Review
Chemistry, Analytical
Zawar Shah, Imdad Ullah, Huiling Li, Andrew Levula, Khawar Khurshid
Summary: Internet of Things (IoT) devices are vulnerable to Distributed Denial of Service (DDoS) attacks due to their limited resources. Blockchain-based solutions are potential to mitigate DDoS attacks in IoT. This survey provides a detailed analysis and evaluation of existing Blockchain-based solutions and identifies future research directions.
Article
Computer Science, Hardware & Architecture
Sowmya Myneni, Ankur Chowdhary, Dijiang Huang, Adel Alshamrani
Summary: The growing number of IoT edge devices have caused a change in the cyber-attack landscape, particularly with the significant increase in magnitude and intensity of DDoS attacks. This paper proposes a distributed DDoS detection and mitigation framework, SmartDefense, based on edge computing approaches, to detect and mitigate DDoS attacks at and near the source.
Review
Computer Science, Information Systems
Manish Snehi, Abhinav Bhandari
Summary: The widespread adoption of IoT, Software-defined Networks, and Cloud Computing has facilitated the development of Cyber-Physical Systems. Despite offering solutions to DDoS attacks, Software-defined Cyber-Physical Systems still face vulnerabilities and security risks. Integrating Fog Computing as an architectural layer can enhance the security of the system.
COMPUTER SCIENCE REVIEW
(2021)
Article
Computer Science, Information Systems
Rintaro Harada, Naotaka Shibata, Shin Kaneko, Kazuaki Honda, Jun Terada, Yota Ishida, Kunio Akashi, Toshiyuki Miyachi
Summary: We propose a novel distributed denial of service (DDoS) attack suppression system that reduces the discarding of normal traffic by controlling the priority of frames in a network. Experimental results demonstrate that our system effectively prevents the discarding of normal traffic and quickly blocks attack traffic.
Article
Automation & Control Systems
Liming Fang, Yang Li, Zhe Liu, Changchun Yin, Minghui Li, Zehong Jimmy Cao
Summary: The application of IoT in the medical field has brought unprecedented convenience but also security risks, leading to the proposal of an anomaly detection system for detecting illegal behavior (DIB) to ensure the safety of control services. The model based on rough set theory and FCVM can improve the accuracy of DIB classification anomalies.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2021)
Article
Computer Science, Information Systems
Faisal Hussain, Syed Ghazanfar Abbas, Ivan Miguel Pires, Sabeeha Tanveer, Ubaid U. Fayyaz, Nuno M. Garcia, Ghalib A. Shah, Farrukh Shahzad
Summary: The study proposes a two-fold machine learning approach to prevent and detect IoT botnet attacks by generating a generic dataset and integrating samples from publicly-available datasets, achieving high accuracy and recall rates. Experimental results demonstrate the effectiveness of this approach in efficiently preventing and detecting botnet attacks.
Article
Computer Science, Hardware & Architecture
Lingfeng Huang
Summary: This paper discusses the issue of DDoS attacks in the IoT environment and proposes an attack prediction system based on data mining technology, which consists of two major modules: the DDoS attack prediction model-construction module and the DDoS attack prediction defense module.
JOURNAL OF SUPERCOMPUTING
(2022)
Article
Computer Science, Information Systems
Yuming Feng, Weizhe Zhang, Shujun Yin, Hao Tang, Yang Xiang, Yu Zhang
Summary: This article proposes a novel reinforcement learning-based collaborative DDoS detection method and utilizes a lightweight unsupervised classifier for network traffic analysis. The dynamic changes in the IoT environment are handled using the soft actor-critic model and a collaborative aggregation module, ensuring excellent detection performance for different types of IoT devices.
IEEE INTERNET OF THINGS JOURNAL
(2023)
Article
Computer Science, Information Systems
Yair Meidan, Dan Avraham, Hanan Libhaber, Asaf Shabtai
Summary: Home IoT devices generate different traffic patterns depending on their daily use and network environments. We propose a two-step collaborative anomaly detection method that uses an autoencoder to differentiate frequent and infrequent traffic flows, followed by clustering to classify them as known or unknown. Our method shows high generalizability, promising performance, and offers benefits such as privacy preservation and resource savings.
IEEE INTERNET OF THINGS JOURNAL
(2023)
Article
Automation & Control Systems
Yong-joon Lee, Hwa-sung Chae, Keun-wang Lee
Summary: With the increasing use of IoT devices, they are becoming targets for DDoS attacks, particularly through vulnerabilities in protocols like SSDP. This study examines various IoT devices used in DDoS attacks and conducts experiments to measure the threat levels, while also suggesting methods for IoT service operators to remove vulnerabilities and for Internet service operators to counter reflection DDoS attacks.
Review
Computer Science, Information Systems
Rajasekhar Chaganti, Bharat Bhushan, Vinayakumar Ravi
Summary: With the advent of technologies like IoT and SDN, the DDoS attack vector has expanded, posing new threats to targeted victims. Blockchain technology, with its decentralized design and secure distributed storage, can enhance security in DDoS mitigation. This paper reviews and categorizes state-of-the-art DDoS mitigation solutions based on blockchain technology, considering deployment location and architectures like IoT and SDN.
COMPUTER COMMUNICATIONS
(2023)
Article
Computer Science, Artificial Intelligence
Mikail Mohammed Salim, Sushil Kumar Singh, Jong Hyuk Park
Summary: Smart cities rely on millions of heterogeneous sensors without standard security architecture. An AI-based framework for IoT fleet security management is proposed to enhance device security and prevent the formation of large botnets.
APPLIED SOFT COMPUTING
(2021)
Article
Computer Science, Hardware & Architecture
Keval Doshi, Yasin Yilmaz, Suleyman Uludag
Summary: Vulnerabilities in IoT devices pose a dangerous threat to Internet services and cyber-physical systems connected to the Internet. A novel anomaly-based Intrusion Detection System (IDS) is proposed to detect and mitigate emerging DDoS attacks, including the stealthy Mongolian DDoS attack characterized by its widely distributed nature and small attack size per source. The proposed IDS demonstrates capability in detecting and mitigating stealthy DDoS attacks even with very low attack size per source through numerical and testbed experiments.
IEEE TRANSACTIONS ON DEPENDABLE AND SECURE COMPUTING
(2021)
Article
Computer Science, Hardware & Architecture
Maryam Songhorabadi, Morteza Rahimi, AmirMehdi MoghadamFarid, Mostafa Haghi Kashani
Summary: The development of smart cities heavily relies on advanced computing paradigms, such as fog computing, to address the requirements of location-aware, latency-sensitive, and security-crucial applications. However, the frequently used cloud-based approaches in smart cities restrict the security, time-sensitive services, flexibility, and reliability. This paper proposes a study to explore the state-of-the-art fog-based approaches in smart cities and presents a classification of these approaches into service-based, resource-based, and application-based classes.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2023)
Article
Computer Science, Information Systems
Xu Chen, Liang Xiao, Wei Feng, Ning Ge, Xianbin Wang
Summary: The proliferation of DDoS attacks in IoT poses threats to security and system performance, and collaborative packet sampling can effectively detect and block such attacks.
IEEE INTERNET OF THINGS JOURNAL
(2022)
