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Field: Advanced Malware Detection Techniques

Cyber Intrusion Detection Using Machine Learning Classification Techniques

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Hamed Alqahtani, Iqbal H. Sarker, Asra Kalim, Syed Md. Minhaz Hossain et al.

Journal: Communications in computer and information science
Year: 2020
Citations: 170

As the alarming growth of connectivity of computers and the significant number of computer-related applications increase in recent years, the challenge of fulfilling cyber-security is increasing consistently. It also needs a proper protection system for numerous cyberattacks. Thus, detecting inconsi...

Physical SciencesComputer ScienceComputer Networks and Communications
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Support Vector Machine and Random Forest Modeling for Intrusion Detection System (IDS)

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Md. Al Mehedi Hasan, Mohammed Nasser, Biprodip Pal, Shamim Ahmad

Journal: Journal of Intelligent Learning Systems and ApplicationsYear: 2014Citations: 169

The success of any Intrusion Detection System (IDS) is a complicated problem due to its nonlinearity and the quantitative or qualitative network traffic data stream with many features. To get rid of this problem, several types of intrusion detection methods have been proposed and shown different lev...

Physical SciencesComputer ScienceComputer Networks and CommunicationsOpen Access
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A dependable hybrid machine learning model for network intrusion detection

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Md. Alamin Talukder, Khondokar Fida Hasan, Md. Manowarul Islam, Md. Ashraf Uddin et al.

Journal: Journal of Information Security and ApplicationsYear: 2022Citations: 164

Network intrusion detection systems (NIDSs) play an important role in computer network security. There are several detection mechanisms where anomaly-based automated detection outperforms others significantly. Amid the sophistication and growing number of attacks, dealing with large amounts of data ...

Physical SciencesComputer ScienceComputer Networks and Communications
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Dependable Intrusion Detection System for IoT: A Deep Transfer Learning Based Approach

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Sk. Tanzir Mehedi, Adnan Anwar, Ziaur Rahman, Kawsar Ahmed et al.

Journal: IEEE Transactions on Industrial InformaticsYear: 2022Citations: 162

Security concerns for Internet of Things (IoT) applications have been alarming because of their widespread use in different enterprise systems. The potential threats to these applications are constantly emerging and changing, and, therefore, sophisticated and dependable defense solutions are necessa...

Physical SciencesComputer ScienceComputer Networks and CommunicationsOpen Access
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Security Threats and Artificial Intelligence Based Countermeasures for Internet of Things Networks: A Comprehensive Survey

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Shakila Zaman, Khaled Alhazmi, Mohammed Aseeri, Muhammad R. Ahmed et al.

Journal: IEEE AccessYear: 2021Citations: 159

The Internet of Things (IoT) has emerged as a technology capable of connecting heterogeneous nodes/objects, such as people, devices, infrastructure, and makes our daily lives simpler, safer, and fruitful. Being part of a large network of heterogeneous devices, these nodes are typically resource-cons...

Physical SciencesComputer ScienceComputer Networks and CommunicationsOpen Access
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Phishing Attacks Detection using Machine Learning Approach

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Mohammad Nazmul Alam, Dhiman Sarma, Farzana Firoz Lima, Ishita Saha et al.

Journal: 2020 Third International Conference on Smart Systems and Inventive Technology (ICSSIT)Year: 2020Citations: 151

Evolving digital transformation has exacerbated cybersecurity threats globally. Digitization expands the doors wider to cybercriminals. Initially cyberthreats approach in the form of phishing to steal the confidential user credentials. Usually, Hackers will influence the users through phishing in or...

Physical SciencesComputer ScienceInformation Systems
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Detecting Fake News using Machine Learning and Deep Learning Algorithms

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Abdullah All Tanvir, Ehesas Mia Mahir, Saima Akhter, Mohammad Rezwanul Huq

Year: 2019Citations: 145

Social media interaction especially the news spreading around the network is a great source of information nowadays. From one's perspective, its negligible exertion, straightforward access, and quick dispersing of information that lead people to look out and eat up news from internet-based life. Twi...

Social SciencesSociology and Political ScienceMisinformation and Its Impacts
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Detection of Distributed Denial of Service (DDoS) Attacks in IOT Based Monitoring System of Banking Sector Using Machine Learning Models

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Umar Islam, Ali Muhammad, Rafiq Mansoor, Md Shamim Hossain et al.

Journal: SustainabilityYear: 2022Citations: 144

Cyberattacks can trigger power outages, military equipment problems, and breaches of confidential information, i.e., medical records could be stolen if they get into the wrong hands. Due to the great monetary worth of the data it holds, the banking industry is particularly at risk. As the number of ...

Physical SciencesComputer ScienceComputer Networks and CommunicationsOpen Access
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Towards Machine Learning Based Intrusion Detection in IoT Networks

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Nahida Islam, Fahiba Farhin, Ishrat Sultana, M. Shamim Kaiser et al.

Journal: Computers, materials & continua/Computers, materials & continua (Print)Year: 2021Citations: 140

The Internet of Things (IoT) integrates billions of self-organized and heterogeneous smart nodes that communicate with each other without human intervention. In recent years, IoT based systems have been used in improving the experience in many applications including healthcare, agriculture, supply c...

Physical SciencesComputer ScienceComputer Networks and CommunicationsOpen Access
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A Critical Review of Artificial Intelligence Based Approaches in Intrusion Detection: A Comprehensive Analysis

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Salman Muneer, Umer Farooq, Atifa Athar, Muhammad Ahsan Raza et al.

Journal: Journal of EngineeringYear: 2024Citations: 136

Intrusion detection (ID) is critical in securing computer networks against various malicious attacks. Recent advancements in machine learning (ML), deep learning (DL), federated learning (FL), and explainable artificial intelligence (XAI) have drawn significant attention as potential approaches for ...

Physical SciencesComputer ScienceComputer Networks and CommunicationsOpen Access
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False data injection attack (FDIA): an overview and new metrics for fair evaluation of its countermeasure

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Mohiuddin Ahmed, Al‐Sakib Khan Pathan

Journal: Complex Adaptive Systems ModelingYear: 2020Citations: 135

Abstract The concept of false data injection attack (FDIA) was introduced originally in the smart grid domain. While the term sounds common, it specifically means the case when an attacker compromises sensor readings in such tricky way that undetected errors are introduced into calculations of state...

Physical SciencesEngineeringControl and Systems EngineeringOpen Access
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CyberLearning: Effectiveness analysis of machine learning security modeling to detect cyber-anomalies and multi-attacks

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Iqbal H. Sarker

Journal: Internet of ThingsYear: 2021Citations: 128

Detecting cyber-anomalies and attacks are becoming a rising concern these days in the domain of cybersecurity. The knowledge of artificial intelligence, particularly, the machine learning techniques can be used to tackle these issues. However, the effectiveness of a learning-based security model may...

Physical SciencesComputer ScienceComputer Networks and Communications
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Cyberbullying Detection on Social Networks Using Machine Learning Approaches

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Md. Manowarul Islam, Md. Ashraf Uddin, Linta Islam, Arnisha Akter et al.

Journal: 2020 IEEE Asia-Pacific Conference on Computer Science and Data Engineering (CSDE)Year: 2020Citations: 116

The use of social media has grown exponentially over time with the growth of the Internet and has become the most influential networking platform in the 21st century. However, the enhancement of social connectivity often creates negative impacts on society that contribute to a couple of bad phenomen...

Physical SciencesComputer ScienceArtificial IntelligenceOpen Access
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Ransomware Classification and Detection With Machine Learning Algorithms

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Mohammad Masum, Md Jobair Hossain Faruk, Hossain Shahriar, Kai Qian et al.

Journal: 2022 IEEE 12th Annual Computing and Communication Workshop and Conference (CCWC)Year: 2022Citations: 112

Malicious attacks, malware, and ransomware families pose critical security issues to cybersecurity, and it may cause catastrophic damages to computer systems, data centers, web, and mobile applications across various industries and businesses. Traditional anti-ransomware systems struggle to fight ag...

Physical SciencesComputer ScienceSignal ProcessingOpen Access
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A Deep Learning Approach to Detect Abusive Bengali Text

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Estiak Ahmed Emon, Shihab Rahman, Joti Banarjee, Amit Kumar Das et al.

Year: 2019Citations: 110

Day by day, Social media sites, online news portals and blogs commenting sections are getting saturated with abusive contents in Bangladesh. Detecting different types of abusive contents in online will not only improve these websites discussion sections but will also ensure user's safety. In this pa...

Physical SciencesComputer ScienceArtificial Intelligence
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