Adnan Ali¹, Jinlong Li¹, Huanhuan Chen¹, Uzair Aslam Bhatti², Asad Khan^3,*

Intelligent Automation & Soft Computing, Vol.38, No.3, pp. 241-258, 2023, DOI:10.32604/iasc.2023.041645

Abstract Spammer detection is to identify and block malicious activities performing users. Such users should be identified and terminated from social media to keep the social media process organic and to maintain the integrity of online social spaces. Previous research aimed to find spammers based on hybrid approaches of graph mining, posted content, and metadata, using small and manually labeled datasets. However, such hybrid approaches are unscalable, not robust, particular dataset dependent, and require numerous parameters, complex graphs, and natural language processing (NLP) resources to make decisions, which makes spammer detection impractical for real-time detection. For example, graph mining requires neighbors’… More >

R. Gnanakumari^1,*, P. Vijayalakshmi²

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

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 (UB) are extracted in the… More >

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

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 of the online security challenges… More >

T. Shanmuigapriya^1,*, S. Swamynathan², Thiruvaazhi Uloli³

Computer Systems Science and Engineering, Vol.43, No.3, pp. 1327-1339, 2022, DOI:10.32604/csse.2022.024440

Abstract Preserving privacy of the user is a very critical requirement to be met with all the international laws like GDPR, California privacy protection act and many other bills in place. On the other hand, Online Social Networks (OSN) has a wide spread recognition among the users, as a means of virtual communication. OSN may also acts as an identity provider for both internal and external applications. While it provides a simplified identification and authentication function to users across multiple applications, it also opens the users to a new spectrum of privacy threats. The privacy breaches costs to the users as… More >

T. Manojpraphakar^*, A. Soundarrajan

Intelligent Automation & Soft Computing, Vol.34, No.2, pp. 699-713, 2022, DOI:10.32604/iasc.2022.025090

Abstract Event recommendation allows people to identify various recent upcoming social events. Based on the Profile or User recommendation people will identify the group of users to subscribe the event and to participate, despite it faces cold-start issues intrinsically. The existing models exploit multiple contextual factors to mitigate the cold-start issues in essential applications on profile recommendations to the event. However, those existing solution does not incorporate the correlation and covariance measures among various contextual factors. Moreover, recommending similar profiles to various groups of the events also has not been well analyzed in the existing literature. The proposed prototype model Correlation… More >

Mesfer Al Duhayyim¹, Haya Mesfer Alshahrani², Fahd N. Al-Wesabi³, Mohammed Alamgeer⁴, Anwer Mustafa Hilal^5,*, Mohammed Rizwanullah⁵

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 6257-6270, 2022, DOI:10.32604/cmc.2022.021212

Abstract Cybersecurity encompasses various elements such as strategies, policies, processes, and techniques to accomplish availability, confidentiality, and integrity of resource processing, network, software, and data from attacks. In this scenario, the rising popularity of Online Social Networks (OSN) is under threat from spammers for which effective spam bot detection approaches should be developed. Earlier studies have developed different approaches for the detection of spam bots in OSN. But those techniques primarily concentrated on hand-crafted features to capture the features of malicious users while the application of Deep Learning (DL) models needs to be explored. With this motivation, the current research article… More >