78 citations · 274 across the 28 of their papers we have counts for
16 papers · 1 filter
Towards Automated Generation of Smart Grid Cyber Range for Cybersecurity Experiments and Training
Daisuke Mashima, Muhammad M. Roomi, Bennet Ng +3
Assurance of cybersecurity is crucial to ensure dependability and resilience of smart power grid systems. In order to evaluate the impact of potential cyber attacks, to assess depl…
Tracing the Origin of Adversarial Attack for Forensic Investigation and Deterrence
Han Fang, Jiyi Zhang, Yupeng Qiu +3
Deep neural networks are vulnerable to adversarial attacks. In this paper, we take the role of investigators who want to trace the attack and identify the source, that is, the part…
Scalable Private Decision Tree Evaluation with Sublinear Communication
Jianli Bai, Xiangfu Song, Shujie Cui +2
Private decision tree evaluation (PDTE) allows a decision tree holder to run a secure protocol with a feature provider. By running the protocol, the feature provider will learn a c…
Mitigating Adversarial Attacks by Distributing Different Copies to Different Users
Jiyi Zhang, Han Fang, Wesley Joon-Wie Tann +3
Machine learning models are vulnerable to adversarial attacks. In this paper, we consider the scenario where a model is distributed to multiple buyers, among which a malicious buye…
Poisoning Online Learning Filters: DDoS Attacks and Countermeasures
Wesley Joon-Wie Tann, Ee-Chien Chang
The recent advancements in machine learning have led to a wave of interest in adopting online learning-based approaches for long-standing attack mitigation issues. In particular, D…
Filtering DDoS Attacks from Unlabeled Network Traffic Data Using Online Deep Learning
Wesley Joon-Wie Tann, Jackie Tan Jin Wei, Joanna Purba +1
DDoS attacks are simple, effective, and still pose a significant threat even after more than two decades. Given the recent success in machine learning, it is interesting to investi…
Defending Model Inversion and Membership Inference Attacks via Prediction Purification
Ziqi Yang, Bin Shao, Bohan Xuan +2
Neural networks are susceptible to data inference attacks such as the model inversion attack and the membership inference attack, where the attacker could infer the reconstruction…
Benefits and Pitfalls of Using Capture the Flag Games in University Courses
Jan Vykopal, Valdemar Švábenský, Ee-Chien Chang
The concept of Capture the Flag (CTF) games for practicing cybersecurity skills is widespread in informal educational settings and leisure-time competitions. However, it is not muc…
Confusing and Detecting ML Adversarial Attacks with Injected Attractors
Jiyi Zhang, Ee-Chien Chang, Hwee Kuan Lee
Many machine learning adversarial attacks find adversarial samples of a victim model by following the gradient of some attack objective functions, either explicitly…
Self-Expiring Data Capsule using Trusted Execution Environment
Hung Dang, Ee-Chien Chang
Data privacy is unarguably of extreme importance. Nonetheless, there exist various daunting challenges to safe-guarding data privacy. These challenges stem from the fact that data…
Effectiveness of Distillation Attack and Countermeasure on Neural Network Watermarking
Ziqi Yang, Hung Dang, Ee-Chien Chang
The rise of machine learning as a service and model sharing platforms has raised the need of traitor-tracing the models and proof of authorship. Watermarking technique is the main…
Adversarial Neural Network Inversion via Auxiliary Knowledge Alignment
Ziqi Yang, Ee-Chien Chang, Zhenkai Liang
The rise of deep learning technique has raised new privacy concerns about the training data and test data. In this work, we investigate the model inversion problem in the adversari…
Fair Marketplace for Secure Outsourced Computations
Hung Dang, Dat Le Tien, Ee-Chien Chang
The cloud computing paradigm offers clients ubiquitous and on demand access to a shared pool of computing resources, enabling the clients to provision scalable services with minima…
Evading Classifiers by Morphing in the Dark
Hung Dang, Yue Huang, Ee-Chien Chang
Learning-based systems have been shown to be vulnerable to evasion through adversarial data manipulation. These attacks have been studied under assumptions that the adversary has c…
Publishing Location Dataset Differential Privately with Isotonic Regression
Chengfang Fang, Ee-Chien Chang
We consider the problem of publishing location datasets, in particular 2D spatial pointsets, in a differentially private manner. Many existing mechanisms focus on frequency counts…
Securing Interactive Sessions Using Mobile Device through Visual Channel and Visual Inspection
Chengfang Fang, Ee-Chien Chang
Communication channel established from a display to a device's camera is known as visual channel, and it is helpful in securing key exchange protocol. In this paper, we study how v…