Results 41 to 50 of about 165,511 (160)

Attack as Detection: Using Adversarial Attack Methods to Detect Abnormal Examples

ACM Transactions on Software Engineering and Methodology
As a new programming paradigm, deep learning (DL) has achieved impressive performance in areas such as image processing and speech recognition, and has expanded its application to solve many real-world problems. However, neural networks and DL are normally black-box systems; even worse, DL-based software are vulnerable to threats from ...
Zhe Zhao 0007, Guangke Chen, Tong Liu 0027, Taishan Li, Fu Song, Jingyi Wang 0004, Jun Sun 0001   +6 more
openaire   +2 more sources

Deep Reinforcement Learning-Based Adversarial Attack and Defense in Industrial Control Systems

Mathematics
Adversarial attacks targeting industrial control systems, such as the Maroochy wastewater system attack and the Stuxnet worm attack, have caused significant damage to related facilities.
Mun-Suk Kim
doaj   +1 more source

Face Presentation Attack Detection

, 2023
Face recognition technology has been widely used in daily interactive applications such as checking-in and mobile payment due to its convenience and high accuracy. However, its vulnerability to presentation attacks (PAs) limits its reliable use in ultra-secure applicational scenarios.
Zitong Yu, Chenxu Zhao, Zhen Lei 0001
openaire   +2 more sources

An Analysis of GPS Spoofing Attack and Efficient Approach to Spoofing Detection in PX4

IEEE Access
Unmanned Aerial Vehicles (UAVs) are aerial vehicles that can go to a particular position without human control or with remote human control. It is because unmanned control mainly relies on position estimation that a lot of research has been studied on ...
Ji Hyuk Jung, Mi Yeon Hong, Hyeongjun Choi, Ji Won Yoon   +3 more
doaj   +1 more source

Phishing Attacks: Detection And Prevention

CoRR, 2020
5 pages, 7 figures, 1 table, essential ...
openaire   +2 more sources

IDAC: Federated Learning-Based Intrusion Detection Using Autonomously Extracted Anomalies in IoT

Sensors
The recent rapid growth in Internet of Things (IoT) technologies is enriching our daily lives but significant information security risks in IoT fields have become apparent.
Takahiro Ohtani, Ryo Yamamoto, Satoshi Ohzahata   +2 more
doaj   +1 more source

Behavioral Fingerprinting of IoT Devices for Forensic Identification Post-Attack

IEEE Access
The rapid adoption of Internet of Things (IoT) devices has amplified security risks, particularly in post-incident scenarios where accurate device attribution and evidence reconstruction are required.
Laveeza Tahir, Isha Bukhari, Kashif Munir, Hasan J. Alyamani, Amine Bermak, Atiq Ur Rehman   +5 more
doaj   +1 more source

Construction of advanced persistent threat attack detection model based on provenance graph and attention mechanism

Tongxin xuebao
In response to the difficulty of existing attack detection methods in dealing with advanced persistent threat (APT) with longer durations, complex and covert attack methods, a model for APT attack detection based on attention mechanisms and provenance ...
Yuancheng LI, Hao LUO, Xinyu WANG, Jiexuan YUAN   +3 more
doaj   +2 more sources

Research on wormhole attacks in wireless mesh networks

Tongxin xuebao, 2011
In order to detect the wormhole attacks effectively in wireless mesh network,a wormhole attack model ac-cording to the MR-LQSR（multi-radio link-quality source routing） protocol proposed by Microsoft was presented.Then,the characteristics of wireless mesh
FU Ying-fang1, ZHANG Xing1, ZHANG Ting1, LUAN Liang-yu3   +3 more
doaj   +2 more sources

Unorganized Malicious Attacks Detection

CoRR, 2016
Recommender system has attracted much attention during the past decade. Many attack detection algorithms have been developed for better recommendations, mostly focusing on shilling attacks, where an attack organizer produces a large number of user profiles by the same strategy to promote or demote an item.
Ming Pang, Wei Gao 0008, Min Tao, Zhi-Hua Zhou   +3 more
openaire   +3 more sources