Results 81 to 90 of about 6,155,073 (227)

Detection of DDoS Attack

International Journal of Advanced Research in Science, Communication and Technology, 2023
DOS Attacks or Denial Of Services Attack have become very common amongst Hackers who use them as a path to get fame and respect in the underground groups of the Internet. Denial of Service Attacks basically means denying valid Internet and Network users from using the services of the target network or server.
null Prof. B. V. Jadhav, null Mansi Mahamuni, null Akshata Ghodke, null Akshata Ghodke, null Vrushali Chavan   +4 more
openaire   +1 more source

Data Attacks on Power Grids: Leveraging Detection

, 2015
Data attacks on meter measurements in the power grid can lead to errors in state estimation. This paper presents a new data attack model where an adversary produces changes in state estimation despite failing bad-data detection checks.
Baldick, Ross, Deka, Deepjyoti, Vishwanath, Sriram   +2 more
core   +1 more source

Quantum Hacking: Experimental demonstration of time-shift attack against practical quantum key distribution systems

, 2011
Quantum key distribution (QKD) systems can send signals over more than 100 km standard optical fiber and are widely believed to be secure. Here, we show experimentally for the first time a technologically feasible attack, namely the time-shift attack ...
B. Qi, Bing Qi, C. H. Bennett, C. H. Bennett, Chi-Hang Fred Fung, Christine Chen, D. Gottesman, G. Brassard, H.-K. Lo, Hoi-Kwong Lo, M. Ben-Or, R. Renner, V. Makarov, Y. Zhao, Yi Zhao   +14 more
core   +1 more source

ATTACK DETECTION SYSTEMS

, 2022
An intrusion detection system is a software or hardware tool designed to detect unauthorized access to or control of a computer system or network, mainly via the Internet. Today, there are several types of IDS that differ in their monitoring and analysis methods. Each approach has its own advantages and disadvantages. In addition, all approaches can be
openaire   +1 more source

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
doaj   +2 more sources

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, Kijoon Chae, Mihui Kim, Shi Li, Xinyi Chen, Kyung Choi   +5 more
doaj   +1 more source

Sleep Deprivation Attack Detection in Wireless Sensor Network

, 2012
Deployment of sensor network in hostile environment makes it mainly vulnerable to battery drainage attacks because it is impossible to recharge or replace the battery power of sensor nodes.
Bhattasali, Tapalina, Chaki, Rituparna, Sanyal, Sugata   +2 more
core   +3 more sources

Multi-Stage Adversarial Defense for Online DDoS Attack Detection System in IoT

IEEE Access
Machine 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, Surafel Lemma Abebe, Henock Mulugeta Melaku   +2 more
doaj   +1 more source

Feature Engineering for Detection of Wormhole Attacking in Mobile Ad Hoc Networks with Machine Learning Methods [PDF]

, 2014
Due to the self-configuring nature of a Mobile Ad Hoc Network (MANET), each node must participate in the routing process, in addition to its other activities.
Dooley, Laurence S., Karlsson, Jonny, Pulkkis, Göran, Westerlund, Magnus   +3 more
core  

Byzantine Attack and Defense in Cognitive Radio Networks: A Survey

, 2015
The Byzantine attack in cooperative spectrum sensing (CSS), also known as the spectrum sensing data falsification (SSDF) attack in the literature, is one of the key adversaries to the success of cognitive radio networks (CRNs).
Ding, Guoru, Han, Zhu, Wang, Jinlong, Wu, Qihui, Zhang, Linyuan, Zou, Yulong   +5 more
core   +1 more source