Spectra of the Spike-Flow Graphs in Geometrically Embedded Neural Networks

Piersa, Jarosław; Schreiber, Tomasz

doi:10.1007/978-3-642-29347-4_17

Cited by 4 publications

(2 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…There is a high possibility that some malicious behavior or thoughts and posts might take place within these socialization activities. Here comes the important role of the social graphs to build a trustworthiness model based on different social activities that take place between users within the same group [60]. It is believed that the social graphs can be constructed specially between cliques to capture different types of social activities.…”

Section: Clique-based Detection Methodologymentioning

confidence: 99%

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

Aldwairi

Tawalbeh

2020

IJECE

View full text Add to dashboard Cite

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.

show abstract

Section: Clique-based Detection Methodologymentioning

confidence: 99%

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

Aldwairi

Tawalbeh

2020

IJECE

View full text Add to dashboard Cite

show abstract

“…A social graph depicts the personal relationships among users in an OSN, and is the cornerstone for the creation of a strong model of trustworthiness that represents all kinds of social activities [19]. Social graphs are heterogeneous because they capture different kinds of social activities such as posting, sharing, and messaging.…”

Section: B Structure Of An Osnmentioning

confidence: 99%

Measuring Reputation and Influence in Online Social Networks: A Systematic Literature Review

et al. 2020

View full text Add to dashboard Cite

Online Social Networks (OSNs) are an integral part of the modern lifestyle, and the use of OSN is highly prevalent today. OSNs have enabled the generation of unprecedented quantities of data on users, their interests, relationships, actions, opinions, locations visited, items purchased, and their experiences in various aspects of life. Data and information related to reputation and influence exist on OSNs and are hidden. The objective of this study is to provide a better and deeper understanding and a detailed review of the current state of research pertaining to the measurement of reputation and influence in OSNs, specifically Twitter. We conducted a Systematic Literature Review to collect, analyze, and synthesize data on the accuracy and value of previous literature that has focused on this field, has addressed a variety of topics, and has been published in digital databases between 2010 and September 2019. We followed a predefined review procedure that integrated both automatic and manual search strategies to cover all relevant research papers published in this period.

show abstract

Eigenvalue Spectra of Functional Networks in fMRI Data and Artificial Models

Zając

Piersa

2013

Artificial Intelligence and Soft Computing

View full text Add to dashboard Cite

Spectra of the Spike-Flow Graphs in Geometrically Embedded Neural Networks

Cited by 4 publications

References 11 publications

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

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

Measuring Reputation and Influence in Online Social Networks: A Systematic Literature Review

Eigenvalue Spectra of Functional Networks in fMRI Data and Artificial Models

Contact Info

Product

Resources

About