Literature Database

Malware Detection using Machine Learning and Deep Learning

Authors: Hemant Rathore, Swati Agarwal, Sanjay K. Sahay, Mohit Sewak | Published: 2019-04-04
Machine Learning Algorithm
Machine Learning Application
Deep Learning Method

White-to-Black: Efficient Distillation of Black-Box Adversarial Attacks

Authors: Yotam Gil, Yoav Chai, Or Gorodissky, Jonathan Berant | Published: 2019-04-04
Adversarial attack
Machine Learning Algorithm
Machine Learning Application

Understanding the efficacy, reliability and resiliency of computer vision techniques for malware detection and future research directions

Authors: Li Chen | Published: 2019-04-03
Malware Detection
Future Research
Deep Learning Technology

HopSkipJumpAttack: A Query-Efficient Decision-Based Attack

Authors: Jianbo Chen, Michael I. Jordan, Martin J. Wainwright | Published: 2019-04-03 | Updated: 2020-04-28
Adversarial Example
Adversarial attack
Distance Evaluation Method

Leveraging Electromagnetic Side-Channel Analysis for the Investigation of IoT Devices

Authors: Asanka Sayakkara, Nhien-An Le-Khac, Mark Scanlon | Published: 2019-04-03
IoT-Specific Threats
Signal Processing Techniques
Machine Learning Algorithm

Active Learning for Network Intrusion Detection

Authors: Amir Ziai | Published: 2019-04-02
Active Learning
Data Preprocessing
Machine Learning Application

Building an Efficient Intrusion Detection System Based on Feature Selection and Ensemble Classifier

Authors: Yuyang Zhou, Guang Cheng, Shanqing Jiang, Mian Dai | Published: 2019-04-02 | Updated: 2020-04-02
Ensemble Learning
Machine Learning Application
evaluation metrics

Updates-Leak: Data Set Inference and Reconstruction Attacks in Online Learning

Authors: Ahmed Salem, Apratim Bhattacharya, Michael Backes, Mario Fritz, Yang Zhang | Published: 2019-04-01 | Updated: 2019-11-30
Model Extraction Attack
Reconstruction Attack
Adversarial Attack Detection

TG-PSM: Tunable Greedy Packet Sequence Morphing Based on Trace Clustering

Authors: Farzam Fanitabasi | Published: 2019-04-01
Data Protection Method
Data-Driven Clustering
Privacy Protection Method

Defending against adversarial attacks by randomized diversification

Authors: Olga Taran, Shideh Rezaeifar, Taras Holotyak, Slava Voloshynovskiy | Published: 2019-04-01
Adversarial Example Detection
Adversarial Attack Detection
Watermark Robustness