This paper identifies and analyzes applications in which Large Language Models (LLMs) can make Internet of Things (IoT) networks more intelligent responsive through three case studies from critical topics: DDoS attack detection, macroprogramming over IoT systems, sensor data processing. Our results reveal that the GPT model under few-shot learning achieves 87.6% detection accuracy, whereas fine-tuned increases value to 94.9%. Given a framework, is capable writing scripts using high-level...

This paper considers mobile computation offloading where task completion times are subject to hard deadline constraints. Hard deadlines difficult meet in conventional due the stochastic nature of wireless channels involved. Rather than using binary offload decisions, we permit concurrent remote and local job execution when it is needed ensure deadlines. The addresses this problem for homogeneous Markovian channel models. An online energy-optimal algorithm, OnOpt, proposed. Its energy...

Equipped with sensing, networking, and computing capabilities, Internet of Things (IoT) such as smartphones, wearables, smart speakers, household robots have been seamlessly weaved into our daily lives. Recent advancements in Generative AI exemplified by GPT, LLaMA, DALL-E, Stable Difussion hold immense promise to push IoT the next level. In this article, we share vision views on benefits that brings IoT, discuss some most important applications IoT-related domains. Fully harnessing is a...

We study the airborne transmission risk associated with holding in-person classes on university campuses for original strain and a more contagious variant of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). adopt model in an enclosed room that considers properties, mask efficiency, initial infection probability occupants. Additionally, we effect vaccination spread virus. The presented has been evaluated simulations using fall 2019 (prepandemic) 2020 (hybrid instruction) course...

Pandemic and epidemic diseases such as CoVID-19, SARS-CoV2, Ebola have spread to multiple countries infected thousands of people. Such mainly through person-to-person contacts. Health care authorities recommend contact tracing procedures prevent the a vast population. Although several mobile applications been developed trace contacts, they typically require collection privacy-intrusive information GPS locations, logging privacy-sensitive data on third party server, or additional...

As IoT deployments grow in scale for applications such as smart cities, they face increasing cyber-security threats. In particular, evidenced by the famous Mirai incident and other ongoing threats, large-scale device networks are particularly susceptible to being hijacked used botnets launch distributed denial of service (DDoS) attacks. Real datasets needed train evaluate use machine learning algorithms deep neural detect defend against DDoS We present a dataset from an urban deployment 4060...

Multi-decision mobile computation offloading occurs when a task to be remotely executed is uploaded in separate parts. Since the upload partitioned, decisions are needed determine best time initiate each upload. The multi-decision problem considered for case where execution completion times subject hard deadline constraints and offloads occur over Markovian wireless channel. An online energy-optimal algorithm, Multiopt (Multi-decision Optimum), introduced, whose optimality proven using...

We investigate the application of artificial intelligence to cybersecurity, contribute safe and secure growth internet things (IoT). Specifically, we train evaluate different neural networks models detect distributed denial service (DDoS) attacks in a large-scale IoT system. consider futuristic launched by sophisticated malicious entities that take over multiple nodes are able disguise their intrusion closely mimicking benign traffic network. Using data from prior work, find truncated Cauchy...

We present a novel "Proof of Social Contact" approach to Sybil control that utilizes the analysis digitally signed information about pairwise encounters between mobile devices are logged in distributed ledger. To illustrate approach, we show examples using binary classification techniques under two different adversary detection models, and evaluate them real-world device encounter trace. discuss number open problems future directions could be pursued by researchers field realize improve such...

This paper considers Preemptive Mobile Computation Offloading when concurrent local execution (CLE) is used to guarantee task time constraints. By allowing simultaneous and remote execution, CLE ensures that job deadlines are always satisfied in the face of unforeseen wireless channel conditions. In preemptive offloading case, at start each slot, a decision made either continue or temporarily interrupt offload. mechanism allows system adapt conditions change. The case for homogeneous...

Airborne transmission is now believed to be the primary way that COVID-19 spreads. We study airborne risk associated with holding in-person classes on university campuses. utilize a model for in an enclosed room considers air change rate room, mask efficiency, initial infection probability of occupants, and also activity level occupants. introduce, use our evaluations, metric R <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">0</sub> <sup...

This study introduces a robust solution for the detection of Distributed Denial Service (DDoS) attacks in Internet Things (IoT) systems, leveraging capabilities Graph Convolutional Networks (GCN). By conceptualizing IoT devices as nodes within graph structure, we present mechanism capable operating efficiently even lossy network environments. We introduce various topologies modeling networks and evaluate them detecting tunable futuristic DDoS attacks. studying different levels connection...

This paper identifies and analyzes applications in which Large Language Models (LLMs) can make Internet of Things (IoT) networks more intelligent responsive through three case studies from critical topics: DDoS attack detection, macroprogramming over IoT systems, sensor data processing. Our results reveal that the GPT model under few-shot learning achieves 87.6% detection accuracy, whereas fine-tuned increases value to 94.9%. Given a framework, is capable writing scripts using high-level...

Epidemic diseases bring many challenges to universities. In the case of airborne contagious like COVID-19, health agencies' guidelines recommend that people maintain a physical distance about 2 meters from each other. Enforcing such distancing on university campus means it will potentially take longer for students get into and out classrooms buildings campus. We use real course registration data large US study wait times would encounter enter exit while keeping recommended meter distance,...

As IoT deployments grow in scale for applications such as smart cities, they face increasing cyber-security threats. In particular, evidenced by the famous Mirai incident and other ongoing threats, large-scale device networks are particularly susceptible to being hijacked used botnets launch distributed denial of service (DDoS) attacks. Real datasets needed train evaluate use machine learning algorithms deep neural detect defend against DDoS We present a dataset from an urban deployment 4060...

We present a comprehensive study on applying machine learning to detect distributed Denial of service (DDoS) attacks using large-scale Internet Things (IoT) systems. While prior works and existing DDoS have largely focused individual nodes transmitting packets at high volume, we investigate more sophisticated futuristic that use large numbers IoT devices camouflage their attack by having each node transmit volume typical benign traffic. introduce new correlation-aware architectures take into...

This short paper summarizes our recent/ongoing works [2, 3, 4] on detecting DDoS attacks in IoT systems. In studies, we conducted a thorough examination of using machine learning to detect Distributed Denial Service (DDoS) large-scale Internet Things (IoT) Unlike prior and typical that focus individual nodes transmitting high volumes packets, explored the more sophisticated advanced future use large number devices while hiding attack by having each node transmit at volume mimics benign...