Search Results for author: Kim-Kwang Raymond Choo

Found 19 papers, 6 papers with code

A Survey of Machine Learning Techniques in Adversarial Image Forensics

1 code implementation19 Oct 2020 Ehsan Nowroozi, Ali Dehghantanha, Reza M. Parizi, Kim-Kwang Raymond Choo

Image forensic plays a crucial role in both criminal investigations (e. g., dissemination of fake images to spread racial hate or false narratives about specific ethnicity groups) and civil litigation (e. g., defamation).

BIG-bench Machine Learning Image Forensics

Generating Image Adversarial Examples by Embedding Digital Watermarks

2 code implementations14 Aug 2020 Yuexin Xiang, Tiantian Li, Wei Ren, Tianqing Zhu, Kim-Kwang Raymond Choo

We devise an efficient mechanism to select host images and watermark images and utilize the improved discrete wavelet transform (DWT) based Patchwork watermarking algorithm with a set of valid hyperparameters to embed digital watermarks from the watermark image dataset into original images for generating image adversarial examples.

BABD: A Bitcoin Address Behavior Dataset for Pattern Analysis

1 code implementation10 Apr 2022 Yuexin Xiang, Yuchen Lei, Ding Bao, Wei Ren, Tiantian Li, Qingqing Yang, Wenmao Liu, Tianqing Zhu, Kim-Kwang Raymond Choo

Cryptocurrencies are no longer just the preferred option for cybercriminal activities on darknets, due to the increasing adoption in mainstream applications.

GE-AdvGAN: Improving the transferability of adversarial samples by gradient editing-based adversarial generative model

1 code implementation11 Jan 2024 Zhiyu Zhu, Huaming Chen, Xinyi Wang, Jiayu Zhang, Zhibo Jin, Kim-Kwang Raymond Choo, Jun Shen, Dong Yuan

With the functional and characteristic similarity analysis, we introduce a novel gradient editing (GE) mechanism and verify its feasibility in generating transferable samples on various models.

Adversarial Attack

A Lightweight Privacy-Preserving Scheme Using Label-based Pixel Block Mixing for Image Classification in Deep Learning

1 code implementation19 May 2021 Yuexin Xiang, Tiantian Li, Wei Ren, Tianqing Zhu, Kim-Kwang Raymond Choo

Experimental findings on the testing set show that our scheme preserves image privacy while maintaining the availability of the training set in the deep learning models.

Data Augmentation Image Classification +1

Greening Cloud-Enabled Big Data Storage Forensics: Syncany as a Case Study

no code implementations27 Jul 2018 Yee-Yang Teing, Ali Dehghantanha, Kim-Kwang Raymond Choo

The pervasive nature of cloud-enabled big data storage solutions introduces new challenges in the identification, collection, analysis, preservation and archiving of digital evidences.

Cryptography and Security

CloudMe Forensics: A Case of Big-Data Investigation

no code implementations26 Jul 2018 Yee-Yang Teing, Ali Dehghantanha, Kim-Kwang Raymond Choo

The issue of increasing volume, variety and velocity of has been an area of concern in cloud forensics.

Cryptography and Security

Digital forensic investigation of two-way radio communication equipment and services

no code implementations22 Jul 2018 Arie Kouwen, Mark Scanlon, Kim-Kwang Raymond Choo, Nhien-An Le-Khac

To date, there is little research on the digital traces in modern radio communication equipment.

Cryptography and Security Computers and Society

Honeypots for employee information security awareness and education training: A conceptual EASY training model

no code implementations25 Jun 2017 Lek Christopher, Kim-Kwang Raymond Choo, Ali Dehghantanha

This paper then examines how analysis of honeypot data can be used in employee information security awareness and education training.

Cryptography and Security Computers and Society

Performance of Android Forensics Data Recovery Tools

no code implementations15 Sep 2017 Bernard Chukwuemeka Ogazi-Onyemaechi, Ali Dehghantanha, Kim-Kwang Raymond Choo

Recovering deleted or hidden data is among most important duties of forensics investigators.

Cryptography and Security

Mobile Cloud Forensics: An Analysis of Seven Popular Android Apps

no code implementations18 Jun 2015 Ben Martini, Quang Do, Kim-Kwang Raymond Choo

Using the evidence collection and analysis methodology for Android devices proposed by Martini, Do and Choo, we examined and analyzed seven popular Android cloud-based apps.

Computers and Society Cryptography and Security

Pocket Diagnosis: Secure Federated Learning against Poisoning Attack in the Cloud

no code implementations23 Sep 2020 Zhuoran Ma, Jianfeng Ma, Yinbin Miao, Ximeng Liu, Kim-Kwang Raymond Choo, Robert H. Deng

Previous works on federated learning have been inadequate in ensuring the privacy of DIs and the availability of the final federated model.

Cryptography and Security

DeepKeyGen: A Deep Learning-based Stream Cipher Generator for Medical Image Encryption and Decryption

no code implementations21 Dec 2020 Yi Ding, Fuyuan Tan, Zhen Qin, Mingsheng Cao, Kim-Kwang Raymond Choo, Zhiguang Qin

In this paper, a novel deep learning-based key generation network (DeepKeyGen) is proposed as a stream cipher generator to generate the private key, which can then be used for encrypting and decrypting of medical images.

Generative Adversarial Network

Poisoning Attacks in Federated Edge Learning for Digital Twin 6G-enabled IoTs: An Anticipatory Study

no code implementations21 Mar 2023 Mohamed Amine Ferrag, Burak Kantarci, Lucas C. Cordeiro, Merouane Debbah, Kim-Kwang Raymond Choo

However, we need to also consider the potential of attacks targeting the underlying AI systems (e. g., adversaries seek to corrupt data on the IoT devices during local updates or corrupt the model updates); hence, in this article, we propose an anticipatory study for poisoning attacks in federated edge learning for digital twin 6G-enabled IoT environments.

Federated Learning Privacy Preserving

Towards Understanding the Generalization of Medical Text-to-SQL Models and Datasets

no code implementations22 Mar 2023 Richard Tarbell, Kim-Kwang Raymond Choo, Glenn Dietrich, Anthony Rios

To show this, we create new splits of the existing medical text-to-SQL dataset MIMICSQL that better measure the generalizability of the resulting models.

Data Augmentation Text-To-SQL

VFedMH: Vertical Federated Learning for Training Multiple Heterogeneous Models

no code implementations20 Oct 2023 Shuo Wang, Keke Gai, Jing Yu, Liehuang Zhu, Kim-Kwang Raymond Choo, Bin Xiao

Then the passive party, who owns only features of the sample, injects the blinding factor into the local embedding and sends it to the active party.

Vertical Federated Learning

MFABA: A More Faithful and Accelerated Boundary-based Attribution Method for Deep Neural Networks

1 code implementation21 Dec 2023 Zhiyu Zhu, Huaming Chen, Jiayu Zhang, Xinyi Wang, Zhibo Jin, Minhui Xue, Dongxiao Zhu, Kim-Kwang Raymond Choo

To better understand the output of deep neural networks (DNN), attribution based methods have been an important approach for model interpretability, which assign a score for each input dimension to indicate its importance towards the model outcome.

FairCompass: Operationalising Fairness in Machine Learning

no code implementations27 Dec 2023 Jessica Liu, Huaming Chen, Jun Shen, Kim-Kwang Raymond Choo

As artificial intelligence (AI) increasingly becomes an integral part of our societal and individual activities, there is a growing imperative to develop responsible AI solutions.

Fairness Subgroup Discovery

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