Conferences & Events

Academic conferences convened by Northeastern faculty, and academic conferences where Northeastern faculty play key roles.

Title

Topic

  • ‘Behind the Scenes: Uncovering TLS and Server Certificate Practice of IoT Device Vendors in the Wild’

    “IoT devices are increasingly used in consumer homes. Despite recent works in characterizing IoT TLS usage for a limited number of in-lab devices, there exists a gap in quantitatively understanding TLS behaviors from devices in the wild and server-side certificate management. To bridge this knowledge gap, we conduct a new measurement study by focusing on the practice of device vendors, through a crowdsourced dataset of network traffic. … Our study highlights potential concerns in the TLS/PKI practice by IoT device vendors.” Find the paper and full list of authors in the Proceedings of the 2023 ACM on Internet Measurement Conference. 

    Learn more

  • ‘BehavIoT: Measuring Smart Home IoT Behavior Using Network-Inferred Behavior Models’

    ,

    “Smart home IoT platforms are typically closed systems, meaning that there is poor visibility into device behavior. Understanding device behavior is important not only for determining whether devices are functioning as expected, but also can reveal implications for privacy, [security and safety]. … In this work, we demonstrate that the vast majority of IoT behavior can indeed be modeled, using a novel multi-dimensional approach that relies only on the (often encrypted) network traffic exchanged by IoT devices.” Find the paper and full list of authors in the Proceedings of the 2023 ACM on Internet Measurement Conference.

    Learn more

    ,
  • ‘Detection of Sexism on Social Media With Multiple Simple Transformers’

    ,

    “Social media platforms have become virtual communication channels, allowing users to voice their thoughts and opinions. However, this openness and features of anonymity have also given rise to the proliferation of harmful and offensive content, including sexism. This research aims at proposing a methodology and explores the use of different simple transformers. …The proposed approach has great scope for the efficient detection of sexist content on social media, aiding in the development of effective content moderation systems.” Find the paper and full list of authors at the CEUR Workshop Proceedings.

    Learn more

  • ‘Localizing Traffic Differentiation’

    “Network neutrality is important for users, content providers, policymakers, and regulators interested in understanding how network providers differentiate performance. … In prior work, WeHe detects differentiation via end-to-end throughput measurements between a client and server but does not isolate the network responsible for it. Differentiation can occur anywhere on the network path between endpoints. … We present a system, WeHeY, built atop WeHe, that can localize traffic differentiation, i.e., obtain concrete evidence that the differentiation happened within the client’s ISP.” Find the paper and full list of authors in the 2023 ACM on Internet Measurement Conference proceedings.

    Learn more

  • ‘An Energy-Efficient Neural Network Accelerator With Improved Protections Against Fault-Attacks’

    “Embedded neural network (NN) implementations are susceptible to misclassification under fault attacks. Injecting strong electromagnetic (EM) pulses is a non-invasive yet detrimental attack that affects the NN operations by (i) causing faults in the NN model/inputs while being read by the NN computation unit and (ii) corrupting NN computations results to cause misclassification eventually. This paper presents the first ASIC demonstration of an energy-efficient NN accelerator with inbuilt fault attack detection.” Find the paper and full list of authors in the European Conference on Solid-State Circuits proceedings.

    Learn more

  • ‘KnitScript: A Domain-Specific Scripting Language for Advanced Machine Knitting’

    “Knitting machines can fabricate complex fabric structures using robust industrial fabrication machines. However, machine knitting’s full capabilities are only available through low-level programming languages that operate on individual machine operations. We present KnitScript, a domain-specific machine knitting scripting language that supports computationally driven knitting designs. KnitScript provides a comprehensive virtual model of knitting machines, giving access to machine-level capabilities as they are needed while automating a variety of tedious and error-prone details.” Find the paper and full list of authors in the Proceedings of the 36th Annual ACM Symposium on User Interface Software and Technology.

    Learn more

    ,
  • ‘A Feasibility Study on the Use of Audio-Based Ecological Momentary Assessment With Persons With Aphasia’

    ,

    “We describe a smartphone/smartwatch system to evaluate anomia in individuals with aphasia by using audio-recording-based ecological momentary assessments. The system delivers object-naming assessments to a participant’s smartwatch, whereby a prompt signals the availability of images of these objects on the watch screen. Participants attempt to speak the names of the images that appear on the watch display out loud and into the watch as they go about their lives.” Find the paper and full list of authors in the Proceedings of the 25th International ACM SIGACCESS Conference on Computers and Accessibility.

    Learn more

    ,
  • ‘E4UnityIntegration-MIT: An Open-Source Unity Plug-in for Collecting Physiological Data Using Empatica E4 During Gameplay’

    “Physiological measurement of player experience during gameplay has been of increasing interest within game research circles. A commonly-used non-invasive wearable device for physiological measurement is the Empatica E4 wristband. … [However,] the E4’s integration with popular game engines such as Unity 3D presents certain challenges due to non-obvious critical bugs in the library and limited documentation applicability within the Unity context. … We present an open-source Unity plug-in designed to mitigate the challenges associated with integrating the E4 into Unity projects.” Find the paper and authors list at the 36th Annual ACM Symposium on User Interface Software and Technology adjunct…

    Learn more

    ,
  • ‘Inclusive Portraits: Race-Aware Human-in-the-Loop Technology’

    “AI has revolutionized the … automatic facial verification of people. Automated approaches … can face challenges when processing content from certain communities, including communities of people of color. This challenge has prompted the adoption of ‘human-in-the-loop’ (HITL) approaches, where human workers collaborate with the AI to minimize errors. However, most HITL approaches do not consider workers’ individual characteristics and backgrounds. This paper proposes a new approach … that connects with social theories around race to design a racially-aware human-in-the-loop system.” Find the paper and authors list at the 3rd ACM Conference on Equity and Access in Algorithms, Mechanisms and Optimization…

    Learn more

    ,
  • ‘FibeRobo: Fabricating 4D Fiber Interfaces by Continuous Drawing of Temperature Tunable Liquid Crystal Elastomers’

    ,

    “We present FibeRobo, a thermally-actuated liquid crystal elastomer (LCE) fiber that can be embedded or structured into textiles and enable silent and responsive interactions with shape-changing, fiber-based interfaces. … This paper contributes to developing temperature-responsive LCE fibers, a facile and scalable fabrication pipeline with optional heating element integration for digital control, mechanical characterization and the establishment of higher hierarchical textile structures and design space. Finally, we introduce a set of demonstrations that illustrate the design space FibeRobo enables.” Find the paper and full list of authors in the 36th Annual ACM Symposium on User Interface Software and Technology proceedings.

    Learn more

    ,
  • ‘Rethinking Neighborhood Consistency Learning on Unsupervised Domain Adaptation’

    “Unsupervised domain adaptation (UDA) involves predicting unlabeled data in a target domain by using labeled data from the source domain. However, recent advances in pseudo-labeling (PL) methods have been hampered by noisy pseudo-labels. … Although neighborhood-based PL can help preserve the local structure, it also risks assigning the whole local neighborhood to the wrong semantic category. To address this issue, we propose a novel framework called neighborhood consistency learning (NCL) that operates at both the semantic and instance levels and features a new consistency objective function.” Find the paper and authors list in the 31st ACM International Conference on Multimedia…

    Learn more

  • ‘In the Room Where It Happens: Characterizing Local Communication and Threats in Smart Homes’

    ,

    “The network communication between Internet of Things (IoT) devices on the same local network has significant implications for platform and device interoperability, security, privacy and correctness. Yet, the analysis of local home Wi-Fi network traffic and its associated security and privacy threats have been largely ignored by prior literature. … In this paper, we present a comprehensive and empirical measurement study to shed light on the local communication within a smart home deployment and its threats.” Find the paper and full list of authors at the 2023 ACM on Internet Measurement Conference proceedings.

    Learn more

    ,
  • ‘Tracking, Profiling and Ad Targeting in the Alexa Echo Smart Speaker Ecosystem’

    ,

    “Smart speakers collect voice commands, which can be used to infer sensitive information about users. Given the potential for privacy harms, there is a need for greater transparency and control over the data collected, used and shared by smart speaker platforms as well as third party skills supported on them. To bridge this gap, we build a framework to measure data collection, usage, and sharing by the smart speaker platforms. … Our results show that Amazon and third parties … collect smart speaker interaction data.” Find the paper and full list of authors at the 2023 ACM on Internet Measurement…

    Learn more

    ,
  • ‘Medical Imaging RPA System Design’

    “Robotic Process Automation (RPA) can minimize human errors, improve efficiency and create a seamless operational environment in the healthcare industry. This paper examines the existing radiology imaging requisition system, which requires human labourers to perform medical request processing and classification. To improve this slow, error-prone and hard-to-scale process, we design an RPA approach that significantly improves efficiency.” Find the paper and full list of authors in the Canadian Conference on Electrical and Computer Engineering proceedings.

    Learn more

    ,
  • ‘AI-Based General Visual Inspection of Aircrafts Based on YOLOv5’

    “Safety is the cornerstone on which the commercial airline industry is built. … The time required for general visual inspections of aircraft can be drastically reduced by using deep learning and remotely piloted aircraft systems (RPAS). Deep learning techniques can be used in aircraft maintenance thanks to the availability of Graphic Processing Units. In our proof of concept study, we use YOLOv5 to build a model that uses high-quality data to find five different aircraft flaws.” Find the paper and full list of authors at the 2023 Canadian Conference on Electrical and Computer Engineering proceedings.

    Learn more

  • ‘Robust Client and Server State Synchronisation Framework For React Applications: React-State-Sync’

    “As the front-end web frameworks ecosystem evolves, we have encountered problems managing client data. Not only are the solutions for this problem diverse, but the problem too has devolved into two parts — client-side state and server-side state. … Our goal is to provide a consolidated architecture that ensures a full sync between the two states while being performant and developer friendly. Based on our tests against React Context API, we increased the dispatch performance by over 400%.” Find the paper and full list of authors at the 2023 Canadian Conference on Electrical and Computer Engineering proceedings.

    Learn more

  • Northeastern welcomes researchers from around the globe for Genome Interpretation Workshop

    “After years of involvement with the Critical Assessment of Genome Interpretation (CAGI), and after co-chairing the group’s most recent conference in 2022, Predrag Radivojac, professor of computer science and associate dean of research, finally got his chance to welcome the group to Boston and to Northeastern. Beginning on Friday, September 29 and continuing through the weekend, nearly 100 computational genomics and biomedical researchers flocked to the top floor of Northeastern’s East Village to catch up on the latest research and evaluate the challenges that remain.”

    Learn more

    ,
  • ‘The Apocalyptic Nature of Rivalry Violence and the Need for a New Research Agenda’

    Claudio Lanza, assistant professor in international Relations and sociology at Northeastern University London, gave a talk on Tuesday, Nov. 7, 2023. The talk was hosted at the Brudnick Center for Violence and Conflict.

    Learn more

    ,
  • Maria Ivanova receives Global Green Mentor award at Climate Week NYC — but she’s just getting started

    Maria Ivanova, director of the School of Public Policy and Urban Affairs at Northeastern University, received the Global Green Mentor award during Climate Week NYC 2023 in recognition of her work in education and environmental governance.

    Learn more

    ,
  • ‘From 5G Sniffing to Harvesting Leakages of Privacy-Preserving Messengers’

    “We present the first open-source tool capable of efficiently sniffing 5G control channels, 5GSniffer and demonstrate its potential to conduct attacks on users privacy. 5GSniffer builds on our analysis of the 5G RAN control channel exposing side-channel leakage. We note that decoding the 5G control channels is significantly more challenging than in LTE. … We devise a set of techniques to achieve real-time control channels sniffing (over three orders of magnitude faster than brute-forcing).” Find the paper and full list of authors at the 2023 IEEE Symposium on Security and Privacy.

    Learn more

    ,
  • ‘An Efficient Algorithm for Fair Multi-Agent Multi-Armed Bandit With Low Regret’

    “Recently a multi-agent variant of the classical multi-armed bandit was proposed to tackle fairness issues in online learning. Inspired by a long line of work in social choice and economics, the goal is to optimize the Nash social welfare instead of the total utility. Unfortunately previous algorithms either are not efficient or achieve sub-optimal regret in terms of the number of rounds. We propose a new efficient algorithm with lower regret than even previous inefficient ones.” Find the paper and full list of authors in the Proceedings of the AAAI Conference on Artificial Intelligence.

    Learn more

  • ‘8th International Workshop on Mental Health and Well-being: Sensing and Intervention’

    “Mental health and well-being are critical components of overall health. … Detecting symptoms of mental illness early-on and delivering interventions to prevent and/or manage symptoms can improve health and well-being outcomes. Ubiquitous systems are increasingly playing a central role in uncovering clinically relevant contextual information on mental health. … The goal of this workshop is to bring together researchers, practitioners, and industry professionals interested in identifying, articulating, and addressing such issues and opportunities.” Find the paper and authors list in the 2023 ACM International Joint Conference on Pervasive and Ubiquitous Computing and the 2023 ACM International Symposium on Wearable Computing…

    Learn more

    ,
  • ‘Black-box Attacks Against Neural Binary Function Detection’

    ,

    “Binary analyses based on deep neural networks (DNNs), or neural binary analyses (NBAs), have become a hotly researched topic in recent years. DNNs have been wildly successful at pushing the performance and accuracy envelopes in the natural language and image processing domains. … [However,] in this paper, we empirically demonstrate that the current state of the art in neural function boundary detection is vulnerable to both inadvertent and deliberate adversarial attacks.” Find the paper and full list of authors in the Proceedings of the 26th International Symposium on Research in Attacks, Intrusions and Defenses.

    Learn more

    ,
  • ‘StereoVoxelNet: Real-Time Obstacle Detection Based on Occupancy Voxels from a Stereo Camera Using Deep Neural Networks’

    , ,

    “Obstacle detection is a safety-critical problem in robot navigation, where stereo matching is a popular vision-based approach. While deep neural networks have shown impressive results in computer vision, most of the previous obstacle detection works only leverage traditional stereo matching techniques to meet the computational constraints for real-time feedback. This paper proposes a computationally efficient method that employs a deep neural network to detect occupancy from stereo images directly. … Our approach extracts the compact obstacle distribution based on volumetric representations.” Find the paper and full list of authors in the 2023 IEEE International Conference on Robotics and Automation proceedings.

    Learn more

    ,
  • ‘High-Throughput Microscopy Image Deblurring With Graph Reasoning Attention Network’

    “High-quality (HQ) microscopy images afford more detailed information for modern life science research and quantitative image analyses. However, in practice, HQ microscopy images are not commonly available or suffer from blurring artifacts. Compared with natural images, such low-quality (LQ) microscopy ones often share some visual characteristics: more complex structures, less informative background, and repeating patterns. … To address those problems, we collect HQ electron microscopy and histology datasets and propose a graph reasoning attention network (GRAN).” Find the paper and full list of authors in the 2023 IEEE 20th International Symposium on Biomedical Imaging proceedings.

    Learn more

  • ‘NeRFInvertor: High Fidelity NeRF-GAN Inversion for Single-Shot Real Image Animation’

    “Nerf-based Generative models have shown impressive capacity in generating high-quality images with consistent 3D geometry. Despite successful synthesis of fake identity images randomly sampled from latent space, adopting these models for generating face images of real subjects is still a challenging task due to its so-called inversion issue. In this paper, we propose a universal method to surgically finetune these NeRF-GAN models in order to achieve high-fidelity animation of real subjects only by a single image.” Find the paper and full list of authors in the 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition proceedings.

    Learn more

  • ‘Viper: A Fast Snapshot Isolation Checker’

    “Snapshot isolation (SI) is supported by most commercial databases and is widely used by applications. However, checking SI today — given a set of transactions, checking if they obey SI — is either slow or gives up soundness. We present viper, an SI checker that is sound, complete and fast. Viper checks black-box databases and hence is transparent to both users and databases. To be fast, viper introduces BC-polygraphs, a new representation of transaction dependencies.” Find the paper and full list of authors in the Proceedings of the Eighteenth European Conference on Computer Systems.

    Learn more

  • ‘Framing Frames: Bypassing Wi-Fi Encryption by Manipulating Transmit Queues’

    “Wi-Fi devices routinely queue frames at various layers of the network stack before transmitting, for instance, when the receiver is in sleep mode. In this work, we investigate how Wi-Fi access points manage the security context of queued frames. By exploiting power-save features, we show how to trick access points into leaking frames in plaintext, or encrypted using the group or an all-zero key. We demonstrate resulting attacks against several open-source network stacks.” Find the paper and full list of authors in the 32nd USENIX Security Symposium proceedings.

    Learn more

    ,
  • ‘La Independiente: Designing Ubiquitous Systems for Latin American and Caribbean Women Crowdworkers’

    “Since 2018, Venezuelans have contributed to 75% of leading AI crowd work platforms’ total workforce. … Few initiatives have investigated the impact of such work in the Global South through the lens of feminist theory. … We surveyed 55 LAC women on the crowd work platform Toloka to understand their personal goals, professional values and hardships. … Most participants shared a desire to hear the experiences of other women crowdworkers.” Find the paper and full list of authors in the Adjunct Proceedings of the 2023 ACM International Joint Conference on Pervasive and Ubiquitous Computing and the International Symposium on Wearable…

    Learn more

    ,
  • ‘SCORE: A Second-Order Conic Initialization for Range-Aided SLAM’

    “We present a novel initialization technique for the range-aided simultaneous localization and mapping (RA-SLAM) problem. In RA-SLAM we consider measurements of point-to-point distances in addition to measurements of rigid transformations to landmark or pose variables. Standard formulations of RA-SLAM approach the problem as non-convex optimization, which requires a good initialization to obtain quality results. The initialization technique proposed here relaxes the RA-SLAM problem to a convex problem which is then solved to determine an initialization for the original, non-convex problem.” Find the paper and full list of authors in the IEEE International Conference on Robotics and Automation proceedings.

    Learn more