Open Access Journal

ISSN : 2394-2320 (Online)

International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Monthly Journal for Computer Science and Engineering

Open Access Journal

International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Monthly Journal for Computer Science and Engineering

ISSN : 2394-2320 (Online)

Design of Suspicious User Profile Identification system Using ACO Algorithm

Author : Asha 1 Dr. Balkishan 2

Date of Publication :19th February 2018

Abstract: The aim of this paper is to design a system for the identification of suspicious user profiles using Ant Colony Optimization algorithm. The communication technologies and their advancements have greatly influenced our daily lives. The technologies like social networking websites, blogs, chat forums, instant messengers and many more are leading various fascinating trends in today’s world. Unfortunately, the increase in suspicious activities is one of the major causes due to the misuse of the technology. The internet is loaded with very large amount of data. Some people make use of the technology to spread rumours, to spread violence, bully other people, spread hate messages or even perform criminal activities like financial frauds etc. and thus increasing the amount of suspicious content over the internet. In this paper, textual data from social networking websites is considered to detect the suspicious user profiles. A suspicious user profile (SUP) detection system is proposed which considers the text based data as input and retrieves the suspicious user profile based on the extracted features.

Reference :

    1. Murugesan, M. Suruthi, R. Pavitha Devi, S. Deepthi, V. Sri Lavanya, and Annie Princy. "Automated Monitoring Suspicious Discussions on Online Forums Using Data Mining Statistical Corpus Based Approach." Imperial Journal of Interdisciplinary Research 2, no. 5 (2016).
    2. Yen, Ting-Fang, Alina Oprea, Kaan Onarlioglu, Todd Leetham, William Robertson, Ari Juels, and Engin Kirda. "Beehive: Large-scale log analysis for detecting suspicious activity in enterprise networks." In Proceedings of the 29th Annual Computer Security Applications Conference, pp. 199-208. ACM, 2013. 
    3. Khangura, M. Dhaliwal, M. Sehgal. “Identification of Suspicious Activities in Chat Logs using Support Vector Machine and Optimization with Genetic Algorithm.” International Journal for Research in Applied Science & Engineering Technology (IJRASET), VII(5), 2017.
    4. Chiu, Carter, Justin Zhan, and Felix Zhan. "Uncovering Suspicious Activity From Partially Paired and Incomplete Multimodal Data." IEEE Access 5 (2017): 13689-13698.
    5. Patil, Yogesh V., Omkar A. Salvi, Paresh R. Waghmare, Akshay D. Kondilkar, and Vijayalaxmi P. Kadroli. "Abnormal Behaviour Detection on Live Streaming." (2017).
    6. M. Jiang, A. Beutel, P. Cui, B. Hooi, S. Yang, and C. Faloutsos, “Spotting Suspicious Behaviors in Multimodal Data: A General Metric and Algorithms,” IEEE Trans. Knowl. Data Eng., vol. 28, no. 8, pp. 2187–2200, 2016.
    7. Alami, Salim, and OMAR EL BEQQALI. "DETECTING SUSPICIOUS PROFILES USING TEXT ANALYSIS WITHIN SOCIAL MEDIA." Journal of Theoretical & Applied Information Technology 73, no. 3 (2015).

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