Detection and Analysis of Distributed Denial-of-service in the Internet of Things—Employing an Artificial Neural Network and Apache Spark Platform

Today, with increasing information technology such as the Internet of Things (IoT) in human life, interconnection and routing protocols need to find optimal solution for safe data transformation with various smart devices. Therefore, it is necessary to provide an enhanced solution to address routing issues with respect to new interconnection methodologies such as the 6LoWPAN protocol. The artificial neural network (ANN) is based on the structure of intelligent systems as a branch of machine interference, has shown magnificent results in previous studies to optimize security-aware routing protocols. In addition, IoT devices generate large amounts of data with variety and accuracy. Therefore, higher performance and better data handling can be achieved when this technology incorporates data for sending and receiving nodes in the environment. Therefore, this study presents a security-aware routing mechanism for IoT technologies. In addition, a comparative analysis of the relationship between previous approaches discusses with quality of service (QoS) factors such as throughput and accuracy for improving routing mechanism. Experimental results show that the use of time-division multiple access (TDMA) method to schedule the sending and receiving of data and the use of the 6LoWPAN protocol when routing the sending and receiving of data can carry out attacks with high accuracy.

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Mitigation of Distributed Denial of Service Attacks on the Internet of Things

Applied Mathematics & Information Sciences ◽

10.18576/amis/130517 ◽

2019 ◽

Vol 13 (5) ◽

pp. 831-837

Author(s):

R., K. Radhika, Kulothungan

Keyword(s):

Internet Of Things ◽

Denial Of Service ◽

The Internet ◽

Denial Of Service Attacks ◽

Distributed Denial Of Service ◽

The Internet Of Things

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DDoS-Capable IoT Malwares: Comparative Analysis and Mirai Investigation

Security and Communication Networks ◽

10.1155/2018/7178164 ◽

2018 ◽

Vol 2018 ◽

pp. 1-30 ◽

Cited By ~ 34

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.

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

Advances in Data Mining and Database Management - Data Mining Trends and Applications in Criminal Science and Investigations ◽

10.4018/978-1-5225-0463-4.ch010 ◽

2016 ◽

pp. 275-334 ◽

Cited By ~ 1

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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Cyber-Physical System and Internet of Things Security

Research Anthology on Combating Denial-of-Service Attacks ◽

10.4018/978-1-7998-5348-0.ch018 ◽

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.

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FR-WARD: Fast Retransmit as a Wary but Ample Response to Distributed Denial-of-Service Attacks from the Internet of Things

2018 27th International Conference on Computer Communication and Networks (ICCCN) ◽

10.1109/icccn.2018.8487342 ◽

2018 ◽

Cited By ~ 1

Author(s):

Samuel Mergendahl ◽

Devkishen Sisodia ◽

Jun Li ◽

Hasan Cam

Keyword(s):

Internet Of Things ◽

Denial Of Service ◽

The Internet ◽

Denial Of Service Attacks ◽

Distributed Denial Of Service ◽

The Internet Of Things

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Distributed Denial of Service Detection using Multi Layered Feed Forward Artificial Neural Network

International Journal of Computer Network and Information Security ◽

10.5815/ijcnis.2017.12.04 ◽

2017 ◽

Vol 9 (12) ◽

pp. 29-35

Author(s):

Ismaila Idris ◽

◽

Obi Blessing Fabian ◽

Shafi’i M. Abdulhamid ◽

Morufu Olalere ◽

...

Keyword(s):

Neural Network ◽

Artificial Neural Network ◽

Denial Of Service ◽

Distributed Denial Of Service ◽

Feed Forward ◽

Artificial Neural

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Malware Threat in Internet of Things and Its Mitigation Analysis

Research Anthology on Combating Denial-of-Service Attacks ◽

10.4018/978-1-7998-5348-0.ch020 ◽

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.

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