Security techniques for intelligent spam sensing and anomaly detection in online social platforms

Copyright © 2020 Institute of Advanced Engineering and Science. All rights reserved. The recent advances in communication and mobile technologies made it easier to access and share information for most people worldwide. Among the most powerful information spreading platforms are the Online Social Networks (OSN)s that allow Internet-connected users to share different information such as instant messages, tweets, photos, and videos. Adding to that many governmental and private institutions use the OSNs such as Twitter for official announcements. Consequently, there is a tremendous need to provide the required level of security for OSN users. However, there are many challenges due to the different protocols and variety of mobile apps used to access OSNs. Therefore, traditional security techniques fail to provide the needed security and privacy, and more intelligence is required. Computational intelligence adds high-speed computation, fault tolerance, adaptability, and error resilience when used to ensure security in OSN apps. This research provides a comprehensive related work survey and investigates the application of artificial neural networks for intrusion detection systems and spam filtering for OSNs. In addition, we use the concept of social graphs and weighted cliques in the detection of suspicious behavior of certain online groups and to prevent further planned actions such as cyber/terrorist attacks before they happen

Security techniques for intelligent spam sensing and anomaly detection in online social platforms

Copyright © 2020 Institute of Advanced Engineering and Science. All rights reserved. The recent advances in communication and mobile technologies made it easier to access and share information for most people worldwide. Among the most powerful information spreading platforms are the Online Social Networks (OSN)s that allow Internet-connected users to share different information such as instant messages, tweets, photos, and videos. Adding to that many governmental and private institutions use the OSNs such as Twitter for official announcements. Consequently, there is a tremendous need to provide the required level of security for OSN users. However, there are many challenges due to the different protocols and variety of mobile apps used to access OSNs. Therefore, traditional security techniques fail to provide the needed security and privacy, and more intelligence is required. Computational intelligence adds high-speed computation, fault tolerance, adaptability, and error resilience when used to ensure security in OSN apps. This research provides a comprehensive related work survey and investigates the application of artificial neural networks for intrusion detection systems and spam filtering for OSNs. In addition, we use the concept of social graphs and weighted cliques in the detection of suspicious behavior of certain online groups and to prevent further planned actions such as cyber/terrorist attacks before they happen

A study on IoT-related security issues, challenges, and solutions.

The Internet of Things is now being developed to be the most cutting-edge and user-centric technology in the works. Raising both an individual\u27s and society\u27s level of life is the goal of this endeavour. When a technology advances, it always acquires certain flaws, which are always open to being attacked and taken advantage of in some manner. In this work, the problems posed by the Internet of Things (IoT) based on the fundamental security principles of confidentiality, integrity, and availability are discussed. It has also been discussed how an overview of the security restrictions, requirements, processes, and solutions implemented for the challenges generated in secured communication inside the IoT ecosystem. In this paper, the vulnerabilities of the underlying Internet of Things network are brought to light, and many security concerns on multiple tiers of the Internet of Things ecosystem have been examined. Based on the findings of our research into the vulnerabilities that are now present, a variety of potential solutions have been proposed in order to solve the ongoing problems that are plaguing the IoT ecosystem. In addition to that, it provides an overview of the various protocols that are used for security in IoT

Characterizing user behavior in online social networks: Analysis of the regular use of Facebook

The analysis of user behaviour in online social networks (OSNs) is one of the important research interests related to human-computer interactions. OSNs gives a large space to share news with no limits around the world and allows user to benefit from properties of this interactive and dynamic system. The study of user behaviour on a social and popular platform characterized by the use of new technologies requires to understand and the analysis of collective behaviour on Facebook. This paper aims to analyse the usage patterns in OSNs using the visible interactions of Facebook, by studying the time of activity and the evolution of human behaviour through a process of detection of visible and non-volatile interactions. In the first step, we perform a data collection process based on breadth first search algorithm (BFS) and semi-supervised crawler agent. In the second step, we build an interaction quantification process to measure users’ activities and analysis related time series. The study of the frequency of periodic use has shown that the communities monitored follow a weekly rhythm that decreases over time to reach a frequency of daily use, which reflects a stability of activities and a case of dependency of use

The protect mobile user data in Russia

This paper studies the issue the information security for smartphone users in Russia. The report analyses the regulations the state uses to prevent undeclared functionality and malicious programs in mobile phones in Russia; the law enforcement practice in this area; the responsibility of legal entities, officials and persons for non-compliance with the requirements for standardization, ensuring information security and violation of declaration of conformity. The paper develops proposals to improve state regulation of undeclared functionality of mobile devices providing the collection of information, including confidential data. The report discusses specific ethical issues related to privacy, including matters relating to compensation for damage resulting from the leakage of personal information and develops proposals for legal ensuring the information security of mobile phone users. The report first outlines the main actors, terms and concepts used in the report. Second the standards for mobile phone developers, although there is no guarantee of complete information security. In this case, the peculiarity of Russia is that standards used in the field of information security are voluntary. Third how law enforcement agencies protect the user community. In this case there is a potential danger that this may entail uncontrolled access of government agencies to confidential data

IoT Privacy and Security: Challenges and Solutions

Privacy and security are among the significant challenges of the Internet of Things (IoT). Improper device updates, lack of efficient and robust security protocols, user unawareness, and famous active device monitoring are among the challenges that IoT is facing. In this work, we are exploring the background of IoT systems and security measures, and identifying (a) different security and privacy issues, (b) approaches used to secure the components of IoT-based environments and systems, (c) existing security solutions, and (d) the best privacy models necessary and suitable for different layers of IoT driven applications. In this work, we proposed a new IoT layered model: generic and stretched with the privacy and security components and layers identification. The proposed cloud/edge supported IoT system is implemented and evaluated. The lower layer represented by the IoT nodes generated from the Amazon Web Service (AWS) as Virtual Machines. The middle layer (edge) implemented as a Raspberry Pi 4 hardware kit with support of the Greengrass Edge Environment in AWS. We used the cloud-enabled IoT environment in AWS to implement the top layer (the cloud). The security protocols and critical management sessions were between each of these layers to ensure the privacy of the users’ information. We implemented security certificates to allow data transfer between the layers of the proposed cloud/edge enabled IoT model. Not only is the proposed system model eliminating possible security vulnerabilities, but it also can be used along with the best security techniques to countermeasure the cybersecurity threats facing each one of the layers; cloud, edge, and IoT