Attack simulation and signature extraction of low-rate DDoS
Tongxin xuebao, 2008 LDDoS （low-rate distributed denial-of-service） was a new type of DDoS attack. It had small traffic and cov- ered by normal network traffic. LDDoS attack was so stealthy that the detection and defense approaches of traditional DDoS could not be effective.
WU Zhi-jun, ZHANG Dong
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An Shilling Attack Detection Algorithm Based on Item Popularity and Novelty Degree Features
工程科学与技术, 2017 :The existing supervised detection algorithms have low precision when they detect shilling attacks.To address this problem,a shilling attack detection algorithm based on the features of popularity and novelty degree was proposed.Firstly,according to the ...
于洪涛, 周倩楠, 张付志
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An Analysis of GPS Spoofing Attack and Efficient Approach to Spoofing Detection in PX4
IEEE AccessUnmanned 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 +3 more
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Intrusion Detection of NSM Based DoS Attacks Using Data Mining in Smart Grid
Energies, 2012 In this paper, we analyze the Network and System Management (NSM) requirements and NSM data objects for the intrusion detection of power systems; NSM is an IEC 62351-7 standard.
JungChan Na +5 more
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Modeling and detection of complex attacks [PDF]
2007 Third International Conference on Security and Privacy in Communications Networks and the Workshops - SecureComm 2007, 2007 A complex attack is a sequence of temporally and spatially separated legal and illegal actions each of which can be detected by various IDS but as a whole they constitute a powerful attack. IDS fall short of detecting and modeling complex attacks therefore new methods are required.
Seyit Ahmet Çamtepe, Bülent Yener
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Multi-Stage Adversarial Defense for Online DDoS Attack Detection System in IoT
IEEE AccessMachine learning-based Distributed Denial of Service (DDoS) attack detection systems have proven effective in detecting and preventing DDoD attacks in Internet of Things (IoT) systems.
Yonas Kibret Beshah +2 more
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Behavioral Fingerprinting of IoT Devices for Forensic Identification Post-Attack
IEEE AccessThe 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 +5 more
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IDAC: Federated Learning-Based Intrusion Detection Using Autonomously Extracted Anomalies in IoT
SensorsThe 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 +2 more
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Deep Reinforcement Learning-Based Adversarial Attack and Defense in Industrial Control Systems
MathematicsAdversarial 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
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DDoS Attack Detection and Attacker Identification
International Journal of Computer Applications, 2012 DDoS attack is a form of DoS attack in which attacker uses authorized user IP address to attack on a particular victim. Of the two types of attack it falls in the active category. The main aim of the attacker is to jam the resources in order to deny services to the recipient. The attacker can use several strategies to achieve this goal, one of which is
S. K. Jena, Brajesh Kashyap
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