applicability range of the textbook scenario of superconducting fluctuations. The measured Lorentzian spectrum of the R-fluctuations identifies their correlation time, which is nearly constant across the transition region and has no relation to the conventional Ginzburg-Landau time scale. Instead, the correlation time coincides with the energy relaxation time determined by a combination of the electron-phonon relaxation and the relaxation via diffusion into reservoirs. Our data is quantitatively consistent with the model of spontaneous temperature fluctuations and highlight the lack of understanding of the resistive transition in materials with slow electron-phonon relaxation. Copyright © 2022, The Authors. All rights reserved.

关键词： Electron-phonon interactions

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Forensic Analysis of Third Party Location Applications in Android and iOS

arXiv

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arXiv 2019年

作者： Bays, Jason Karabiyik, Umit Department of Computer and Information Technology Purdue University West LafayetteIN United States

Location sharing applications are becoming increasingly common. These applications allow users to share their own locations and view contacts’ current locations on a map. Location applications are commonly used by friends and family members to view Global Positioning System (GPS) location of an individual, but valuable forensic evidence may exist in this data when stored locally on smartphones. This paper aims to discover forensic artifacts from two popular third-party location sharing applications on iOS and Android devices. Industry standard mobile forensic suites are utilized to discover if any locally stored data could be used to assist investigations reliant on knowing the past location of a suspect. Security issues raised regarding the artifacts found during our analysis is also discussed. Copyright © 2019, The Authors. All rights reserved.

关键词： Location

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Identifying Consumer Health Terms of Side Effects in Twitter Posts

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Studies in Health technology and Informatics 2018年 251卷 273-276页

作者： Jiang, Keyuan Chen, Tingyu Calix, Ricardo A. Bernard, Gordon R. Computer Information Technology and Graphics Purdue University Northwest United States Department of Medicine Vanderbilt University United States

ISBN: (纸本)9781614998792

Prevalence of social media has driven a growing number of health related applications with the information shared by online users. It is well known that a gap exists between healthcare professionals and laypeople in expressing the same health concepts. Filling this gap is particularly important for health related applications using social media data. A data-driven, attributional similarity-based method was developed to identify Twitter terms related to side effect concepts. For the 10 most common side effect (symptom) concepts, our method was able to identify a total of 333 Twitter terms, among which only 90 are mapped to those in the consumer health vocabulary (CHV). The identified Twitter terms are specific to Twitter data, indicating a need to expand the existing CHV, and many of them seem to have less ambiguity in word senses than those in CHV. © 2018 The authors and IOS Press. All rights reserved.

关键词： Social networking (online)

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Advanced Fuzzy C-Means Algorithm Based on Local Density and Distance

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Journal of Shanghai Jiaotong university(Science) 2018年第5期23卷 636-642页

作者： Shaochun PANG Yijie SHAO Sen JIANG Keyuan School of Computer Engineering and Science Shanghai UniversityShanghai 200444China Department of Computer Information Technology ＆ Graphics Purdue University NorthwestHammond 46323USA

This paper presents an advanced fuzzy C-means(FCM) clustering algorithm to overcome the weakness of the traditional FCM algorithm, including the instability of random selecting of initial center and the limitation of the data separation or the size of clusters. The advanced FCM algorithm combines the distance with density and improves the objective function so that the performance of the algorithm can be improved. The experimental results show that the proposed FCM algorithm requires fewer iterations yet provides higher accuracy than the traditional FCM algorithm. The advanced algorithm is applied to the influence of stars' box-office data, and the classification accuracy of the first class stars achieves 92.625%.

关键词： objective function clustering center fuzzy C-means （FCM） clustering algorithm degree of member-ship

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Valley interference and spin exchange at the atomic scale in silicon

arXiv

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arXiv 2021年

作者： Voisin, Benoit Bocquel, J. Tankasala, A. Usman, M. Salfi, J. Rahman, R. Simmons, M.Y. Hollenberg, L.C.L. Rogge, S. Centre for Quantum Computation and Communication Technology School of Physics The University of New South Wales SydneyNSW2052 Australia Electrical and Computer Engineering Department Purdue University West LafayetteIN United States Centre for Quantum Computation and Communication Technology School of Physics The University of Melbourne ParkvilleVIC3010 Australia School of Computing and Information Systems Melbourne School of Engineering The University of Melbourne ParkvilleVIC3010 Australia School of Physics The University of New South Wales SydneyNSW2052 Australia

Tunneling is a fundamental quantum process with no classical equivalent, which can compete with Coulomb interactions to give rise to complex phenomena. Phosphorus dopants in silicon can be placed with atomic precision to address the different regimes arising from this competition. However, they exploit wavefunctions relying on crystal band symmetries, which tunneling interactions are inherently sensitive to. Here we directly image lattice-aperiodic valley interference between coupled atoms in silicon using scanning tunneling microscopy. Our atomistic analysis unveils the role of envelope anisotropy, valley interference and dopant placement on the Heisenberg spin exchange interaction. We find that the exchange can become immune to valley interference by engineering in-plane dopant placement along specific crystallographic directions. A vacuum-like behaviour is recovered, where the exchange is maximised to the overlap between the donor orbitals, and pair-to-pair variations limited to a factor of less than 10 considering the accuracy in dopant positioning. This robustness remains over a large range of distances, from the strongly Coulomb interacting regime relevant for high-fidelity quantum computation to strongly coupled donor arrays of interest for quantum simulation in silicon. © 2021, CC BY.

关键词： Landforms

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Peri-Net: Analysis of Crack Patterns Using Deep Neural Networks

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Journal of Peridynamics and Nonlocal Modeling 2019年第2期1卷 131-142页

作者： Kim, Moonseop Winovich, Nick Lin, Guang Jeong, Wontae School of Mechanical Engineering Purdue University 585 Purdue Mall West Lafayette 47907-2088 IN United States Department of Mathematics Purdue University 150 N. University Street West Lafayette 47907-2067 IN United States Department of Statistics (by courtesy) Purdue University 150 N. University Street West Lafayette 47907-2067 IN United States School of Mathematics and Statistics Nanjing University of Information Science and Technology Nanjing 210044 China School of Electrical and Computer Engineering Purdue University 465 Northwestern Ave West Lafayette 47907 IN United States

In this work, we introduce convolutional neural networks designed to predict and analyze damage patterns on a disk resulting from molecular dynamic (MD) collision simulations. The simulations under consideration are specifically designed to produce cracks on the disk and, accordingly, numerical methods which require partial derivative information, such as finite element analysis, are not applicable. These simulations can, however, be carried out using peridynamics, a nonlocal extension of classical continuum mechanics based on integral equations which overcome the difficulties in modeling deformation discontinuities. Although this nonlocal extension provides a highly accurate model for the MD simulations, the computational complexity and corresponding run times increase greatly as the simulations grow larger. We propose the use of neural network approximations to complement peridynamic simulations by providing quick estimates which maintain much of the accuracy of the full simulations while reducing simulation times by a factor of 1500. We propose two distinct convolutional neural networks: one trained to perform the forward problem of predicting the damage pattern on a disk provided the location of a colliding object’s impact, and another trained to solve the inverse problem of identifying the collision location, angle, velocity, and size given the resulting damage pattern. © 2019, Springer Nature Switzerland AG.

关键词： Convolutional neural networks Crack patterns Machine learning Molecular dynamic simulation Peridynamics

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Understanding the skill provision in gig economy from a network perspective: A case study of fiverr

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Proceedings of the ACM on Human-computer Interaction 2019年第CSCW期3卷 1-23页

作者： Huang, Keman Yao, Jinhui Yin, Ming Sloan School of Management Massachusetts Institute of Technology 245 First Street E94-15th Floor CambridgeMA02142 United States School of Electrical and Information Engineering University of Sydney Sydney Australia Department of Computer Science Purdue University West LafayetteMA47907 United States

The recent emergence of gig economy facilitates the exchange of skilled labor by allowing workers to showcase and sell their skills to a global market. Despite the recent effort on thoroughly examining who workers in gig economy are and what their experience in gig economy are like, our knowledge on how exactly workers provide their skills in gig economy, and how worker’s strategies of providing and expanding skills relate to their success in gig economy is still lacking. In this paper, we conduct a case study on a prominent gig economy platform, ***, to better understand the provision of skills on it through large-scale, data-driven analysis. In particular, we propose the concept of "skill space" from a network perspective to characterize the relationship between different skills by measuring how frequently workers provide different skills together. Through our analysis, we reveal interesting patterns in worker’s provision of skills on Fiverr. We then show how these patterns change over time and differ across subgroups of workers with different characteristics. In addition, we find that providing a set of skills that are highly-related with each other correlates with a better overall performance in gig economy, and when workers expand their skillsets, expanding to a new skill that is highly-related to the existing skills takes less time and is associated with better performance on the new skill. We conclude by discussing the implications of our findings for gig economy workers and platform in general. © 2019 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： International trade

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Deep CNN-based methods to evaluate neighborhood-scale urban valuation through street scenes perception 3

Deep CNN-based methods to evaluate neighborhood-scale urban ...

引用

3rd IEEE International Conference on Data Science in Cyberspace, DSC 2018

作者： Zhao, Junhan Liu, Xiang Kuang, Yanqun Chen, Yingjie Victor Yang, Baijian Computer Graphics Technology Purdue University West LafayetteIN United States Computer and Information Technology Purdue University West LafayetteIN United States

ISBN: (纸本)9781538642108

Social data from city level provides unprecedented opportunities to identify urban attributes from various angles. Citizens are likely to evaluate the quality of the neighborhood and make important decisions by their perceptions and the feedback from the environment. In this paper, we studied the correlation between the neighborhood's environment with their properties values and land values. It is profitable to train the algorithm by parallel deep convolutional neural networks on the visual urban scenes data associated with quantitative non-visual urban characteristics in the same views. The result of our approach defines a scenarized profile from building-level details to city-level traits. The main contribution of this work is providing a unique and more accurate perspective to urban valuation estimations, by integrating the scattered sources of pieces of information and implanting into the available images. This urban evaluation approach will be more human-centered, which can be extended to help urban planners and citizens to explore the significant impacts on city decision optimization or spatial economics-related issues like decreasing the cost of properties assessment. © 2018 IEEE.

关键词： Deep neural networks

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