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Computer Security

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Robustifying models against adversarial attacks by Langevin dynamics.

Neural networks : the official journal of the International Neural Network Society
Adversarial attacks on deep learning models have compromised their performance considerably. As remedies, a number of defense methods were proposed, which however, have been circumvented by newer and more sophisticated attacking strategies. In the mi...

Exponential Synchronization of Delayed Memristor-Based Uncertain Complex-Valued Neural Networks for Image Protection.

IEEE transactions on neural networks and learning systems
This article solves the exponential synchronization issue of memristor-based complex-valued neural networks (MCVNNs) with time-varying uncertainties via feedback control. Compared with the traditional control methods, a more practical and general con...

Cyberattacks Detection in IoT-Based Smart City Applications Using Machine Learning Techniques.

International journal of environmental research and public health
In recent years, the widespread deployment of the Internet of Things (IoT) applications has contributed to the development of smart cities. A smart city utilizes IoT-enabled technologies, communications and applications to maximize operational effici...

Challenges Developing Deep Learning Algorithms in Cytology.

Acta cytologica
BACKGROUND: The incorporation of digital pathology into routine pathology practice is becoming more widespread. Definite advantages exist with respect to the implementation of artificial intelligence (AI) and deep learning in pathology, including cyt...

The data dimensionality reduction and bad data detection in the process of smart grid reconstruction through machine learning.

PloS one
To detect false data injection attacks (FDIAs) in power grid reconstruction and solve the problem of high data dimension and bad abnormal data processing in the power system, thereby achieving safe and stable operation of the power grid system, this ...

A detection method for android application security based on TF-IDF and machine learning.

PloS one
Android is the most widely used mobile operating system (OS). A large number of third-party Android application (app) markets have emerged. The absence of third-party market regulation has prompted research institutions to propose different malware d...

Detecting face presentation attacks in mobile devices with a patch-based CNN and a sensor-aware loss function.

PloS one
With the widespread use of biometric authentication comes the exploitation of presentation attacks, possibly undermining the effectiveness of these technologies in real-world setups. One example takes place when an impostor, aiming at unlocking someo...

Review of Clinical Research Informatics.

Yearbook of medical informatics
OBJECTIVES: Clinical Research Informatics (CRI) declares its scope in its name, but its content, both in terms of the clinical research it supports-and sometimes initiates-and the methods it has developed over time, reach much further than the name s...

A systematic review of fuzzing based on machine learning techniques.

PloS one
Security vulnerabilities play a vital role in network security system. Fuzzing technology is widely used as a vulnerability discovery technology to reduce damage in advance. However, traditional fuzz testing faces many challenges, such as how to muta...