366 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- NortonLifeLock (Ireland)IE3 papers
- Commonwealth Scientific and Industrial Research OrganisationAU2 papers
- Data61AU2 papers
- Georgia Institute of TechnologyUS2 papers
- King Abdullah University of Science and TechnologySA2 papers
- The University of QueenslandAU2 papers
- Boston UniversityUS1 paper
- Cambridge Cognition (United Kingdom)GB1 paper
- Carnegie Mellon UniversityUS1 paper
- Duke UniversityUS1 paper
- Goddard Space Flight CenterUS1 paper
- Indraprastha Institute of Information Technology DelhiIN1 paper
19 papers
Marked for Disruption: Tracing the Evolution of Malware Delivery Operations Targeted for Takedown
Colin C. Ife, Yun Shen, Steven J. Murdoch +1
The malware and botnet phenomenon is among the most significant threats to cybersecurity today. Consequently, law enforcement agencies, security companies, and researchers are cons…
ANDRUSPEX : Leveraging Graph Representation Learning to Predict Harmful App Installations on Mobile Devices
Yun Shen, Gianluca Stringhini
Android's security model severely limits the capabilities of anti-malware software. Unlike commodity anti-malware solutions on desktop systems, their Android counterparts run as sa…
Malware Makeover: Breaking ML-based Static Analysis by Modifying Executable Bytes
Keane Lucas, Mahmood Sharif, Lujo Bauer +2
Motivated by the transformative impact of deep neural networks (DNNs) in various domains, researchers and anti-virus vendors have proposed DNNs for malware detection from raw bytes…
Deep Detector Health Management under Adversarial Campaigns
Javier Echauz, Keith Kenemer, Sarfaraz Hussein +4
Machine learning models are vulnerable to adversarial inputs that induce seemingly unjustifiable errors. As automated classifiers are increasingly used in industrial control system…
Collaborative Graph Walk for Semi-supervised Multi-Label Node Classification
Uchenna Akujuobi, Han Yufei, Qiannan Zhang +1
In this work, we study semi-supervised multi-label node classification problem in attributed graphs. Classic solutions to multi-label node classification follow two steps, first le…
Recurrent Attention Walk for Semi-supervised Classification
Uchenna Akujuobi, Qiannan Zhang, Han Yufei +1
In this paper, we study the graph-based semi-supervised learning for classifying nodes in attributed networks, where the nodes and edges possess content information. Recent approac…
ATTACK2VEC: Leveraging Temporal Word Embeddings to Understand the Evolution of Cyberattacks
Yun Shen, Gianluca Stringhini
Despite the fact that cyberattacks are constantly growing in complexity, the research community still lacks effective tools to easily monitor and understand them. In particular, th…
Secure and Utility-Aware Data Collection with Condensed Local Differential Privacy
Mehmet Emre Gursoy, Acar Tamersoy, Stacey Truex +2
Local Differential Privacy (LDP) is popularly used in practice for privacy-preserving data collection. Although existing LDP protocols offer high utility for large user populations…
Siamese Networks for Semantic Pattern Similarity
Yassine Benajiba, Jin Sun, Yong Zhang +3
Semantic Pattern Similarity is an interesting, though not often encountered NLP task where two sentences are compared not by their specific meaning, but by their more abstract sema…
Detecting DGA domains with recurrent neural networks and side information
Ryan R. Curtin, Andrew B. Gardner, Slawomir Grzonkowski +2
Modern malware typically makes use of a domain generation algorithm (DGA) to avoid command and control domains or IPs being seized or sinkholed. This means that an infected system…
Gradient Similarity: An Explainable Approach to Detect Adversarial Attacks against Deep Learning
Jasjeet Dhaliwal, Saurabh Shintre
Deep neural networks are susceptible to small-but-specific adversarial perturbations capable of deceiving the network. This vulnerability can lead to potentially harmful consequenc…
A User-Friendly Hybrid Sparse Matrix Class in C++
Conrad Sanderson, Ryan Curtin
When implementing functionality which requires sparse matrices, there are numerous storage formats to choose from, each with advantages and disadvantages. To achieve good performan…
Lung and Pancreatic Tumor Characterization in the Deep Learning Era: Novel Supervised and Unsupervised Learning Approaches
Sarfaraz Hussein, Pujan Kandel, Candice W. Bolan +2
Risk stratification (characterization) of tumors from radiology images can be more accurate and faster with computer-aided diagnosis (CAD) tools. Tumor characterization through suc…
Practical Attacks Against Graph-based Clustering
Yizheng Chen, Yacin Nadji, Athanasios Kountouras +4
Graph modeling allows numerous security problems to be tackled in a general way, however, little work has been done to understand their ability to withstand adversarial attacks. We…
An Open Source C++ Implementation of Multi-Threaded Gaussian Mixture Models, k-Means and Expectation Maximisation
Conrad Sanderson, Ryan Curtin
Modelling of multivariate densities is a core component in many signal processing, pattern recognition and machine learning applications. The modelling is often done via Gaussian m…
Detecting Adversarial Samples from Artifacts
Reuben Feinman, Ryan R. Curtin, Saurabh Shintre +1
Deep neural networks (DNNs) are powerful nonlinear architectures that are known to be robust to random perturbations of the input. However, these models are vulnerable to adversari…
Comparing Speech and Keyboard Text Entry for Short Messages in Two Languages on Touchscreen Phones
Sherry Ruan, Jacob O. Wobbrock, Kenny Liou +2
With the ubiquity of mobile touchscreen devices like smartphones, two widely used text entry methods have emerged: small touch-based keyboards and speech recognition. Although spee…
Analyzing Social and Stylometric Features to Identify Spear phishing Emails
Prateek Dewan, Anand Kashyap, Ponnurangam Kumaraguru
Spear phishing is a complex targeted attack in which, an attacker harvests information about the victim prior to the attack. This information is then used to create sophisticated,…
IRTS observation of the near-infrared extragalactic background light
T. Matsumoto, S. Matsuura, H. Murakami +6
We searched for near-infrared extragalactic background light (EBL) in the data from the Near-InfraRed Spectrometer (NIRS) on the Infrared Telescope in Space (IRTS). After subtracti…