Wenlong Zhu^1,*, Yu Miao¹, Shuangshuang Yang², Zuozheng Lian¹, Lianhe Cui¹

CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 3111-3131, 2023, DOI:10.32604/cmc.2023.036159 - 31 March 2023

Abstract Influence maximization of temporal social networks (IMT) is a problem that aims to find the most influential set of nodes in the temporal network so that their information can be the most widely spread. To solve the IMT problem, we propose an influence maximization algorithm based on an improved K-shell method, namely improved K-shell in temporal social networks (KT). The algorithm takes into account the global and local structures of temporal social networks. First, to obtain the kernel value Ks of each node, in the global scope, it layers the network according to the temporal characteristic… More >

R. Gnanakumari^1,*, P. Vijayalakshmi²

Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 2719-2730, 2023, DOI:10.32604/iasc.2023.034145 - 15 March 2023

Abstract In social data analytics, Virtual Community (VC) detection is a primary challenge in discovering user relationships and enhancing social recommendations. VC formation is used for personal interaction between communities. But the usual methods didn’t find the Suspicious Behaviour (SB) needed to make a VC. The Generalized Jaccard Suspicious Behavior Similarity-based Recurrent Deep Neural Network Classification and Ranking (GJSBS-RDNNCR) Model addresses these issues. The GJSBS-RDNNCR model comprises four layers for VC formation in Social Networks (SN). In the GJSBS-RDNNCR model, the SN is given as an input at the input layer. After that, the User’s Behaviors… More >

Muhammad Riaz¹, Masooma Raza Hashmi¹, Faruk Karaaslan², Aslıhan Sezgin³, Mohammed M. Ali Al Shamiri^4,5,*, Mohammed M. Khalaf^6,7

CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.2, pp. 1759-1783, 2023, DOI:10.32604/cmes.2023.023327 - 06 February 2023

Abstract This paper aims to introduce the novel concept of neutrosophic crisp soft set (NCSS), including various types of neutrosophic crisp soft sets (NCSSs) and their fundamental operations. We define NCS-mapping and its inverse NCS-mapping between two NCS-classes. We develop a robust mathematical modeling with the help of NCS-mapping to analyze the emerging trends in social networking systems (SNSs) for our various generations. We investigate the advantages, disadvantages, and natural aspects of SNSs for five generations. With the changing of the generations, it is analyzed that emerging trends and the benefits of SNSs are increasing day More > Graphic Abstract

Diana T. Mosa^1,2, Mahmoud Y. Shams^3,*, Amr A. Abohany², El-Sayed M. El-kenawy⁴, M. Thabet⁵

CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1271-1290, 2023, DOI:10.32604/cmc.2023.036422 - 06 February 2023

Abstract Cyber Attacks are critical and destructive to all industry sectors. They affect social engineering by allowing unapproved access to a Personal Computer (PC) that breaks the corrupted system and threatens humans. The defense of security requires understanding the nature of Cyber Attacks, so prevention becomes easy and accurate by acquiring sufficient knowledge about various features of Cyber Attacks. Cyber-Security proposes appropriate actions that can handle and block attacks. A phishing attack is one of the cybercrimes in which users follow a link to illegal websites that will persuade them to divulge their private information. One… More >

Rupali Gangarde^1,2,*, Amit Sharma³, Ambika Pawar⁴

CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 2171-2190, 2023, DOI:10.32604/cmc.2023.035559 - 06 February 2023

Abstract Online Social Networks (OSN) sites allow end-users to share a great deal of information, which may also contain sensitive information, that may be subject to commercial or non-commercial privacy attacks. As a result, guaranteeing various levels of privacy is critical while publishing data by OSNs. The clustering-based solutions proved an effective mechanism to achieve the privacy notions in OSNs. But fixed clustering limits the performance and scalability. Data utility degrades with increased privacy, so balancing the privacy utility trade-off is an open research issue. The research has proposed a novel privacy preservation model using the… More >

C. Suganthini^*, R. Baskaran

Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 1715-1731, 2023, DOI:10.32604/iasc.2023.034019 - 05 January 2023

Abstract In online social networks (OSN), they generate several specific user activities daily, corresponding to the billions of data points shared. However, although users exhibit significant interest in social media, they are uninterested in the content, discussions, or opinions available on certain sites. Therefore, this study aims to identify influential communities and understand user behavior across networks in the information diffusion process. Social media platforms, such as Facebook and Twitter, extract data to analyze the information diffusion process, based on which they cascade information among the individuals in the network. Therefore, this study proposes an influential… More >

Farah Batool¹, Abdul Rehman², Dongsun Kim^2,*, Assad Abbas¹, Raheel Nawaz³, Tahir Mustafa Madni¹

CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 6535-6553, 2023, DOI:10.32604/cmc.2023.033832 - 28 December 2022

Abstract The authors propose an informed search greedy approach that efficiently identifies the influencer nodes in the social Internet of Things with the ability to provide legitimate information. Primarily, the proposed approach minimizes the network size and eliminates undesirable connections. For that, the proposed approach ranks each of the nodes and prioritizes them to identify an authentic influencer. Therefore, the proposed approach discards the nodes having a rank (α) lesser than 0.5 to reduce the network complexity. α is the variable value represents the rank of each node that varies between 0 to 1. Node with… More >

Anwer Mustafa Hilal^1,2,*, Aisha Hassan Abdalla Hashim¹, Heba G. Mohamed³, Lubna A. Alharbi⁴, Mohamed K. Nour⁵, Abdullah Mohamed⁶, Ahmed S. Almasoud⁷, Abdelwahed Motwakel²

Computer Systems Science and Engineering, Vol.45, No.2, pp. 2033-2047, 2023, DOI:10.32604/csse.2023.031181 - 03 November 2022

Abstract Recent developments on Internet and social networking have led to the growth of aggressive language and hate speech. Online provocation, abuses, and attacks are widely termed cyberbullying (CB). The massive quantity of user generated content makes it difficult to recognize CB. Current advancements in machine learning (ML), deep learning (DL), and natural language processing (NLP) tools enable to detect and classify CB in social networks. In this view, this study introduces a spotted hyena optimizer with deep learning driven cybersecurity (SHODLCS) model for OSN. The presented SHODLCS model intends to accomplish cybersecurity from the identification More >

Hanan Abdullah Mengash¹, Jaber S. Alzahrani², Majdy M. Eltahir³, Fahd N. Al-Wesabi⁴, Abdullah Mohamed⁵, Manar Ahmed Hamza^6,*, Radwa Marzouk⁷

Computer Systems Science and Engineering, Vol.45, No.2, pp. 1393-1407, 2023, DOI:10.32604/csse.2023.030328 - 03 November 2022

Abstract Presently, smart cities play a vital role to enhance the quality of living among human beings in several ways such as online shopping, e-learning, e-healthcare, etc. Despite the benefits of advanced technologies, issues are also existed from the transformation of the physical word into digital word, particularly in online social networks (OSN). Cyberbullying (CB) is a major problem in OSN which needs to be addressed by the use of automated natural language processing (NLP) and machine learning (ML) approaches. This article devises a novel search and rescue optimization with machine learning enabled cybersecurity model for… More >

Swarna Sudha Muppudathi¹, Valarmathi Krishnasamy^2,*

Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 1027-1042, 2023, DOI:10.32604/iasc.2023.031165 - 29 September 2022

Abstract Social Networking Sites (SNSs) are nowadays utilized by the whole world to share ideas, images, and valuable contents by means of a post to reach a group of users. The use of SNS often inflicts the physical and the mental health of the people. Nowadays, researchers often focus on identifying the illegal behaviors in the SNS to reduce its negative influence. The state-of-art Natural Language processing techniques for anomaly detection have utilized a wide annotated corpus to identify the anomalies and they are often time-consuming as well as certainly do not guarantee maximum accuracy. To overcome… More >