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Abstract
Among the myriad of applications of natural language processing (NLP), assisting law enforcement agencies (LEA) in detecting and preventing cybercrimes is one of the most recent and promising ones. The promotion of violence or hate by digital means is considered a cybercrime as it leverages the cyberspace to support illegal activities in the real world. The paper at hand proposes a solution that uses neural network (NN) based NLP to monitor suspicious activities in social networks allowing us to identify and prevent related cybercrimes. An LEA can find similar posts grouped in clusters, then determine their level of polarity, and identify a subset of user accounts that promote violent activities to be reviewed extensively as part of an effort to prevent crimes and specifically hostile social manipulation (HSM). Different experiments were also conducted to prove the feasibility of the proposal.
Highlights
Information and communications technology (ICT) has revolutionized our society, and artificial intelligence in particular is currently leading such a revolution, taking a central role able to remarkably impact the near future of humankind [1]. us, researchers devoted to artificial intelligence raised the following question: Could a machine replace some people’s functionalities and become a central axis for the generations in certain aspects of their lives? Starting from such a question, different advances have been made in that regard, and in this paper, we review the ability of artificial intelligence to understand human language
Scenario 2: Black Lives Matter Movement in the United States. is second scenario implied the collection of 18,741 tweets with the hashtag #blm related to the protests in the United States against racism and police abuse in the case of the death of George Floyd. e initial set of tweets was reduced to 1,287 tweets, from 1,131 users accounts, after eliminating retweets to just identify creators of content. e mentioned hashtag refers to the movement “Black Lives Matter” that aims to eradicate white supremacy and build local power to intervene in violence inflicted on black communities. e collection of tweets in this scenario was done on July 15, 2020, when a video appears showing the moments leading up to George Floyd’s death
Deep learning and Natural language processing (NLP) have proven their potential in the support of cybersecurity labors and in the detection of cybercrimes. e adoption of neural network (NN)-based NLP solutions by law enforcement agencies (LEA) would strengthen a national cyber defense strategy reducing considerably the time of attention to cybersecurity incidents and providing LEAs with the capacity to detect and prevent hostile social manipulation (HSM)
Summary
Information and communications technology (ICT) has revolutionized our society, and artificial intelligence in particular is currently leading such a revolution, taking a central role able to remarkably impact the near future of humankind [1]. us, researchers devoted to artificial intelligence raised the following question: Could a machine replace some people’s functionalities and become a central axis for the generations in certain aspects of their lives? Starting from such a question, different advances have been made in that regard, and in this paper, we review the ability of artificial intelligence to understand human language. Other proposals of the use of NLP models in cybersecurity aim to design models to detect hate speech in cyberspace [9] and to interact with suspects to profile their interest regarding online child sexual abuse [3]. In this context, the paper at hand proposes a solution to uncover cybercrimes in social media through NLP.
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