scholarly journals A Survey on Botnets: Incentives, Evolution, Detection and Current Trends

2021 ◽  
Vol 13 (8) ◽  
pp. 198
Author(s):  
Simon Nam Thanh Vu ◽  
Mads Stege ◽  
Peter Issam El-Habr ◽  
Jesper Bang ◽  
Nicola Dragoni
Keyword(s):  
Literature Review ◽  
Pervasive Computing ◽  
Denial Of Service ◽  
The Internet ◽  
Distributed Denial Of Service ◽  
Botnet Detection ◽  
Current Trends ◽  
Malware Propagation ◽  
The Many ◽  
The Internet Of Things

Botnets, groups of malware-infected hosts controlled by malicious actors, have gained prominence in an era of pervasive computing and the Internet of Things. Botnets have shown a capacity to perform substantial damage through distributed denial-of-service attacks, information theft, spam and malware propagation. In this paper, a systematic literature review on botnets is presented to the reader in order to obtain an understanding of the incentives, evolution, detection, mitigation and current trends within the field of botnet research in pervasive computing. The literature review focuses particularly on the topic of botnet detection and the proposed solutions to mitigate the threat of botnets in system security. Botnet detection and mitigation mechanisms are categorised and briefly described to allow for an easy overview of the many proposed solutions. The paper also summarises the findings to identify current challenges and trends within research to help identify improvements for further botnet mitigation research.

scholarly journals DDoS-Capable IoT Malwares: Comparative Analysis and Mirai Investigation

2018 ◽  
Vol 2018 ◽  
pp. 1-30 ◽  
Author(s):  
Michele De Donno ◽  
Nicola Dragoni ◽  
Alberto Giaretta ◽  
Angelo Spognardi
Keyword(s):  
Comparative Analysis ◽  
Internet Of Things ◽  
Detailed Analysis ◽  
Real World ◽  
General Framework ◽  
Denial Of Service ◽  
The Internet ◽  
Distributed Denial Of Service ◽  
Ddos Attacks ◽  
The Internet Of Things

The Internet of Things (IoT) revolution has not only carried the astonishing promise to interconnect a whole generation of traditionally “dumb” devices, but also brought to the Internet the menace of billions of badly protected and easily hackable objects. Not surprisingly, this sudden flooding of fresh and insecure devices fueled older threats, such as Distributed Denial of Service (DDoS) attacks. In this paper, we first propose an updated and comprehensive taxonomy of DDoS attacks, together with a number of examples on how this classification maps to real-world attacks. Then, we outline the current situation of DDoS-enabled malwares in IoT networks, highlighting how recent data support our concerns about the growing in popularity of these malwares. Finally, we give a detailed analysis of the general framework and the operating principles of Mirai, the most disruptive DDoS-capable IoT malware seen so far.

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.

Cyber-Physical System and Internet of Things Security

2021 ◽  
pp. 328-357
Author(s):  
Thomas Ulz ◽  
Sarah Haas ◽  
Christian Steger
Keyword(s):  
Internet Of Things ◽  
Public Awareness ◽  
Denial Of Service ◽  
The Internet ◽  
Distributed Denial Of Service ◽  
Ddos Attacks ◽  
Industrial Iot ◽  
Confidential Data ◽  
Iot Devices ◽  
The Internet Of Things

An increase of distributed denial-of-service (DDoS) attacks launched by botnets such as Mirai has raised public awareness regarding potential security weaknesses in the Internet of Things (IoT). Devices are an attractive target for attackers because of their large number and due to most devices being online 24/7. In addition, many traditional security mechanisms are not applicable for resource constraint IoT devices. The importance of security for cyber-physical systems (CPS) is even higher, as most systems process confidential data or control a physical process that could be harmed by attackers. While industrial IoT is a hot topic in research, not much focus is put on ensuring information security. Therefore, this paper intends to give an overview of current research regarding the security of data in industrial CPS. In contrast to other surveys, this work will provide an overview of the big CPS security picture and not focus on special aspects.

Malware Threat in Internet of Things and Its Mitigation Analysis

2021 ◽  
pp. 371-387
Author(s):  
Shingo Yamaguchi ◽  
Brij Gupta
Keyword(s):  
Internet Of Things ◽  
Large Volume ◽  
Denial Of Service ◽  
The Internet ◽  
Distributed Denial Of Service ◽  
Ddos Attack ◽  
New Type ◽  
Iot Devices ◽  
Mitigation Methods ◽  
The Internet Of Things

This chapter introduces malware's threat in the internet of things (IoT) and then analyzes the mitigation methods against the threat. In September 2016, Brian Krebs' web site “Krebs on Security” came under a massive distributed denial of service (DDoS) attack. It reached twice the size of the largest attack in history. This attack was caused by a new type of malware called Mirai. Mirai primarily targets IoT devices such as security cameras and wireless routers. IoT devices have some properties which make them malware attack's targets such as large volume, pervasiveness, and high vulnerability. As a result, a DDoS attack launched by infected IoT devices tends to become massive and disruptive. Thus, the threat of Mirai is an extremely important issue. Mirai has been attracting a great deal of attention since its birth. This resulted in a lot of information related to IoT malware. Most of them came from not academia but industry represented by antivirus software makers. This chapter summarizes such information.

scholarly journals A Methodological Approach for Assessing Amplified Reflection Distributed Denial of Service on the Internet of Things

Sensors ◽  
2016 ◽  
Vol 16 (11) ◽  
pp. 1855 ◽  
Author(s):  
João Costa Gondim ◽  
Robson de Oliveira Albuquerque ◽  
Anderson Clayton Alves Nascimento ◽  
Luis García Villalba ◽  
Tai-Hoon Kim
Keyword(s):  
Internet Of Things ◽  
Methodological Approach ◽  
Denial Of Service ◽  
The Internet ◽  
Distributed Denial Of Service ◽  
The Internet Of Things

Distributed Denial-of-Service Attack Detection and Mitigation for the Internet of Things

2020 ◽  
Vol 11 (2) ◽  
pp. 18-32
Author(s):  
Opeyemi Peter Ojajuni ◽  
Yasser Ismail ◽  
Albertha Lawson
Keyword(s):  
Internet Of Things ◽  
Denial Of Service ◽  
Application Programming Interface ◽  
Attack Detection ◽  
The Internet ◽  
Distributed Denial Of Service ◽  
Financial Loss ◽  
Ddos Attack ◽  
The Internet Of Things ◽  
Sdn Controller

The Internet of Things (IoT) allows different devices with internet protocol (IP) address to be connected together via the internet to collect, provide, store, and exchange data amongst themselves. The distributed denial of service (DDoS) attack is one of the inevitable challenges which should be addressed in the development of the IoT. A DDoS attack has the potential to render a victim's services unavailable, which can then lead to additional challenges such as website outage, financial loss, reputational damage and loss of confidential information. In this article, a framework of the SDN controller via an application programming interface (API) is compared to an existing framework. SDN provides a new architecture that can detect and mitigate a DDoS attack so that it makes the networking functionalities programmable via the API and also it centralizes the control management of the IoT devices. Experimental results show the capability of the SDN framework to analyze a real-time traffic of the SDN controller via the API by setting a control bandwidth usage threshold using the API.

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.

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