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Found 24 papers, 6 papers with code
Contextual Chart Generation for Cyber Deception
Honeyfiles are a type of honeypot that mimic real, sensitive documents, creating the illusion of the presence of valuable data.
SoK: Can Trajectory Generation Combine Privacy and Utility?
This work focuses on the systematisation of the state-of-the-art generative models for trajectories in the context of the proposed framework.
BotSSCL: Social Bot Detection with Self-Supervised Contrastive Learning
To address these challenges, we propose a novel framework for social Bot detection with Self-Supervised Contrastive Learning (BotSSCL).
Multiple Hypothesis Dropout: Estimating the Parameters of Multi-Modal Output Distributions
In many real-world applications, from robotics to pedestrian trajectory prediction, there is a need to predict multiple real-valued outputs to represent several potential scenarios.
Local Differential Privacy for Smart Meter Data Sharing
In this paper, we propose a novel LDP approach (named LDP-SmartEnergy) that utilizes randomized response techniques with sliding windows to facilitate the sharing of appliance-level energy consumption data over time while not revealing individual users' appliance usage patterns.
False Information, Bots and Malicious Campaigns: Demystifying Elements of Social Media Manipulations
While researchers from various disciplines have investigated different manipulation-triggering elements of OSNs (such as understanding information diffusion on OSNs or detecting automated behavior of accounts), these works have not been consolidated to present a comprehensive overview of the interconnections among these elements.
Discretization-based ensemble model for robust learning in IoT
IoT device identification is the process of recognizing and verifying connected IoT devices to the network.
DualVAE: Controlling Colours of Generated and Real Images
The disentangled representation is obtained by two novel mechanisms: (i) a dual branch architecture that separates image colour attributes from geometric attributes, and (ii) a new ELBO that trains the combined colour and geometry representations.
Transformative Effects of ChatGPT on Modern Education: Emerging Era of AI Chatbots
ChatGPT, an AI-based chatbot, was released to provide coherent and useful replies based on analysis of large volumes of data.
Masked Vector Quantization
Generative models with discrete latent representations have recently demonstrated an impressive ability to learn complex high-dimensional data distributions.
Diverse Multimedia Layout Generation with Multi Choice Learning
In the above example, this would form an unacceptable layout with a logo in the centre.
Machine Learning-based Automatic Annotation and Detection of COVID-19 Fake News
Existing work neglects the presence of bots that act as a catalyst in the spread and focuses on fake news detection in 'articles shared in posts' rather than the post (textual) content.
Deception for Cyber Defence: Challenges and Opportunities
Deception is rapidly growing as an important tool for cyber defence, complementing existing perimeter security measures to rapidly detect breaches and data theft.
Transferable Graph Backdoor Attack
In this paper, we disclose the TRAP attack, a Transferable GRAPh backdoor attack.
Can pre-trained Transformers be used in detecting complex sensitive sentences? -- A Monsanto case study
We experimented with four different categories of documents in the Monsanto dataset and observed that BERT achieves better F2 scores by 24. 13\% to 65. 79\% for GHOST, 30. 14\% to 54. 88\% for TOXIC, 39. 22\% for CHEMI, 53. 57\% for REGUL compared to existing sensitive information detection models.
Is this IoT Device Likely to be Secure? Risk Score Prediction for IoT Devices Using Gradient Boosting Machines
Security risk assessment and prediction are critical for organisations deploying Internet of Things (IoT) devices.
HaS-Nets: A Heal and Select Mechanism to Defend DNNs Against Backdoor Attacks for Data Collection Scenarios
We have witnessed the continuing arms race between backdoor attacks and the corresponding defense strategies on Deep Neural Networks (DNNs).
Energy and Service-priority aware Trajectory Design for UAV-BSs using Double Q-Learning
Next-generation mobile networks have proposed the integration of Unmanned Aerial Vehicles (UAVs) as aerial base stations (UAV-BS) to serve ground nodes.
Recommender Systems for the Internet of Things: A Survey
Recommendation represents a vital stage in developing and promoting the benefits of the Internet of Things (IoT).
STG2Seq: Spatial-temporal Graph to Sequence Model for Multi-step Passenger Demand Forecasting
Multi-step passenger demand forecasting is a crucial task in on-demand vehicle sharing services.
MOF-BC: A Memory Optimized and Flexible BlockChain for Large Scale Networks
To allow for the removal of stored transactions, all keys would need to be stored which complicates key management and storage.
Cryptography and Security
LSB: A Lightweight Scalable BlockChain for IoT Security and Privacy
We explore LSB in a smart home setting as a representative example for broader IoT applications.
Cryptography and Security
MindID: Person Identification from Brain Waves through Attention-based Recurrent Neural Network
The proposed approach is evaluated over 3 datasets (two local and one public).
Human-Computer Interaction
Converting Your Thoughts to Texts: Enabling Brain Typing via Deep Feature Learning of EEG Signals
An electroencephalography (EEG) based Brain Computer Interface (BCI) enables people to communicate with the outside world by interpreting the EEG signals of their brains to interact with devices such as wheelchairs and intelligent robots.
