{"title":"Study on Mental Disorder Detection via Social Media Mining","authors":"I. Syarif, Nadia Ningtias, T. Badriyah","doi":"10.1109/CCCS.2019.8888096","DOIUrl":"https://doi.org/10.1109/CCCS.2019.8888096","url":null,"abstract":"Traditional mental health studies rely on information collected through personal contact with professional healthcare specialists. Recent work shows the utility of social media data for studying mental disorder. It is supported by the massive usage of social media and the disclosure that social media is a pool of emotion. Study on social media data could potentially complement the traditional technique in its ability to provide natural measurements.We build a corpus of self-declared mental illness diagnosis on Twitter using a source of publicly-available data. This study implements computational linguistic process with linguistic and emotion feature to model the rate of depression in social media data. We propose the features of SenticNet’s four dimensions emotional state of the mind, self-reference, and mental disorder wordcount. The results are shown using a rule-based system to determine the level of depression based on language. We found 1,733 typical words from the depression diagnosed group. This finding is based on the match of Wordnet, SenticNet, Vader, TextBlob, and has been evaluated by synonyms checking. Our proposed method has been successfully identified and then categorized 8105 tweets into 3 levels of depression, 1028 tweets are categorized as high, 1073 moderate, and 1605 low.","PeriodicalId":152148,"journal":{"name":"2019 4th International Conference on Computing, Communications and Security (ICCCS)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121832351","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":"SDN-RBAC: An Access Control Model for SDN Controller Applications","authors":"Abdullah Al-Alaj, R. Krishnan, R. Sandhu","doi":"10.1109/CCCS.2019.8888031","DOIUrl":"https://doi.org/10.1109/CCCS.2019.8888031","url":null,"abstract":"The architecture of Software-defined Networks provides the flexibility in developing innovative networking applications for managing and analyzing the network from a centralized controller. Since these applications directly and dynamically access critical network resources, any privilege abuse from controller applications could lead to various attacks impacting the entire network domain. As a result, the security concern is ranked one of the top issues that prevent enterprise and data center networks from adopting SDN. Since access control is a natural solution to the over-privilege problem and to address this critical security issue, we propose and implement a formal role-based access control model (SDN-RBAC) for SDN applications that helps in applying least of privilege principle at the level of applications and their sessions. We also identify different approaches in which the system can handle application sessions in order to reduce exposure to the network attack surface in case of application being compromised, buggy, or malicious. Through proof-of-concept prototype, we implemented our model with multi-session support in Floodlight controller and used hooking techniques to enforce the security policy without any change to the code of the Floodlight framework. The implementation verifies the model’s usability and effectiveness against unauthorized access requests by controller applications and shows how the framework can identify application sessions and reject unauthorized operations in real time.","PeriodicalId":152148,"journal":{"name":"2019 4th International Conference on Computing, Communications and Security (ICCCS)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115331739","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":"ICCCS 2019 Copyright Page","authors":"","doi":"10.1109/cccs.2019.8888118","DOIUrl":"https://doi.org/10.1109/cccs.2019.8888118","url":null,"abstract":"","PeriodicalId":152148,"journal":{"name":"2019 4th International Conference on Computing, Communications and Security (ICCCS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129834461","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":"Analyzing CNN Model Performance Sensitivity to the Ordering of Non-Natural Data","authors":"Randy Klepetko, R. Krishnan","doi":"10.1109/CCCS.2019.8888041","DOIUrl":"https://doi.org/10.1109/CCCS.2019.8888041","url":null,"abstract":"Convolutional Neural Networks (CNN) have had significant success in identifying and classifying image datasets. CNNs have also been used effectively in classifying non-visual datasets such as malware and gene expression. In all of these applications, CNNs require data to be organized in a certain order. In the case of images, this order is naturally presented. However, in the case of non-visual data, this order is sometimes not naturally defined and hence requires an artificially defined order. The sensitivity of a CNN model’s performance to various artificial orders of non-natural datasets is not well-understood. In this paper, we investigate this problem by experimenting with various orders of a dataset derived from malware behavior in a cloud auto-scaling environment. We show that the ordering can have a major impact on the performance of the CNN and offer some insights on how to derive one or more orderings that could provide better performance.","PeriodicalId":152148,"journal":{"name":"2019 4th International Conference on Computing, Communications and Security (ICCCS)","volume":"120 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115822337","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":"An architecture to manage security services for cloud applications","authors":"M. Repetto, A. Carrega, G. Lamanna","doi":"10.1109/CCCS.2019.8888061","DOIUrl":"https://doi.org/10.1109/CCCS.2019.8888061","url":null,"abstract":"The uptake of virtualization and cloud technologies has pushed novel development and operation models for the software, bringing more agility and automation. Unfortunately, cyber-security paradigms have not evolved at the same pace and are not yet able to effectively tackle the progressive disappearing of a sharp security perimeter. In this paper, we describe a novel cyber-security architecture for cloud-based distributed applications and network services. We propose a security orchestrator that controls pervasive, lightweight, and programmable security hooks embedded in the virtual functions that compose the cloud application, pursuing better visibility and more automation in this domain. Our approach improves existing management practice for service orchestration, by decoupling the management of the business logic from that of security. We also describe the current implementation stage for a programmable monitoring, inspection, and enforcement framework, which represents the ground technology for the realization of the whole architecture.","PeriodicalId":152148,"journal":{"name":"2019 4th International Conference on Computing, Communications and Security (ICCCS)","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122288653","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":"Interoperability of home automation systems as a critical challenge for IoT","authors":"V. Miori, Dario Russo, L. Ferrucci","doi":"10.1109/CCCS.2019.8888125","DOIUrl":"https://doi.org/10.1109/CCCS.2019.8888125","url":null,"abstract":"The spread of enabling technologies for the Internet of Things allows the creation of new scenarios in which home automation plays a significant role. Platforms for smart cities and communities, which must include applications for energy efficiency, health, mobility, security, etc., cannot ignore the use of data gathered directly from homes. In order to implement such scenarios, all the related technological infrastructure and home systems must be able to understand each other and exchange information. In this work, we present a new platform that achieves interoperability between heterogeneous home automation systems. It allows different, incompatible technologies to cooperate inside and outside the home, thus creating a single ecosystem. In order to achieve tins goal, specific problems need to be solved to be able to construct “bridges” between the various home automation networks currently in use. In this regard, some specific solutions adopted for integrating two different technologies (KNX and MyHome) within a home automation platform are illustrated.","PeriodicalId":152148,"journal":{"name":"2019 4th International Conference on Computing, Communications and Security (ICCCS)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125222578","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}
Samer Y. Khamaiseh, Edoardo Serra, Zhiyuan Li, Dianxiang Xu
{"title":"Detecting Saturation Attacks in SDN via Machine Learning","authors":"Samer Y. Khamaiseh, Edoardo Serra, Zhiyuan Li, Dianxiang Xu","doi":"10.1109/CCCS.2019.8888049","DOIUrl":"https://doi.org/10.1109/CCCS.2019.8888049","url":null,"abstract":"Software Defined Networking (SDN) is a new network paradigm that facilitates network management by separating the control plane from the data plane. Studies have shown that an SDN may experience a high packet loss rate and a long delay in forwarding messages when the OpenFlow channel is overwhelmed by a saturation attack. The existing approaches have focused on the detection of saturation attacks caused by TCP-SYN flooding through periodic analysis of network traffic. However, there are two issues. First, previous approaches are incapable of detecting other types, especially unknown types, of saturation attacks. Second, they rely on predetermined time-window of network traffic and thus are unable to determine what time window of traffic data would be appropriate for effective attack detection. To tackle these problems, this paper first investigates the impact of different time-windows of OpenFlow traffic on the detection performance of three classification algorithms: the Support Vector Machine (SVM), the Naïve Bayes (NB) classifier, and the K-Nearest Neighbors (K-NN) classifier. We have built and analyzed a total of 150 models on OpenFlow traffic datasets generated from both physical and simulated SDN environments. The experiment results show that the chosen time-interval of OpenFlow traffic heavily influences the detection performance – larger time-windows may result in decreased detection performance. In addition, we were able to achieve reasonable accuracy on detection of unknown attacks by applying proper time-windows of OpenFlow traffic.","PeriodicalId":152148,"journal":{"name":"2019 4th International Conference on Computing, Communications and Security (ICCCS)","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117168813","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. Martalò, G. Ferrari, S. Perri, Gianmichele Verdano, F. D. Mola, Francesco Monica
{"title":"UWB TDoA-based Positioning Using a Single Hotspot with Multiple Anchors","authors":"M. Martalò, G. Ferrari, S. Perri, Gianmichele Verdano, F. D. Mola, Francesco Monica","doi":"10.1109/CCCS.2019.8888099","DOIUrl":"https://doi.org/10.1109/CCCS.2019.8888099","url":null,"abstract":"In this paper, we address target positioning in scenarios where the reference nodes, denoted as anchors, are not distributed at the perimeter of the area where the target is, but are concentrated in a very small region and target is outside this region. This scenario may be meaningful in smart building applications, where anchor nodes cannot be distributed and cabled in the monitored area. On the other hand, anchors may be installed on a single hotspot to be placed at the center of the environment of interest. In this case, the target has to be localized outside the polytope identified by the anchors. To this end, we investigate Ultra WideBand (UWB)-based target positioning with Time Difference of Arrival (TDoA) processing at the anchors. A comparative analysis between geometric and Particle Swarm Optimization (PSO) algorithms is carried out. Our results show accurate angle of arrival estimation accuracy. Moreover, while PSO guarantees a better performance, in terms of average position estimation error, the “dispersion” of position estimation (i.e., the standard deviation of the position error) is higher than in the case of geometric algorithms.","PeriodicalId":152148,"journal":{"name":"2019 4th International Conference on Computing, Communications and Security (ICCCS)","volume":"131 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117190947","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. Bolkhovskaya, A. Maltsev, V. Sergeev, W. Keusgen, M. Peter
{"title":"Accurate Iterative Algorithm for Detection and the Signal AoA Estimation in Low SNR Region","authors":"O. Bolkhovskaya, A. Maltsev, V. Sergeev, W. Keusgen, M. Peter","doi":"10.1109/CCCS.2019.8888112","DOIUrl":"https://doi.org/10.1109/CCCS.2019.8888112","url":null,"abstract":"The GLRT (Generalized Likelihood Ratio Test) method is applied for joint detection and the angle-of-arrive (AoA) estimation of an unknown signal in multi-element antenna arrays. The direct method of the maximum likelihood (ML) estimation of the power and the AoA of a signal with a plane wavefront and unknown temporal structure is considered. An efficient iterative procedure is proposed for implementation of this approach. For the useful signal detection the Neumann-Pearson criterion is applied at the final iteration step and the threshold value for the decision statistics is calculated by simulations. The performance characteristics of the proposed joint detection-estimation iterative algorithm are compared with three-step algorithm, which based on the sample correlation matrix eigenvectors and eigenvalues analysis. It was found that in high SNR region the accuracies of the proposed iterative algorithm and the three-step algorithm practically reach the low CRBs, but in low SNR region and the short sample sizes the iterative algorithm at 35% - 50% over performs the accuracy of the three-step algorithm.","PeriodicalId":152148,"journal":{"name":"2019 4th International Conference on Computing, Communications and Security (ICCCS)","volume":"72 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125375072","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}
A. Raschellà, M. Mackay, F. Bouhafs, Bjørn Ivar Teigen
{"title":"Evaluation of Channel Assignment Algorithms in a Dense Real World WLAN","authors":"A. Raschellà, M. Mackay, F. Bouhafs, Bjørn Ivar Teigen","doi":"10.1109/CCCS.2019.8888082","DOIUrl":"https://doi.org/10.1109/CCCS.2019.8888082","url":null,"abstract":"This paper addresses the problem of Access Point (AP) channel assignment in dense IEEE 802.11 Wireless Local Area Networks (WLANs) implemented in a real world scenario, based on a housing complex located in Oslo, Norway. Currently, the APs composing this housing complex are centrally configured through a channel selection approach based on a genetic algorithm that aims to minimize the cumulative interference experienced by each AP. In this work, we present the performance of an alternative channel assignment algorithm in comparison to the existing genetic one. More specifically, the algorithm investigated in this work aims to minimize a network-wide parameter called interference impact, which represents the interference caused by an AP to all the other APs in the neighbourhood. Moreover, the algorithm is implemented using the spectrum programming architecture Wi-5 based on Software-Defined Networking (SDN). Although the benefits of this algorithm have been demonstrated in simulated environments, this work presents its first evaluation in a dense real world scenario. The performance analysis illustrates the important gains obtained in terms of the data transmissions quality through the proposed algorithm compared against the AP channel selection approach currently implemented in the considered scenario.","PeriodicalId":152148,"journal":{"name":"2019 4th International Conference on Computing, Communications and Security (ICCCS)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115457923","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}