Machine learning for SPAM detection

P Teja Nallamothu… - Asian Journal of …, 2023 - eprint.subtopublish.com
In practically every industry today, from business to education, emails/messages are used.
Ham and spam are the two subcategories of emails/messages. Email or message spam …

Trustworthy llms: a survey and guideline for evaluating large language models' alignment

Y Liu, Y Yao, JF Ton, X Zhang, R Guo, H Cheng… - arXiv preprint arXiv …, 2023 - arxiv.org
Ensuring alignment, which refers to making models behave in accordance with human
intentions [1, 2], has become a critical task before deploying large language models (LLMs) …

Detecting harmful content on online platforms: what platforms need vs. where research efforts go

A Arora, P Nakov, M Hardalov, SM Sarwar… - ACM Computing …, 2023 - dl.acm.org
The proliferation of harmful content on online platforms is a major societal problem, which
comes in many different forms, including hate speech, offensive language, bullying and …

Detection of fake accounts on social media using multimodal data with deep learning

B Goyal, NS Gill, P Gulia, O Prakash… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
In recent years, the proliferation of fake accounts on social media has become a significant
concern for individuals, organizations, and society. Fake accounts play an important role in …

[PDF][PDF] Gamified inoculation against misinformation in India: a randomized control trial

T Harjani, MS Basol, J Roozenbeek… - Journal of Trial and …, 2023 - assets.pubpub.org
Although the spread of misinformation is a pervasive and disruptive global problem, extant
research is skewed towards “WEIRD” countries leaving questions about how to tackle …

A comprehensive review of security threats and solutions for the online social networks industry

NA Nawaz, K Ishaq, U Farooq, A Khalil… - PeerJ Computer …, 2023 - peerj.com
The term “cyber threats” refers to the new category of hazards that have emerged with the
rapid development and widespread use of computing technologies, as well as our growing …

Anti-ant framework for android malware detection and prevention using supervised learning

M Awais, MA Tariq, J Iqbal… - 2023 4th International …, 2023 - ieeexplore.ieee.org
Android users have been increasing drastically by the day, therefore apps for android users
are being introduced frequently in the market which are currently available on the Play …

SEBD: A Stream Evolving Bot Detection Framework with Application of PAC Learning Approach to Maintain Accuracy and Confidence Levels

E Alothali, K Hayawi, H Alashwal - Applied Sciences, 2023 - mdpi.com
A simple supervised learning model can predict a class from trained data based on the
previous learning process. Trust in such a model can be gained through evaluation …

Detecting suspicious transactions in a virtual-currency-enabled online social network

Y Zhou, B Hu, J Zhang, L Sun, X Zhu, T Liu - Journal of Network and …, 2023 - Elsevier
Online social networks (OSN) have started to integrate financial capabilities such as the
usage of virtual currency. In OSNs with such capabilities, user accounts can also be used as …

Digital fingerprinting for identifying malicious collusive groups on Twitter

R Ikwu, L Giommoni, A Javed, P Burnap… - Journal of …, 2023 - academic.oup.com
Propagation of malicious code on online social networks (OSNs) is often a coordinated effort
by collusive groups of malicious actors hiding behind multiple online identities (or digital …