A Comprehensive Study on Distributed Denial of Service Attacks in Internet of Things Based Smart Grid

2019 ◽  
pp. 685-691
Author(s):  
A. Valliammai ◽  
U. Bavatharinee ◽  
K. Shivadharshini ◽  
N. Hemavathi ◽  
M. Meenalochani ◽  
...  
Keyword(s):  
Internet Of Things ◽  
Smart Grid ◽  
Denial Of Service ◽  
Denial Of Service Attacks ◽  
Distributed Denial Of Service ◽  
Comprehensive Study

Data Mining Techniques for Distributed Denial of Service Attacks Detection in the Internet of Things

2016 ◽  
pp. 275-334 ◽  
Author(s):  
Pheeha Machaka ◽  
Fulufhelo Nelwamondo
Keyword(s):  
Data Mining ◽  
Internet Of Things ◽  
Denial Of Service ◽  
Current Data ◽  
The Internet ◽  
Denial Of Service Attacks ◽  
Distributed Denial Of Service ◽  
Ddos Attacks ◽  
Data Mining Techniques ◽  
The Internet Of Things

This chapter reviews the evolution of the traditional internet into the Internet of Things (IoT). The characteristics and application of the IoT are also reviewed, together with its security concerns in terms of distributed denial of service attacks. The chapter further investigates the state-of-the-art in data mining techniques for Distributed Denial of Service (DDoS) attacks targeting the various infrastructures. The chapter explores the characteristics and pervasiveness of DDoS attacks. It also explores the motives, mechanisms and techniques used to execute a DDoS attack. The chapter further investigates the current data mining techniques that are used to combat and detect these attacks, their advantages and disadvantages are explored. Future direction of the research is also provided.

Strategic Honeypot Game Model for Distributed Denial of Service Attacks in the Smart Grid

2017 ◽  
Vol 8 (5) ◽  
pp. 2474-2482 ◽  
Author(s):  
Kun Wang ◽  
Miao Du ◽  
Sabita Maharjan ◽  
Yanfei Sun
Keyword(s):  
Smart Grid ◽  
Denial Of Service ◽  
Denial Of Service Attacks ◽  
Game Model ◽  
Distributed Denial Of Service

Data Mining Techniques for Distributed Denial of Service Attacks Detection in the Internet of Things

2020 ◽  
pp. 561-608
Author(s):  
Pheeha Machaka ◽  
Fulufhelo Nelwamondo
Keyword(s):  
Data Mining ◽  
Internet Of Things ◽  
Denial Of Service ◽  
Current Data ◽  
The Internet ◽  
Denial Of Service Attacks ◽  
Distributed Denial Of Service ◽  
Ddos Attacks ◽  
Data Mining Techniques ◽  
The Internet Of Things

This chapter reviews the evolution of the traditional internet into the Internet of Things (IoT). The characteristics and application of the IoT are also reviewed, together with its security concerns in terms of distributed denial of service attacks. The chapter further investigates the state-of-the-art in data mining techniques for Distributed Denial of Service (DDoS) attacks targeting the various infrastructures. The chapter explores the characteristics and pervasiveness of DDoS attacks. It also explores the motives, mechanisms and techniques used to execute a DDoS attack. The chapter further investigates the current data mining techniques that are used to combat and detect these attacks, their advantages and disadvantages are explored. Future direction of the research is also provided.

Conceptual Framework to Mitigate Internet of Things-DDoS attacks using Fog Nodes

2020 ◽  
Vol 14 ◽  
Author(s):  
B.B. Gupta ◽  
Harish S.A.
Keyword(s):  
Internet Of Things ◽  
Conceptual Framework ◽  
Real Time ◽  
Autonomous System ◽  
Denial Of Service ◽  
Denial Of Service Attacks ◽  
Distributed Denial Of Service ◽  
Technology Infrastructure ◽  
Information Technology Infrastructure ◽  
Remote Server

: Internet of Things has proven to maximize workflow and data sensing capabilities. Contrarily, Distributed Denial of Service attacks that employ compromised Internet of Things devices have caused considerable damage to the Information Technology infrastructure since their advent. More specifically, Application level attacks facilitated using affected Internet of Things devices are found to be difficult to detect and defend against. Seemingly benign traffic from infected devices exit the network edge to target a remote server. The conceptual framework described in this paper attempts to mitigate malicious Internet of Things traffic at the source network. Fog nodes at the source Autonomous System are utilized in tandem with a ratio metric that flags traffic as well as the originating device as suspicious or benign based on traffic ratios calculated in real time. Subsequently, malicious traffic is blocked inside the Autonomous System. The burden and risk of protecting the external network from Distributed Denial of Service attacks is transferred to Fog nodes inherent to every source network. The proposed conceptual defense framework is proactive and performs in real time attack scenarios.

Mitigating Distributed Denial of Service Attacks with Dynamic Resource Pricing

2001 ◽  
Author(s):  
David Mankins ◽  
Rajesh Krishnan ◽  
Ceilyn Boyd ◽  
John Zao ◽  
Michael Frentz
Keyword(s):  
Denial Of Service ◽  
Denial Of Service Attacks ◽  
Distributed Denial Of Service ◽  
Resource Pricing ◽  
Dynamic Resource
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