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An Accurate Detection Approach for IoT Botnet Attacks Using Interpolation Reasoning Method

Information (Switzerland), 2022
Nowadays, the rapid growth of technology delivers many new concepts and notations that aim to increase the efficiency and comfort of human life. One of these techniques is the Internet of Things (IoT). The IoT has been used to achieve efficient operation
Mouhammd Alkasassbeh, Mohammad Almseidin, Alkasassbeh Mouhammd   +2 more
exaly   +3 more sources

A Two-Fold Machine Learning Approach to Prevent and Detect IoT Botnet Attacks

IEEE Access, 2021
The botnet attack is a multi-stage and the most prevalent cyber-attack in the Internet of Things (IoT) environment that initiates with scanning activity and ends at the distributed denial of service (DDoS) attack.
Ubaid Ullah Fayyaz, Faisal Hussain, Nuno M Garcia   +2 more
exaly   +3 more sources

Botnet detection in internet of things using stacked ensemble learning model [PDF]

Scientific Reports
Botnets are used for malicious activities such as cyber-attacks, spamming, and data theft and have become a significant threat to cyber security. Despite existing approaches for cyber attack detection, botnets prove to be a particularly difficult problem
Mudasir Ali, Muhammad Faheem Mushtaq, Urooj Akram, Daniel Gavilanes Aray, Manuel Masias Vergara, Hanen Karamti, Imran Ashraf   +6 more
doaj   +2 more sources

Explainable artificial intelligence for botnet detection in internet of things [PDF]

Scientific Reports
The proliferation of internet of things (IoT) devices has led to unprecedented connectivity and convenience. However, this increased interconnectivity has also introduced significant security challenges, particularly concerning the detection and ...
Mohamed Saied, Shawkat Guirguis
doaj   +2 more sources

Systematic Literature Review of IoT Botnet DDOS Attacks and Evaluation of Detection Techniques

Sensors
Internet of Things (IoT) technology has become an inevitable part of our daily lives. With the increase in usage of IoT Devices, manufacturers continuously develop IoT technology.
Nicola Dragoni, Sanjay Arunachala, Metehan Gelgi   +2 more
exaly   +3 more sources

Deep Learning-Based Intrusion Detection System for Detecting IoT Botnet Attacks: A Review

IEEE Access
The proliferation of Internet of Things (IoT) devices has brought about an increased threat of botnet attacks, necessitating robust security measures. In response to this evolving landscape, deep learning (DL)-based intrusion detection systems (IDS) have
Iznan Hasbullah, Mohammed Anbar, Selvakumar Manickam   +2 more
exaly   +3 more sources

Review of Botnet Attack Detection in SDN-Enabled IoT Using Machine Learning

Sensors, 2022
The orchestration of software-defined networks (SDN) and the internet of things (IoT) has revolutionized the computing fields. These include the broad spectrum of connectivity to sensors and electronic appliances beyond standard computing devices ...
Worku Gachena Negera, Friedhelm Schwenker, Taye Girma Debelee, Henock Mulugeta Melaku, Yehualashet Megeresa Ayano   +4 more
doaj   +1 more source

Enhancing the security in cyber-world by detecting the botnets using ensemble classification based machine learning

Measurement: Sensors, 2023
With various malware, botnets are the legitimate risk increasing against cybersecurity providing criminal operations like malware dispersal, distributed denial of service attacks, fraud clicking, phishing, and identification of theft. Existing techniques
Sathiyandrakumar Srinivasan, Deepalakshmi P   +1 more
doaj   +1 more source

Adaptive secure malware efficient machine learning algorithm for healthcare data

CAAI Transactions on Intelligence Technology, EarlyView., 2023
Abstract Malware software now encrypts the data of Internet of Things (IoT) enabled fog nodes, preventing the victim from accessing it unless they pay a ransom to the attacker. The ransom injunction is constantly accompanied by a deadline. These days, ransomware attacks are too common on IoT healthcare devices.
Mazin Abed Mohammed, Abdullah Lakhan, Dilovan Asaad Zebari, Karrar Hameed Abdulkareem, Jan Nedoma, Radek Martinek, Usman Tariq, Majed Alhaisoni, Prayag Tiwari   +8 more
wiley   +1 more source

Artificial Intelligence outflanks all other machine learning classifiers in Network Intrusion Detection System on the realistic cyber dataset CSE-CIC-IDS2018 using cloud computing

ICT Express, 2021
Our paramount task is to examine and detect network attacks, is one of the daunting tasks because the variety of attacks are day by day existing in colossal number.
V. Kanimozhi, T. Prem Jacob
doaj   +1 more source