{"title":"A model of quantifying social relationships","authors":"Disa Sariola","doi":"10.1109/EISIC49498.2019.9108853","DOIUrl":"https://doi.org/10.1109/EISIC49498.2019.9108853","url":null,"abstract":"This article proposes a mathematical model for quantifying relationships between agents within a network based on their similarity, dissimilarity, level of friendship, group and activity status of the agent. We propose a set of functions to facilitate quantifying social dynamics. Our functions cover the comparison of an agent with group and comparing a group with groups based on their set of attributes. We also propose a model of comparison for agent vs. agent based on their attributes, features and the likelihood of attribute similarity between agents. The model employs a method of determining connection probabilities between nodes in order to find hidden connections between agents. We build on existing work in the study of social networks.","PeriodicalId":117256,"journal":{"name":"2019 European Intelligence and Security Informatics Conference (EISIC)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126844207","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"HOTSPOT: Crossing the Air-Gap Between Isolated PCs and Nearby Smartphones Using Temperature","authors":"Mordechai Guri","doi":"10.1109/EISIC49498.2019.9108874","DOIUrl":"https://doi.org/10.1109/EISIC49498.2019.9108874","url":null,"abstract":"Air-gapped computers are hermetically isolated from the Internet to eliminate any means of information leakage. In this paper we present HOTSPOT - a new type of airgap crossing technique. Signals can be sent secretly from air-gapped computers to nearby smartphones and then on to the Internet - in the form of thermal pings. The thermal signals are generated by the CPUs and GPUs and intercepted by a nearby smartphone. We examine this covert channel and discuss other work in the field of air-gap covert communication channels. We present technical background and describe thermal sensing in modern smartphones. We implement a transmitter on the computer side and a receiver Android App on the smartphone side, and discuss the implementation details. We evaluate the covert channel and tested it in a typical work place. Our results show that it possible to send covert signals from air-gapped PCs to the attacker on the Internet through the thermal pings. We also propose countermeasures for this type of covert channel which has thus far been overlooked.","PeriodicalId":117256,"journal":{"name":"2019 European Intelligence and Security Informatics Conference (EISIC)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132664614","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
O. Simek, Alyssa C. Mensch, Lin Li, Charlie K. Dagli
{"title":"Characterization of Disinformation Networks Using Graph Embeddings and Opinion Mining","authors":"O. Simek, Alyssa C. Mensch, Lin Li, Charlie K. Dagli","doi":"10.1109/EISIC49498.2019.9108876","DOIUrl":"https://doi.org/10.1109/EISIC49498.2019.9108876","url":null,"abstract":"Global social media networks' omnipresent access, real time responsiveness and ability to connect with and influence people have been responsible for these networks' sweeping growth. However, as an unintended consequence, these defining characteristics helped create a powerful new technology for spread of propaganda and false information. We present a novel approach for characterizing disinformation networks on social media and distinguishing between different network roles using graph embeddings and hierarchical clustering. In addition, using topic filtering, we correlate the node characterization results with proxy opinion estimates. We plan to study opinion dynamics using signal processing on graphs approaches using longer-timescale social media datasets with the goal to model and infer influence among users in social media networks.","PeriodicalId":117256,"journal":{"name":"2019 European Intelligence and Security Informatics Conference (EISIC)","volume":"95 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134043701","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Andrew J. Park, Lee D. Patterson, Herbert H. Tsang, Ryan Ficocelli, Valerie Spicer, Justin Song
{"title":"Devising and Optimizing Crowd Control Strategies Using Agent-Based Modeling and Simulation","authors":"Andrew J. Park, Lee D. Patterson, Herbert H. Tsang, Ryan Ficocelli, Valerie Spicer, Justin Song","doi":"10.1109/EISIC49498.2019.9108875","DOIUrl":"https://doi.org/10.1109/EISIC49498.2019.9108875","url":null,"abstract":"Sporting events can attract large crowds who are capable of spurring on their teams. Emotionally charged crowds have a potential to become violent and disruptive, damaging and destroying public properties. Managing and controlling riotous crowds is an important responsibility for police officers to keep public order and safety. Devising and optimizing crowd management strategies is difficult without the knowledge of the scale and situations of the crowd in advance. This paper presents a three-dimensional (3D) simulation framework that simulates a riot and the police response to the riot. The simulation framework is based on agent-based modeling and simulation, consisting of crowd agents, police agents, and transit systems. This study focuses on a specific crowd control strategy: pushing the crowd to the public transit. The police officers in this simulation form police lines which move towards targeted positions pushing the crowd towards the position. In order to optimally disperse the crowd, the police lines move towards public access stations in the transit systems, coercing the crowd to the vicinity of the public transit and containing them there. By directing the crowd into the area where public transit picks up passengers, the crowd would dissipate as crowd occupants got on the transit to leave. The 2011 Vancouver Stanley Cup riot is used in the simulation as a case study. The result of the actual crowd control of the event and that of the crowd control simulation are compared. The framework of this study can be used for other sporting or large crowd events at various locations and for devising different crowd control planning strategies.","PeriodicalId":117256,"journal":{"name":"2019 European Intelligence and Security Informatics Conference (EISIC)","volume":"136 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115889187","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
M. Thoma, Ian Oliver, Juha Röning, Madhusanka Liyanage, T. Hoàng
{"title":"EISIC 2019 Keynotes","authors":"M. Thoma, Ian Oliver, Juha Röning, Madhusanka Liyanage, T. Hoàng","doi":"10.1109/eisic49498.2019.9108893","DOIUrl":"https://doi.org/10.1109/eisic49498.2019.9108893","url":null,"abstract":"","PeriodicalId":117256,"journal":{"name":"2019 European Intelligence and Security Informatics Conference (EISIC)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128083698","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
N. Bastas, George Kalpakis, T. Tsikrika, S. Vrochidis, Y. Kompatsiaris
{"title":"A comparative study of clustering methods using word embeddings","authors":"N. Bastas, George Kalpakis, T. Tsikrika, S. Vrochidis, Y. Kompatsiaris","doi":"10.1109/EISIC49498.2019.9108898","DOIUrl":"https://doi.org/10.1109/EISIC49498.2019.9108898","url":null,"abstract":"Grouping large amounts of data is critical for various tasks, including the identification of content on a specific topic of interest (such as terrorism-related content) within a collection of material gathered from online sources. Various existing approaches typically extract relevant features using topic distributions and/or embedding methods, and subsequently apply clustering techniques in the derived representation space. In this work, we present a comparative study using Latent Dirichlet Allocation (LDA), Paragraph-Vector Distributed Bag-of-Words (PV-DBOW), and Paragraph-Vector Distributed Memory (PV-DM) models as representation methods, in conjunction with five traditional clustering algorithms, namely k-means, spherical k-means, possibilistic fuzzy c-means, agglomerative clustering and NMF, on two publicly available and one proprietary datasets. Fifteen combinations are formed which are assessed using external clustering validity measures, such as Adjusted Mutual Information (AMI) and Adjusted Rand Index (ARI) against available ground-truth. Our results indicate that using PV-DBOW leads in general to better clustering performance in all datasets.","PeriodicalId":117256,"journal":{"name":"2019 European Intelligence and Security Informatics Conference (EISIC)","volume":"12 11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124334183","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}