Wajdi Alhakami^*

CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 3211-3237, 2024, DOI:10.32604/cmc.2023.043935 - 15 May 2024

Abstract The Kingdom of Saudi Arabia (KSA) has achieved significant milestones in cybersecurity. KSA has maintained solid regulatory mechanisms to prevent, trace, and punish offenders to protect the interests of both individual users and organizations from the online threats of data poaching and pilferage. The widespread usage of Information Technology (IT) and IT Enable Services (ITES) reinforces security measures. The constantly evolving cyber threats are a topic that is generating a lot of discussion. In this league, the present article enlists a broad perspective on how cybercrime is developing in KSA at present and also takes… More >

Fiaz Majeed¹, Afzaal Ahmad¹, Muhammad Awais Hassan², Muhammad Shafiq^3,*, Jin-Ghoo Choi³, Habib Hamam^4,5,6,7

CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 601-614, 2023, DOI:10.32604/cmc.2023.036074 - 31 October 2023

Abstract Every day, the media reports tons of crimes that are considered by a large number of users and accumulate on a regular basis. Crime news exists on the Internet in unstructured formats such as books, websites, documents, and journals. From such homogeneous data, it is very challenging to extract relevant information which is a time-consuming and critical task for the public and law enforcement agencies. Keyword-based Information Retrieval (IR) systems rely on statistics to retrieve results, making it difficult to obtain relevant results. They are unable to understand the user's query and thus face word… More >

Junxiang Yin^*

CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 4601-4629, 2023, DOI:10.32604/cmc.2023.034190 - 31 October 2022

Abstract The objective of crime prediction, one of the most important technologies in social computing, is to extract useful information from many existing criminal records to predict the next process-related crime. It can aid the police in obtaining criminal information and warn the public to be vigilant in certain areas. With the rapid growth of big data, the Internet of Things, and other technologies, as well as the increasing use of artificial intelligence in forecasting models, crime prediction models based on deep learning techniques are accelerating. Therefore, it is necessary to classify the existing crime prediction… More >

Ashit Kumar Dutta^1,*, Basit Qureshi², Yasser Albagory³, Majed Alsanea⁴, Manal Al Faraj¹, Abdul Rahaman Wahab Sait⁵

Computer Systems Science and Engineering, Vol.44, No.3, pp. 2395-2409, 2023, DOI:10.32604/csse.2023.027502 - 01 August 2022

Abstract Fake news and its significance carried the significance of affecting diverse aspects of diverse entities, ranging from a city lifestyle to a country global relativity, various methods are available to collect and determine fake news. The recently developed machine learning (ML) models can be employed for the detection and classification of fake news. This study designs a novel Chaotic Ant Swarm with Weighted Extreme Learning Machine (CAS-WELM) for Cybersecurity Fake News Detection and Classification. The goal of the CAS-WELM technique is to discriminate news into fake and real. The CAS-WELM technique initially pre-processes the input More >

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 - 10 August 2023

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 More >

Abdulsamad A. AL-Marghilani^*

CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 809-824, 2022, DOI:10.32604/cmc.2022.021185 - 03 November 2021

Abstract Presently, suspect prediction of crime scenes can be considered as a classification task, which predicts the suspects based on the time, space, and type of crime. Performing digital forensic investigation in a big data environment poses several challenges to the investigational officer. Besides, the facial sketches are widely employed by the law enforcement agencies for assisting the suspect identification of suspects involved in crime scenes. The sketches utilized in the forensic investigations are either drawn by forensic artists or generated through the computer program (composite sketches) based on the verbal explanation given by the eyewitness… More >

Nasir Mahmood^*, Muhammad Usman Ghani Khan

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4411-4428, 2022, DOI:10.32604/cmc.2022.013956 - 11 October 2021

Abstract This study proposes an architecture for the prediction of extremist human behaviour from projected suicide bombings. By linking ‘dots’ of police data comprising scattered information of people, groups, logistics, locations, communication, and spatiotemporal characters on different social media groups, the proposed architecture will spawn beneficial information. This useful information will, in turn, help the police both in predicting potential terrorist events and in investigating previous events. Furthermore, this architecture will aid in the identification of criminals and their associates and handlers. Terrorism is psychological warfare, which, in the broadest sense, can be defined as the… More >

Yeshi Nidup^*

Journal of Cyber Security, Vol.3, No.3, pp. 133-148, 2021, DOI:10.32604/jcs.2021.024136 - 17 November 2021

Abstract This study aimed to find out the awareness about the online security threat and understanding of the preventive measuresto secure the youthsfrom online risks. For this, a quantitative method was applied and the survey questionnaire was instituted to collect the data randomly from the youths studying in class eleven and higher. A total of 264 youths, 147 female and 117 male responded to the survey questionnaire. The data was organized and analyzed using Excel data analysis tool package, interpreted and represented in the form of graphs with some explanations. The awareness about the online security… More >

Isha Puthige¹, Kartikay Bansal¹, Chahat Bindra¹, Mahekk Kapur¹, Dilbag Singh¹, Vipul Kumar Mishra¹, Apeksha Aggarwal¹, Jinhee Lee², Byeong-Gwon Kang², Yunyoung Nam^2,*, Reham R. Mostafa³

CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 2761-2777, 2021, DOI:10.32604/cmc.2021.018128 - 21 July 2021

Abstract The study aims to formulate a solution for identifying the safest route between any two inputted Geographical locations. Using the New York City dataset, which provides us with location tagged crime statistics; we are implementing different clustering algorithms and analysed the results comparatively to discover the best-suited one. The results unveil the fact that the K-Means algorithm best suits for our needs and delivered the best results. Moreover, a comparative analysis has been performed among various clustering techniques to obtain best results. we compared all the achieved results and using the conclusions we have developed More >

Hyun Yoo¹, Ji-Won Baek², Kyungyong Chung^3,*

Intelligent Automation & Soft Computing, Vol.29, No.2, pp. 319-334, 2021, DOI:10.32604/iasc.2021.018115 - 16 June 2021

Abstract With the convergence and development of the Internet of things (IoT) and artificial intelligence, closed-circuit television, wearable devices, and artificial neural networks have been combined and applied to crime prevention and follow-up measures against crimes. However, these IoT devices have various limitations based on the physical environment and face the fundamental problem of privacy violations. In this study, voice data are collected and emotions are classified based on an acoustic sensor that is free of privacy violations and is not sensitive to changes in external environments, to overcome these limitations. For the classification of emotions… More >