Framework for surveillance of instant messages in instant messengers and social neworking sites using data mining and ontology

Ali, Mohammed Mahmood; Mohammed, Khaja Moizuddin; Rajamani, Lakshmi

doi:10.1109/techsym.2014.6808064

Cited by 12 publications

(5 citation statements)

References 8 publications

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“…Another frame work which detects suspicious messages in Instant messengers and social networking sites using Ontology and Association Rule Mining (ARM) is used to detect the domain of the message keywords [33]. Pre-defined phishing rules have been considered which are to be mapped with the ontology generator through NLP, to obtain the domain of the suspected word.…”

Section: Related Workmentioning

confidence: 99%

“…Pre-defined phishing rules have been considered which are to be mapped with the ontology generator through NLP, to obtain the domain of the suspected word. The user is not alerted instead the e-crime department is notified if any suspicious activity is detected [33]. The overall detection is content based and thus in spite of using the NLP, the context part is not explored, the use of ontology is restricted to information extraction and domain identification only.…”

Section: Related Workmentioning

confidence: 99%

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Phishing Detection in IMS Using Domain Ontology and CBA - An Innovative Rule Generation Approach

Qaseem¹,

Govardhan²

2014

IJIST

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Phishing Detection in IMS Using Domain Ontology and CBA - An Innovative Rule Generation Approach

Qaseem¹,

Govardhan²

2014

IJIST

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“…Facebook Messenger is an instant messaging application that allows users to share messages, videos, photos, location, create group chats, play games, and send money using debit card details 16 . The study of 17 also noted additional more features including feature to play games among the users.…”

Section: Introductionmentioning

confidence: 99%

Examining artifacts generated by setting Facebook Messenger as a default SMS application on Android: Implication for personal data privacy

Ntonja

Ashawa

2020

Security and Privacy

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The use of mobile devices and social media applications in organized crime is increasingly increasing. Facebook Messenger is the most popular social media applications used globally. Unprecedented time is spent by many interacting globally with known and unknown individuals using Facebook. During their interaction, personal information is uploaded. Thus, crafting a myriad of privacy trepidation to users. While there are researches performed on the forensic artifacts' extraction from Facebook, no research is conducted on setting Facebook Messenger applications as a default messaging application on Android. Two Android mobile devices were used for data generation and Facebook Messenger account was created. Disc imaging and data partition were examined and accessed to identify changes in the orca database of the application package using DB browser. The data were then generated using unique words which were used for conducting key searches. The research discovered that mqtt_log_event0.txt of the Com.Facebook.orca/Cache directory stores chat when messenger is set as a default messaging app. The research finding shows that chats are recorded under messages tab together with SMS of data/data/com.facebook.orca/databases/smstakeover_db and data/data/com.facebook.orca/databases/threads_db. This indicates that only smstakeover_db stores SMS messaging information when using messenger application. It is observed that once the user deletes a sent SMS message, the phone number and the deleted time stamp remained in the data/data/com.facebook.orca/databases/smstakeover_db database in the address_table are recoverable. The results suggest that anonymization of data is essential if Facebook chats are to be shared for further research into social media content.

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“…The number of worldwide users is expected to reach some 3.02 billion by 2021 1 , around a third of the Earth's entire population. As of March 31, 2019, Facebook claims to have 2.38 billion monthly active users worldwide 2 . This expansion in connectedness among people on digital platforms has created a vast repository of information with potential value for LEAs in to use more efficiently for making informed decisions.…”

Section: Introductionmentioning

confidence: 99%

Towards Designing a Knowledge Graph-Based Framework for Investigating and Preventing Crime on Online Social Networks

Elezaj

Yayilgan

Kalemi

et al. 2019

Communications in Computer and Information Science

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Online Social Networks (OSNs) have fundamentally and permanently altered the arena of digital and classical crime. Recently, law enforcement agencies (LEAs) have been using OSNs as a data source to collect Open Source Intelligence for fighting and preventing crime. However, most existing technological developments for LEAs to fight and prevent crime rely on conventional database technology, which poses problems. As social network usage is increasing rapidly, storing and querying data for information retrieval is critical because of the characteristics of social networks, such as unstructured nature, high volumes, velocity, and data interconnectivity. This paper presents a knowledge graph-based framework, an outline of a framework designed to support crime investigators solve and prevent crime, from data collection to inferring digital evidence admissible in court. The main component of the proposed framework is a hybrid ontology linked to a graph database, which provides LEAs with the possibility to process unstructured data and identify hidden patterns and relationships in the interconnected data of OSNs.

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Framework for surveillance of instant messages in instant messengers and social neworking sites using data mining and ontology

Cited by 12 publications

References 8 publications

Phishing Detection in IMS Using Domain Ontology and CBA - An Innovative Rule Generation Approach

Phishing Detection in IMS Using Domain Ontology and CBA - An Innovative Rule Generation Approach

Examining artifacts generated by setting Facebook Messenger as a default SMS application on Android: Implication for personal data privacy

Towards Designing a Knowledge Graph-Based Framework for Investigating and Preventing Crime on Online Social Networks

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