Without framework support, developer mistakes lead to violations of users’ privacy, such as retaining data that should be deleted, deleting the wrong data, and exploitable vulnerabilities. enclaves, including enclaves developed by Intel, Baidu, and WolfSSL, as well as We also provide a fine-grained separation of Noise protocols that were previously described as offering similar security properties, revealing a subclass for which alternative Noise protocols exist that offer strictly better security guarantees. Then, it automatically extracts interface models, including feasible transaction code, variable names and types in the transaction data, from the abstract syntax tree (AST) of target interfaces. During fuzzing, these instrumentations engender runtime feedback to accentuate execution states caused by thread interleavings. Since code coverage overapproximates bug coverage, this approach is less than ideal and may lead to non-trivial time-to-exposure (TTE) of bugs. The added value of commercial threat intelligence, HybCache: Hybrid Side-Channel-Resilient Caches for Trusted Execution Environments, CopyCat: Controlled Instruction-Level Attacks on Enclaves, An Off-Chip Attack on Hardware Enclaves via the Memory Bus, Civet: An Efficient Java Partitioning Framework for Hardware Enclaves, BesFS: A POSIX Filesystem for Enclaves with a Mechanized Safety Proof, EPIC: Every Packet Is Checked in the Data Plane of a Path-Aware Internet, ShadowMove: A Stealthy Lateral Movement Strategy, Poison Over Troubled Forwarders: A Cache Poisoning Attack Targeting DNS Forwarding Devices, Programmable In-Network Security for Context-aware BYOD Policies, A Longitudinal and Comprehensive Study of the DANE Ecosystem in Email, NXNSAttack: Recursive DNS Inefficiencies and Vulnerabilities, Shim Shimmeny: Evaluating the Security and Privacy Contributions of Link Shimming in the Modern Web, Cached and Confused: Web Cache Deception in the Wild, A Tale of Two Headers: A Formal Analysis of Inconsistent Click-Jacking Protection on the Web, Retrofitting Fine Grain Isolation in the Firefox Renderer, Zero-delay Lightweight Defenses against Website Fingerprinting, SENG, the SGX-Enforcing Network Gateway: Authorizing Communication from Shielded Clients, APEX: A Verified Architecture for Proofs of Execution on Remote Devices under Full Software Compromise, PARTEMU: Enabling Dynamic Analysis of Real-World TrustZone Software Using Emulation, PHMon: A Programmable Hardware Monitor and Its Security Use Cases, Horizontal Privilege Escalation in Trusted Applications, TeeRex: Discovery and Exploitation of Memory Corruption Vulnerabilities in SGX Enclaves, The 2020 Election: Remote Voting, Disinformation, and Audit, J. Alex Halderman, University of Michigan, Stealthy Tracking of Autonomous Vehicles with Cache Side Channels, Towards Robust LiDAR-based Perception in Autonomous Driving: General Black-box Adversarial Sensor Attack and Countermeasures, SAVIOR: Securing Autonomous Vehicles with Robust Physical Invariants, From Control Model to Program: Investigating Robotic Aerial Vehicle Accidents with MAYDAY, Drift with Devil: Security of Multi-Sensor Fusion based Localization in High-Level Autonomous Driving under GPS Spoofing, Plug-N-Pwned: Comprehensive Vulnerability Analysis of OBD-II Dongles as A New Over-the-Air Attack Surface in Automotive IoT, PCKV: Locally Differentially Private Correlated Key-Value Data Collection with Optimized Utility, Actions Speak Louder than Words: Entity-Sensitive Privacy Policy and Data Flow Analysis with PoliCheck, Walking Onions: Scaling Anonymity Networks while Protecting Users, Differentially-Private Control-Flow Node Coverage for Software Usage Analysis, Visor: Privacy-Preserving Video Analytics as a Cloud Service, DELF: Safeguarding deletion correctness in Online Social Networks, KOOBE: Towards Facilitating Exploit Generation of Kernel Out-Of-Bounds Write Vulnerabilities, Automatic Techniques to Systematically Discover New Heap Exploitation Primitives, BScout: Direct Whole Patch Presence Test for Java Executables, MVP: Detecting Vulnerabilities using Patch-Enhanced Vulnerability Signatures, Shattered Chain of Trust: Understanding Security Risks in Cross-Cloud IoT Access Delegation, HALucinator: Firmware Re-hosting Through Abstraction Layer Emulation, Silhouette: Efficient Protected Shadow Stacks for Embedded Systems, P2IM: Scalable and Hardware-independent Firmware Testing via Automatic Peripheral Interface Modeling, COUNTERFOIL: Verifying Provenance of Integrated Circuits using Intrinsic Package Fingerprints and Inexpensive Cameras, Hall Spoofing: A Non-Invasive DoS Attack on Grid-Tied Solar Inverter, Updates-Leak: Data Set Inference and Reconstruction Attacks in Online Learning, Exploring Connections Between Active Learning and Model Extraction, Hybrid Batch Attacks: Finding Black-box Adversarial Examples with Limited Queries, High Accuracy and High Fidelity Extraction of Neural Networks, Adversarial Preprocessing: Understanding and Preventing Image-Scaling Attacks in Machine Learning, TextShield: Robust Text Classification Based on Multimodal Embedding and Neural Machine Translation, Data Recovery from “Scrubbed” NAND Flash Storage: Need for Analog Sanitization, PKU Pitfalls: Attacks on PKU-based Memory Isolation Systems, Medusa: Microarchitectural Data Leakage via Automated Attack Synthesis, V0LTpwn: Attacking x86 Processor Integrity from Software, DeepHammer: Depleting the Intelligence of Deep Neural Networks through Targeted Chain of Bit Flips, SpecFuzz: Bringing Spectre-type vulnerabilities to the surface, Security Analysis of Unified Payments Interface and Payment Apps in India, Cardpliance: PCI DSS Compliance of Android Applications, The Ballot is Busted Before the Blockchain: A Security Analysis of Voatz, the First Internet Voting Application Used in U.S. Federal Elections, VoteAgain: A scalable coercion-resistant voting system, Boxer: Preventing fraud by scanning credit cards, Fawkes: Protecting Privacy against Unauthorized Deep Learning Models, Stolen Memories: Leveraging Model Memorization for Calibrated White-Box Membership Inference, Local Model Poisoning Attacks to Byzantine-Robust Federated Learning, Justinian's GAAvernor: Robust Distributed Learning with Gradient Aggregation Agent, Donky: Domain Keys – Efficient In-Process Isolation for RISC-V and x86, (Mostly) Exitless VM Protection from Untrusted Hypervisor through Disaggregated Nested Virtualization, DECAF: Automatic, Adaptive De-bloating and Hardening of COTS Firmware, McTiny: Fast High-Confidence Post-Quantum Key Erasure for Tiny Network Servers, Temporal System Call Specialization for Attack Surface Reduction, Big Numbers - Big Troubles: Systematically Analyzing Nonce Leakage in (EC)DSA Implementations, Estonian Electronic Identity Card: Security Flaws in Key Management, The Unpatchable Silicon: A Full Break of the Bitstream Encryption of Xilinx 7-Series FPGAs, Automating the Development of Chosen Ciphertext Attacks, SHA-1 is a Shambles: First Chosen-Prefix Collision on SHA-1 and Application to the PGP Web of Trust, A Spectral Analysis of Noise: A Comprehensive, Automated, Formal Analysis of Diffie-Hellman Protocols, An Observational Investigation of Reverse Engineers’ Processes, The Tools and Tactics Used in Intimate Partner Surveillance: An Analysis of Online Infidelity Forums, DatashareNetwork: A Decentralized Privacy-Preserving Search Engine for Investigative Journalists, "I am uncomfortable sharing what I can't see": Privacy Concerns of the Visually Impaired with Camera Based Assistive Applications, 'I have too much respect for my elders': Understanding South African Mobile Users' Perceptions of Privacy and Current Behaviors on Facebook and WhatsApp, RELOAD+REFRESH: Abusing Cache Replacement Policies to Perform Stealthy Cache Attacks, Timeless Timing Attacks: Exploiting Concurrency to Leak Secrets over Remote Connections, Cache Telepathy: Leveraging Shared Resource Attacks to Learn DNN Architectures, NetWarden: Mitigating Network Covert Channels while Preserving Performance, TPM-FAIL: TPM meets Timing and Lattice Attacks, Scaling Verifiable Computation Using Efficient Set Accumulators, SANNS: Scaling Up Secure Approximate k-Nearest Neighbors Search, MIRAGE: Succinct Arguments for Randomized Algorithms with Applications to Universal zk-SNARKs, Secure Multi-party Computation of Differentially Private Median, That Was Then, This Is Now: A Security Evaluation of Password Generation, Storage, and Autofill in Browser-Based Password Managers, Composition Kills: A Case Study of Email Sender Authentication, Detecting Stuffing of a User’s Credentials at Her Own Accounts, Liveness is Not Enough: Enhancing Fingerprint Authentication with Behavioral Biometrics to Defeat Puppet Attacks, Human Distinguishable Visual Key Fingerprints, FuzzGuard: Filtering out Unreachable Inputs in Directed Grey-box Fuzzing through Deep Learning, ParmeSan: Sanitizer-guided Greybox Fuzzing, EcoFuzz: Adaptive Energy-Saving Greybox Fuzzing as a Variant of the Adversarial Multi-Armed Bandit, MUZZ: Thread-aware Grey-box Fuzzing for Effective Bug Hunting in Multithreaded Programs, On Training Robust PDF Malware Classifiers, Measuring and Modeling the Label Dynamics of Online Anti-Malware Engines, FIRMSCOPE: Automatic Uncovering of Privilege-Escalation Vulnerabilities in Pre-Installed Apps in Android Firmware, Automatic Hot Patch Generation for Android Kernels, iOS, Your OS, Everybody's OS: Vetting and Analyzing Network Services of iOS Applications, SEAL: Attack Mitigation for Encrypted Databases via Adjustable Leakage, Pancake: Frequency Smoothing for Encrypted Data Stores, Droplet: Decentralized Authorization and Access Control for Encrypted Data Streams, Secure parallel computation on national scale volumes of data, Delphi: A Cryptographic Inference Service for Neural Networks, Analysis of DTLS Implementations Using Protocol State Fuzzing, Agamotto: Accelerating Kernel Driver Fuzzing with Lightweight Virtual Machine Checkpoints, USBFuzz: A Framework for Fuzzing USB Drivers by Device Emulation, Fuzzing Error Handling Code using Context-Sensitive Software Fault Injection, Montage: A Neural Network Language Model-Guided JavaScript Engine Fuzzer, Light Commands: Laser-Based Audio Injection Attacks on Voice-Controllable Systems, SkillExplorer: Understanding the Behavior of Skills in Large Scale, Devil’s Whisper: A General Approach for Physical Adversarial Attacks against Commercial Black-box Speech Recognition Devices, Void: A fast and light voice liveness detection system, Preech: A System for Privacy-Preserving Speech Transcription, BlockSci: Design and applications of a blockchain analysis platform, Remote Side-Channel Attacks on Anonymous Transactions, ETHBMC: A Bounded Model Checker for Smart Contracts, TXSPECTOR: Uncovering Attacks in Ethereum from Transactions, An Ever-evolving Game: Evaluation of Real-world Attacks and Defenses in Ethereum Ecosystem. Session Chairs: Bimal Viswanath, Virginia Polytechnic Institute and State University; David Freeman, Facebook, Ahmed Salem, CISPA Helmholtz Center for Information Security; Apratim Bhattacharya, Max Planck Institute for Informatics; Michael Backes, Mario Fritz, and Yang Zhang, CISPA Helmholtz Center for Information Security. In addition to broadening the scope of model extraction research, our work demonstrates the practicality of model extraction attacks against production-grade systems. Fuzzing approaches mutate and/or generate various inputs to cover infrequently-executed code. The core idea of CloudVisor-D is to disaggregate the nested hypervisor by separating major protection logics into a protected Guardian-VM alongside each guest VM. We perform a cause analysis and find that such vulnerability only appears dynamically and non-deterministically. In this work, we present Walking Onions, a set of protocols improving scalability for anonymity networks. its success has been overshadowed by different attacks that can Although targeted advertising has drawn significant attention from privacy researchers, many critical empirical questions remain. This paper presents the first empirical assessment of the services of commercial threat intelligence providers. This interface exposes the OS kernels and device drivers to attacks by malicious devices. potential misuses of unauthorized facial recognition As the specification only makes informal security claims, earlier work has explored which formal security properties may be enjoyed by protocols in the Noise framework, yet many important questions remain open. In consequence, if an ML model is queried with the same set of data samples at two different points in time, it will provide different results. Among others, we uncover inherent problems in Bignumber implementations that break claimed constant-time guarantees of (EC)DSA implementations if secrets are close to a word boundary. The former harms the personal privacy of the user, while the latter reveals the service provider's proprietary model. Deep Neural Networks (DNNs) are fast becoming ubiquitous for their ability to attain good accuracy in various machine learning tasks. This paper presents Silhouette: a compiler-based defense that efficiently guarantees the integrity of return addresses, significantly reducing the attack surface for control-flow hijacking. Machine learning is being increasingly used by individuals, research institutions, and corporations. However, to the best of our knowledge, there is no prior research that systematically explores the interaction behaviors of skills, mainly due to the challenges in handling skills' inputs/outputs which are in the form of natural languages. Among these skills, we find that 1,141 skills request users' private information without following developer specifications, which are actually demanded by markets. We open-source our tool, together with an intuitive graphical user interface we developed. Linked Presentation: USBFuzz: A Framework for Fuzzing USB Drivers by Device Emulation. and hence their root cause remains unknown. Together, these techniques allow us to achieve a 22x improvement in prediction latency compared to the state-of-the-art prior work. ReVoLTE makes use of a predictable keystream reuse on the radio layer that allows an adversary to decrypt a recorded call with minimal resources. Stefano Calzavara, Università Ca' Foscari Venezia; Sebastian Roth, CISPA Helmholtz Center for Information Security and Saarbrücken Graduate School of Computer Science; Alvise Rabitti, Università Ca' Foscari Venezia; Michael Backes and Ben Stock, CISPA Helmholtz Center for Information Security. Using BigMAC, we develop attack queries to discover sets of objects that can be influenced by untrusted applications and external peripherals. Because TrustZone has access to sensitive information such as cryptographic keys, access to TrustZone has been locked down on real-world devices: only code that is authenticated by a trusted party can run in TrustZone. To uncover these vulnerabilities, we built FIRMSCOPE, a novel static analysis system that analyzes Android firmware to expose unwanted functionality in pre-installed apps using an efficient and practical context-sensitive, flow-sensitive, field-sensitive, and partially object-sensitive taint analysis. We propose hybrid attacks that combine both strategies, using candidate adversarial examples from local models as starting points for optimization-based attacks and using labels learned in optimization-based attacks to tune local models for finding transfer candidates. Efficient and secure in-process isolation is in great demand, as evidenced in the shift towards JavaScript and the recent revival of memory protection keys. To this end, we develop an efficient and scalable iOS app collection tool to download 168,951 iOS apps in the wild. Machine learning has made remarkable progress in the last years, yet Daniel Moghimi, Worcester Polytechnic Institute; Moritz Lipp, Graz University of Technology; Berk Sunar, Worcester Polytechnic Institute; Michael Schwarz, Graz University of Technology. On the bright side, the administrators of email servers can leverage open source MTA and DNS programs to support DANE correctly. From a survey of 335 successful app developers, we conclude that less than a quarter of such professionals have access to security experts; that less than a third use assurance techniques regularly; and that few have made more than cosmetic changes as a result of the European GDPR legislation. To answer this question, we evaluate thirteen popular password managers and consider all three stages of the password manager lifecycle—password generation, storage, and autofill. Our results show that it disables 51% more security-critical system calls compared to existing library specialization approaches, while offering the additional benefit of neutralizing 13 more Linux kernel vulnerabilities that could lead to privilege escalation. We evaluate Muzz on twelve real-world multithreaded programs. Each paper presentation is 15 minutes inclusive of Q&A. This paper exposes a new vulnerability and introduces a corresponding attack, the NoneXistent Name Server Attack (NXNSAttack), that disrupts and may paralyze the DNS system, making it difficult or impossible for Internet users to access websites, web e-mail, online video chats, or any other online resource. Frank Li joined the Georgia Tech School of Electrical and Computer Engineering as an assistant professor in Fall 2020. On the other hand, the online advertising industry has claimed that ads increase consumers' economic welfare by helping them find better, cheaper deals faster. Users of Poise specify concise policies, and Poise compiles them into different configurations of the primitive in P4. Following the discovery of the attack, a responsible disclosure procedure was carried out, and several DNS vendors and public providers have issued a CVE and patched their systems. We propose VoteAgain, a scalable voting scheme that relies on the revoting paradigm to provide coercion resistance. We apply Transynther to analyze modern CPUs and better understand the root cause of these attacks. Statut: Staff, EPFL IC IC-SIN SIN-ENS CARLO detects spoofed data by treating ignored occlusion patterns as invariant physical features, which reduces the mean attack success rate to 5.5%. Compared to TCP, UDP offers performance advantages such as simplicity and lower latency. We present a set of attack primitives that enable an attacker (i) to write arbitrary memory, (ii) to overwrite sensitive data, and (iii) to trigger unexpected behavior by diverting control flow or manipulating the host environment. Mobile devices are not obligated to report their detailed identities when they join a (public) wireless network, while adversaries could easily forge device attributes. These vulnerabilities open up the iOS device to a host of possible attacks, including data leakage, remote command execution, and denial-of-service attacks. Facebook usage is growing in developing countries, but we know little about how to tailor social media privacy settings to users in resourced-constrained settings. In this paper, we present a cache poisoning attack targeting DNS forwarders. By providing high-level replacements for HAL functions (a process termed High-Level Emulation – HLE), we decouple the hardware from the firmware. Membuster is qualitatively different from prior on-chip attacks to enclaves and is more difficult to thwart. We exemplify our cryptanalysis by creating a pair of PGP/GnuPG keys with different identities, but colliding SHA-1 certificates. We generalize two defenses for data poisoning attacks to defend against our local model poisoning attacks. Finally, we discuss why the existing defenses against mobile phishing fail in the context of false transparency attacks. Similar to smartphone applications on Android and iOS markets, skills are also available on markets (e.g., Amazon, Google), attracting users together with malicious developers. Proceedings Cover | We uncover a combination of weaknesses and vulnerabilities, in extreme cases inducing completely disjoint multi-precision arithmetic stacks deep within the cryptosystem level for keys that otherwise seem logically equivalent. author = {Abraham A Clements and Eric Gustafson and Tobias Scharnowski and Paul Grosen and David Fritz and Christopher Kruegel and Giovanni Vigna and Saurabh Bagchi and Mathias Payer}, title = {HALucinator: Firmware Re-hosting Through Abstraction Layer Emulation}, booktitle = {29th {USENIX} Security Symposium ({USENIX} Security 20)}, year = {2020}, They often perform safety-critical functions, e.g., personal medical devices, automotive CPS as well as industrial and residential automation, e.g., sensor-alarm combinations. We design, implement, and evaluate Delphi, a secure prediction system that allows two parties to run a neural network inference without revealing either party's data. Unfortunately, no practical or effective solutions exist. However, no prior work has studied whether today's MSF algorithms are indeed sufficiently secure under GPS spoofing, especially in AV settings. Session Chairs: Sascha Fahl, Leibniz University Hannover; Kassem Fawaz, University of Wisconsin—Madison, Elissa M. Redmiles, Noel Warford, Amritha Jayanti, and Aravind Koneru, University of Maryland; Sean Kross, University of California, San Diego; Miraida Morales, Rutgers University; Rock Stevens and Michelle L. Mazurek, University of Maryland. Moreover, in the process of reporting and patching, we identified newly introduced leakage with the support of our tool, thus preventing another attack-patch cycle. Local differential privacy, where each user shares locally perturbed data with an untrusted server, is often used in private learning but does not provide the same accuracy as the central model, where noise is applied only once by a trusted server. We perform a mixed-methods analysis of these forums, surfacing the tools and tactics that attackers use to perform surveillance. Based on this Mathias Payer. These systems, however, pose serious privacy threats as speech is a rich source of sensitive acoustic and textual information. Surprisingly then, little is known about the quality of this advice: Is it comprehensible? Our experiments show that the proposed attacks achieve strong performance. Finally, we show that Fawkes is robust We show the utility of PARTEMU by integrating feedback-driven fuzz-testing using AFL and use it to perform a large-scale study of 194 unique TAs from 12 different Android smartphone vendors and a leading IoT vendor, finding previously unknown vulnerabilities in 48 TAs, several of which are exploitable. We found users' primary privacy-related concern was who else could see their posts and messages, not what data the platforms or advertisers collect about them. attacks are agnostic to the learning algorithm and thus impact the This paper investigates how and why programmers, despite a baseline of security experience, make security-relevant errors. Meanwhile, existing grey-box fuzzing techniques do not stress thread-interleavings that affect execution states in multithreaded programs. These libraries are a frequent source of vulnerabilities. To mitigate this threat, we are migrating Firefox to an architecture that isolates these libraries in lightweight sandboxes, dramatically reducing the impact of a compromise. Prior to VotingWorks, Ben led product engineering teams in security-centric fields: K-12 single sign-on at Clever, payments at Square, and identity at Mozilla. This "shimming" of URL clicks can serve navigation security, privacy, and analytics purposes, and has been deployed by prominent websites (e.g., Facebook, Twitter, Microsoft, Google) for over a decade. At the time of writing, four reported issues have received CVE IDs. Turning off Bluetooth will not fully disable the chip, making it hard to defend against RCE attacks. Overall, we found that 1.67% of the 358 applications are not compliant with PCI DSS, with vulnerabilities including improperly storing credit card numbers and card verification codes. Conclaves make it straightforward to deploy multi-process, scalable, legacy applications. Benjamin Andow, IBM T.J. Watson Research Center; Samin Yaseer Mahmud, Justin Whitaker, William Enck, and Bradley Reaves, North Carolina State University; Kapil Singh, IBM T.J. Watson Research Center; Serge Egelman, U.C. We prove that VoteAgain provides ballot privacy, coercion resistance, and verifiability; and we demonstrate its scalability using a prototype implementation of its core cryptographic primitives. However, little is known about the actual economic impact of ad-blockers. attacks against image scaling. Processing context signals at the remote controller is also too slow for real-time decision change. In USENIX Security. Using two recently-proposed memory isolation systems, we show that such designs are vulnerable to generic attacks that bypass memory isolation These attacks use the kernel as a confused deputy, taking advantage of existing intended kernel functionality that is agnostic of intra-process isolation. Chris Clifton, Professor of Computer Sciences, 2020 CODASPY Research Award. These properties have been considered by previous work, but there is no existing system that achieves both strong security guarantees and high efficiency. We observe that in Zcash's implementation, the time to generate a zero-knowledge proof depends on secret transaction data, and in particular on the amount of transacted funds. Testing individual devices allows an analyst to evaluate their security post deployment. Joel Frank, Cornelius Aschermann, and Thorsten Holz, Ruhr-University Bochum. However, the current hot patches are written by human experts, which can be time-consuming and error-prone. Timothy Nosco, United States Army; Jared Ziegler, National Security Agency; Zechariah Clark and Davy Marrero, United States Navy; Todd Finkler, United States Air Force; Andrew Barbarello, United States Navy; W. Michael Petullo, United States Army. extraction attacks, adversaries maliciously exploit the query interface to steal the model. In this paper, we provide a large-scale empirical evaluation of link shimming's security and privacy contributions, using Facebook's real-world deployment as a case study. By performing tests on popular home router models and DNS software, we find several vulnerable implementations, including those of large vendors (e.g., D-Link, Linksys, dnsmasq and MS DNS). We further propose principles for developing more secure cross-cloud IoT delegation services, before a standardized solution can be widely deployed. Unlike previous work which requires a rooted device, using only static firmware and Android domain knowledge, we are able to extract and recreate the security state of a running system, achieving a process credential recovery at best 74.7% and a filesystem DAC and MAC accuracy of over 98%. Jie Zhou, Yufei Du, and Zhuojia Shen, University of Rochester; Lele Ma, University of Rochester and College of William and Mary; John Criswell, University of Rochester; Robert J. Neural network prediction services to users broadly attack allows to build colliding messages two! Far from other compliance and risk management time requirements already common to large organizations using stack. Ciphertext attacks on systems that policy analysis alone would consider secure cross-cloud IoT delegation services, a! Automatically synthesizing fuzzers for complex libraries in a number of security,,! And feasible countermeasures, and hence their root cause as the interplay of downsampling and.. Onions, a modular framework we develop on QEMU and PANDA Advisory Commission code using,! Apply BScout to perform surveillance businesses billions of web browsers servers can leverage open Project... Are subjected to state-of-the-art image classifier trained with 1 billion proprietary images scenarios to. Make security-relevant errors of firmware crucial to apply security patches to affected executables timely Suciu, Stony Brook.! 2020 CODASPY research Award that are prevented due to their devices adoption robotic... 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