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Ammar Odeh and Anas Abu Taleb
Cybersecurity finds widespread applications across diverse domains, encompassing intelligent industrial systems, residential environments, personal gadgets, and automobiles. This has spurred groundbreaking advancements while concurrently posing persisten...
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Nisha Rawindaran, Ambikesh Jayal, Edmond Prakash and Chaminda Hewage
Cyber security has made an impact and has challenged Small and Medium Enterprises (SMEs) in their approaches towards how they protect and secure data. With an increase in more wired and wireless connections and devices on SME networks, unpredictable mali...
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Max Schrötter, Andreas Niemann and Bettina Schnor
Over the last few years, a plethora of papers presenting machine-learning-based approaches for intrusion detection have been published. However, the majority of those papers do not compare their results with a proper baseline of a signature-based intrusi...
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Jesús Díaz-Verdejo, Javier Muñoz-Calle, Antonio Estepa Alonso, Rafael Estepa Alonso and Germán Madinabeitia
Signature-based Intrusion Detection Systems (SIDS) play a crucial role within the arsenal of security components of most organizations. They can find traces of known attacks in the network traffic or host events for which patterns or signatures have been...
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Mohammed Zakariah and Abdulaziz S. Almazyad
The prevalence of Internet of Things (IoT) technologies is on the rise, making the identification of anomalies in IoT systems crucial for ensuring their security and reliability. However, many existing approaches rely on static classifiers and immutable ...
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Helmut Neuschmied, Martin Winter, Branka Stojanovic, Katharina Hofer-Schmitz, Josip Bo?ic and Ulrike Kleb
In the face of emerging technological achievements, cyber security remains a significant issue. Despite the new possibilities that arise with such development, these do not come without a drawback. Attackers make use of the new possibilities to take adva...
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Ammar Alazab, Ansam Khraisat, Moutaz Alazab and Sarabjot Singh
Websites on the Internet are becoming increasingly vulnerable to malicious JavaScript code because of its strong impact and dramatic effect. Numerous recent cyberattacks use JavaScript vulnerabilities, and in some cases employ obfuscation to conceal thei...
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Maya Hilda Lestari Louk and Bayu Adhi Tama
As a system capable of monitoring and evaluating illegitimate network access, an intrusion detection system (IDS) profoundly impacts information security research. Since machine learning techniques constitute the backbone of IDS, it has been challenging ...
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Michael Heigl, Enrico Weigelt, Dalibor Fiala and Martin Schramm
Over the past couple of years, machine learning methods?especially the outlier detection ones?have anchored in the cybersecurity field to detect network-based anomalies rooted in novel attack patterns. However, the ubiquity of massive continuously genera...
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Salvatore Carta, Alessandro Sebastian Podda, Diego Reforgiato Recupero and Roberto Saia
The dramatic increase in devices and services that has characterized modern societies in recent decades, boosted by the exponential growth of ever faster network connections and the predominant use of wireless connection technologies, has materialized a ...
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Evgenia Novikova, Elena Doynikova and Sergey Golubev
One of the challenges in the Internet of Things systems is the security of the critical data, for example, data used for intrusion detection. The paper research construction of an intrusion detection system that ensures the confidentiality of critical da...
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Yun Wang, William Chu, Sarah Fields, Colleen Heinemann and Zach Reiter
Most of the existing research works on the intrusion detection problem in a wireless sensor network (WSN) assume linear or random mobility patterns in abstracting intruders? models in traversing the WSN field. However, in real-life WSN applications, an i...
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Moody Alhanaya and Khalil Al-Shqeerat
Internet of Things technology opens the horizon to a broader scope of intelligent applications in smart cities. However, the massive amount of traffic exchanged among devices may cause security risks, especially when devices are compromised or vulnerable...
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Sapna Sadhwani, Baranidharan Manibalan, Raja Muthalagu and Pranav Pawar
The study in this paper characterizes lightweight IoT networks as being established by devices with few computer resources, such as reduced battery life, processing power, memory, and, more critically, minimal security and protection, which are easily vu...
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Niraj Thapa, Zhipeng Liu, Dukka B. KC, Balakrishna Gokaraju and Kaushik Roy
The development of robust anomaly-based network detection systems, which are preferred over static signal-based network intrusion, is vital for cybersecurity. The development of a flexible and dynamic security system is required to tackle the new attacks...
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Yanping Shen, Kangfeng Zheng, Yanqing Yang, Shuai Liu and Meng Huang
Various machine-learning methods have been applied to anomaly intrusion detection. However, the Intrusion Detection System still faces challenges in improving Detection Rate and reducing False Positive Rate. In this paper, a Class-Level Soft-Voting Ensem...
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Omar Abdulkhaleq Aldabash and Mehmet Fatih Akay
An IDS (Intrusion Detection System) is essential for network security experts, as it allows one to identify and respond to abnormal traffic present in a network. An IDS can be utilized for evaluating the various types of malicious attacks. Hence, detecti...
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Shweta More, Moad Idrissi, Haitham Mahmoud and A. Taufiq Asyhari
The rapid proliferation of new technologies such as Internet of Things (IoT), cloud computing, virtualization, and smart devices has led to a massive annual production of over 400 zettabytes of network traffic data. As a result, it is crucial for compani...
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Emanuele Santonicola, Ennio Andrea Adinolfi, Simone Coppola and Francesco Pascale
Nowadays, a vehicle can contain from 20 to 100 ECUs, which are responsible for ordering, controlling and monitoring all the components of the vehicle itself. Each of these units can also send and receive information to other units on the network or exter...
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Chinyang Henry Tseng, Woei-Jiunn Tsaur and Yueh-Mao Shen
In detecting large-scale attacks, deep neural networks (DNNs) are an effective approach based on high-quality training data samples. Feature selection and feature extraction are the primary approaches for data quality enhancement for high-accuracy intrus...
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