Open Access

ARTICLE

Abdul Rauf¹, Muhammad Asif Khan^1,*, Hamid Hussain Awan², Waseem Shahzad³, Najeeb Ul Husaan⁴
Journal of Cyber Security, Vol.4, No.4, pp. 201-222, 2022, DOI:10.32604/jcs.2022.038791
Abstract In the modern world, law enforcement authorities are facing challenges due to the advanced technology used by criminals to commit crimes. Criminals follow specific patterns to carry out their crimes, which can be identified using machine learning and swarm intelligence approaches. This article proposes the use of the Ant Colony Optimization algorithm to create an associative classification of crime data, which can reveal potential relationships between different features and crime types. The experiments conducted in this research show that this approach can discover various associations among the features of crime data and the specific patterns that major crime types depend… More >

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ARTICLE

Jalaj Pateria^1,*, Laxmi Ahuja¹, Subhranil Som²
Journal of Cyber Security, Vol.4, No.4, pp. 223-238, 2022, DOI:10.32604/jcs.2023.040186
Abstract Cyberattacks have reached their peak during COVID-19, and intruders urge to gain the upper hand in the cybersecurity battlefield, even gaining dominance. Now intruders are trying harder to elude behavior analysis techniques, which in turn gets organization security to come for a toss. This phenomenon is even more prevalent in agentless environments (IOT devices, mobile devices), where we do not have any access to edge devices and rely on packet data to predict any attack and its actors. In this paper, we shall be discussing enhancing the accuracy of anomalous behavior detection techniques for efficient threat intelligence and revamping deception… More >

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295

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REVIEW

Kofi Sarpong Adu-Manu^*, Richard Kwasi Ahiable, Justice Kwame Appati, Ebenezer Essel Mensah
Journal of Cyber Security, Vol.4, No.4, pp. 239-267, 2022, DOI:10.32604/jcs.2023.041095
Abstract Organisations closed their offices and began working from home online to prevent the spread of the COVID-19 virus. This shift in work culture coincided with increased online use during the same period. As a result, the rate of cybercrime has skyrocketed. This study examines the approaches, techniques, and countermeasures of Social Engineering and phishing in this context. The study discusses recent trends in the existing approaches for identifying phishing assaults. We explore social engineering attacks, categorise them into types, and offer both technical and social solutions for countering phishing attacks which makes this paper different from similar works that mainly… More >

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367

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ARTICLE

Arkan Kh Shakr Sabonchi^1,*, Zainab Hashim Obaid²
Journal of Cyber Security, Vol.4, No.4, pp. 269-286, 2022, DOI:10.32604/jcs.2023.041707
Abstract The widespread use of Internet of Things (IoT) devices, such as smart appliances, phones, and watches, has brought about concerns regarding security and privacy. With the increasing prevalence of cyberattacks from both malicious and non-malicious sources, security has become a critical factor in the design of IoT systems. In particular, data security poses a significant challenge due to the growing amount of data stored in IoT systems. Inadequate security measures can allow hackers to take over IoT devices remotely, resulting in significant damage. To address these concerns and improve the security of IoT-based smart door lock systems, this research proposes… More >

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Open Access

ARTICLE

Abdulrahman M. Abdulghani, Mokhles M. Abdulghani, Wilbur L. Walters, Khalid H. Abed^*
Journal of Cyber Security, Vol.4, No.4, pp. 287-298, 2022, DOI:10.32604/jcs.2023.042486
Abstract Unmanned Aerial Vehicles (UAVs) proliferate quickly and play a significant part in crucial tasks, so it is important to protect the security and integrity of UAV communication channels. Intrusion Detection Systems (IDSs) are required to protect the UAV communication infrastructure from unauthorized access and harmful actions. In this paper, we examine a new approach for enhancing intrusion detection in UAV communication channels by utilizing the Long Short-Term Memory network (LSTM) combined with the Synthetic Minority Oversampling Technique (SMOTE) algorithm, and this integration is the binary classification method (LSTM-SMOTE). We successfully achieved 99.83% detection accuracy by using the proposed approach and… More >

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RETRACTION

Y. Sarada Devi, M. Roopa
Journal of Cyber Security, Vol.4, No.4, pp. 299-299, 2022, DOI:10.32604/jcs.2022.040534
Abstract This article has no abstract. More >

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