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Cyber-attacks are constantly increasing and can prove difficult to mitigate, even with proper cybersecurity controls. Currently, cyber threat intelligence (CTI) efforts focus on internal threat feeds such as antivirus and system logs. While this approach is valuable, it is reactive in nature as it relies on activity which has already occurred. CTI experts have argued that an actionable CTI program...
Identifying the physical person behind an SNS account has become a critical issue in investigations of SNS-involved crime cases. It is a challenging task because information provided by users on an SNS platform could be false, conflicting, missing and deceptive. One way to gain an accurate profile of a user is to link up all their multiple accounts created on different social platforms, which is referred...
Terror operations are carried out by a team of terrorists with their interaction and cooperation. Different tie strengths, such as acquaintances, friends, and family members, influence the construction and reconstruction of the operation team. Understanding the interaction patterns of tie strength might be useful not only for advancing our understanding of terror operations, but ultimately for providing...
This paper presents a system that uses machine learning to recognize military vehicles in social media images. To do so, the system draws on recent advances in applying deep neural networks to computer vision tasks, while also making extensive use of openly available libraries, models and data. Training a vehicle recognition system over three classes, the paper reports on two experiments that use...
Public sentiment permeated through social media is usually regarded as an important measure for public opinion monitoring, policy making, and so forth. However, the deluge of user-generated content in web, especially in social platform, causes great challenge to public sentiment analysis tasks. Therefore, Web-derived Emotional Word Detection (WEWD) is proposed as a fundamental tool aims to alleviate...
Public sentiments affecting health outcomes are increasingly modulated by social media. Existing literature mainly focus on investigating how network structure affects the contagion of health sentiments. However, most of these studies neglect that the interaction topology change in time. In fact, the change of inter-individual connections over time is associated with individual attributes. The mechanism...
With the development of social media technology, users often register accounts, post messages and create friend links on several different platforms. Performing user identity mapping on multi-platform based on the behavior patterns of users is considerable for network supervision and personalization service. The existing methods focus on utilizing either text information or structure information alone...
Social media has become an important platform for people to express opinions, share information and communicate with others. Detecting and tracking topics from social media can help people grasp essential information and facilitate many security-related applications. As social media texts are usually short, traditional topic evolution models built based on LDA or HDP often suffer from the data sparsity...
In this paper we present results of a research on automatic extremist text detection. For this purpose an experimental dataset in the Russian language was created. According to the Russian legislation we cannot make it publicly available. We compared various classification methods (multinomial naive Bayes, logistic regression, linear SVM, random forest, and gradient boosting) and evaluated the contribution...
Cyber-trafficking is the illegal transport of humans, drugs, weapons, or goods by means of Internet-enabled electronic devices. Currently, there is a lack of surveillance and understanding of the rapidly growing social concern about cyber-trafficking (CT). This paper describes the Cyber-Trafficking Surveillance System (CyTraSS) and provides preliminary findings of using the system to monitor CT social...
Online emotion diffusion is a compound process that involves interactions with multiple modalities. For instance, different behaviors influence the velocity and scale of emotion diffusion in online communities. Depicting and predicting massive online emotions helps to guide the trend of emotion evolution, thus avoiding unprecedented damages in crises. However, most existing work tries to depict and...
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