Although reflection methods in Android can facilitate developing applications, they will block control flow and data flow in static analysis, making its precision decreased. To solve this problem, we trigger applications to execute reflection methods and record its reflection targets at runtime. Reflection targets may be a method invocation, field setting or instantiating of some classes. Considering many static analysis' input is apk file, we further transform reflection methods in apk into explicit method invocation, field setting and class initiating according to the recorded reflection targets. Our experiment result shows that, based on our method, some static analysis can perform better on these transformed apk and produce more precise results.
{"title":"Resolving reflection methods in Android applications","authors":"Zhichao Cheng, Fanping Zeng, Xingqiu Zhong, Mingsong Zhou, Chengcheng Lv, Shuli Guo","doi":"10.1109/ISI.2017.8004892","DOIUrl":"https://doi.org/10.1109/ISI.2017.8004892","url":null,"abstract":"Although reflection methods in Android can facilitate developing applications, they will block control flow and data flow in static analysis, making its precision decreased. To solve this problem, we trigger applications to execute reflection methods and record its reflection targets at runtime. Reflection targets may be a method invocation, field setting or instantiating of some classes. Considering many static analysis' input is apk file, we further transform reflection methods in apk into explicit method invocation, field setting and class initiating according to the recorded reflection targets. Our experiment result shows that, based on our method, some static analysis can perform better on these transformed apk and produce more precise results.","PeriodicalId":423696,"journal":{"name":"2017 IEEE International Conference on Intelligence and Security Informatics (ISI)","volume":"310 4","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121011426","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}
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 to as Account Linkage (AL). However, existing AL techniques suffer from the problem of information unreliability. Recent advances in location acquisition and wireless communication technologies give rise to new opportunities for AL. In this paper, we propose a framework that links up multiple accounts belonging to the same individual by comparing habit patterns extracted from user-generated location data. We built a topic model to capture users habit patterns in both spatial and temporal dimensions. Results of experiments carried out on a real-world dataset demonstrate the feasibility and validity of the proposed framework.
{"title":"Linking social network accounts by modeling user spatiotemporal habits","authors":"Xiaohui Han, Lianhai Wang, Shujiang Xu, Guangqi Liu, Dawei Zhao","doi":"10.1109/ISI.2017.8004868","DOIUrl":"https://doi.org/10.1109/ISI.2017.8004868","url":null,"abstract":"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 to as Account Linkage (AL). However, existing AL techniques suffer from the problem of information unreliability. Recent advances in location acquisition and wireless communication technologies give rise to new opportunities for AL. In this paper, we propose a framework that links up multiple accounts belonging to the same individual by comparing habit patterns extracted from user-generated location data. We built a topic model to capture users habit patterns in both spatial and temporal dimensions. Results of experiments carried out on a real-world dataset demonstrate the feasibility and validity of the proposed framework.","PeriodicalId":423696,"journal":{"name":"2017 IEEE International Conference on Intelligence and Security Informatics (ISI)","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126351814","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}
Pub Date : 2017-07-01DOI: 10.1109/ISI.2017.8004912
Chai Linpeng, Zhang Bin
The one-off public key scheme gets more and more attention for its security features. However, there are two problems in the current schemes proposed, one is that the security threat of user's privacy disclosure for plaintext transmission, the other one is that attackers can infer the identities of the communication participants via signature correctness verification. For the problem mentioned above, we propose an identity-based one-off public key scheme for privacy preservation based on signcrytion algorithm. the scheme ensures that the confidentiality of the message, and only the specified verifier can verified the signature correctness. Furthermore, The scheme has lower computation and communication overhead compared with current available schemes.
{"title":"An identity-based one-off public key scheme for privacy preservation","authors":"Chai Linpeng, Zhang Bin","doi":"10.1109/ISI.2017.8004912","DOIUrl":"https://doi.org/10.1109/ISI.2017.8004912","url":null,"abstract":"The one-off public key scheme gets more and more attention for its security features. However, there are two problems in the current schemes proposed, one is that the security threat of user's privacy disclosure for plaintext transmission, the other one is that attackers can infer the identities of the communication participants via signature correctness verification. For the problem mentioned above, we propose an identity-based one-off public key scheme for privacy preservation based on signcrytion algorithm. the scheme ensures that the confidentiality of the message, and only the specified verifier can verified the signature correctness. Furthermore, The scheme has lower computation and communication overhead compared with current available schemes.","PeriodicalId":423696,"journal":{"name":"2017 IEEE International Conference on Intelligence and Security Informatics (ISI)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127049545","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}
Pub Date : 2017-07-01DOI: 10.1109/ISI.2017.8004916
Pengshuai Cui, Peidong Zhu, Peng Xun, Zhuoqun Xia
In this paper, we propose two dependence link addition strategies to enhance the robustness of interdependent Cyber-Physical Systems. One is based on intra-degree and receiving capability difference and the other is based on intra-degree and receiving capability ratio. Numerical simulations demonstrate that the two strategies are better than adding dependence links randomly.
{"title":"Enhance the robustness of cyber-physical systems by adding interdependency","authors":"Pengshuai Cui, Peidong Zhu, Peng Xun, Zhuoqun Xia","doi":"10.1109/ISI.2017.8004916","DOIUrl":"https://doi.org/10.1109/ISI.2017.8004916","url":null,"abstract":"In this paper, we propose two dependence link addition strategies to enhance the robustness of interdependent Cyber-Physical Systems. One is based on intra-degree and receiving capability difference and the other is based on intra-degree and receiving capability ratio. Numerical simulations demonstrate that the two strategies are better than adding dependence links randomly.","PeriodicalId":423696,"journal":{"name":"2017 IEEE International Conference on Intelligence and Security Informatics (ISI)","volume":"101 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133612238","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}
Pub Date : 2017-07-01DOI: 10.1109/ISI.2017.8004917
C. Y. Tseung, Kam-pui Chow, X. Zhang
DDoS attack is still one of the major threats from Internet. We propose a new technique to mitigate different types of DDoS, combining and taking advantages of both machine learning algorithms and Bloom filter. We use machine learning to extract features of attacks, then use a customized Bloom filter to defend attacks based on selected features. We implemented and tested the performance of the proposed technique in a lab environment.
{"title":"Extended abstract: Anti-DDoS technique using self-learning bloom filter","authors":"C. Y. Tseung, Kam-pui Chow, X. Zhang","doi":"10.1109/ISI.2017.8004917","DOIUrl":"https://doi.org/10.1109/ISI.2017.8004917","url":null,"abstract":"DDoS attack is still one of the major threats from Internet. We propose a new technique to mitigate different types of DDoS, combining and taking advantages of both machine learning algorithms and Bloom filter. We use machine learning to extract features of attacks, then use a customized Bloom filter to defend attacks based on selected features. We implemented and tested the performance of the proposed technique in a lab environment.","PeriodicalId":423696,"journal":{"name":"2017 IEEE International Conference on Intelligence and Security Informatics (ISI)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125322609","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}
Pub Date : 2017-07-01DOI: 10.1109/ISI.2017.8004895
Nan Xu
Public sentiment is regarded as an important measure for event detection, information security, policy making etc. Analyzing public sentiments relies more and more on large amount of multimodal contents, in contrast to the traditional text-based and image-based sentiment analysis. However, most previous works directly extract feature from image as the additional information for text modality and then merge these features for multimodal sentiment analysis. More detailed semantic information in image, like image caption which contains useful semantic components for sentiment analysis, has been ignored. In this paper, we propose a Hierarchical Semantic Attentional Network based on image caption, HSAN, for multimodal sentiment analysis. It has a hierarchical structure that reflects the hierarchical structure of tweet and uses image caption to extract visual semantic feature as the additional information for text in multimodal sentiment analysis task. We also introduce the attention with context mechanism, which learns to consider the context information for encoding. The experiments on two public available datasets show the effectiveness of our model.
{"title":"Analyzing multimodal public sentiment based on hierarchical semantic attentional network","authors":"Nan Xu","doi":"10.1109/ISI.2017.8004895","DOIUrl":"https://doi.org/10.1109/ISI.2017.8004895","url":null,"abstract":"Public sentiment is regarded as an important measure for event detection, information security, policy making etc. Analyzing public sentiments relies more and more on large amount of multimodal contents, in contrast to the traditional text-based and image-based sentiment analysis. However, most previous works directly extract feature from image as the additional information for text modality and then merge these features for multimodal sentiment analysis. More detailed semantic information in image, like image caption which contains useful semantic components for sentiment analysis, has been ignored. In this paper, we propose a Hierarchical Semantic Attentional Network based on image caption, HSAN, for multimodal sentiment analysis. It has a hierarchical structure that reflects the hierarchical structure of tweet and uses image caption to extract visual semantic feature as the additional information for text in multimodal sentiment analysis task. We also introduce the attention with context mechanism, which learns to consider the context information for encoding. The experiments on two public available datasets show the effectiveness of our model.","PeriodicalId":423696,"journal":{"name":"2017 IEEE International Conference on Intelligence and Security Informatics (ISI)","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128021319","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}
Pub Date : 2017-07-01DOI: 10.1109/ISI.2017.8004893
Li Qian, Wang Xiu-cun
Because of the characteristics of the availability and practicability, mobile media technology had got a rapid development in the whole world. So, people now often use mobile devices through a mobile application (APP). Based on this, this study established a mobile application customer engagement model to carry on the investigation and research about mobile application of customers' recommendation. The results showed that mobile customer perceived support and commitment affected the continuous customer engagement, and customer commitment was the intermediary variable of customer perceived support and customer recommendation.
{"title":"The impact of different perceived support dimensions of mobile media APP users on customer commitment and customer recommendation","authors":"Li Qian, Wang Xiu-cun","doi":"10.1109/ISI.2017.8004893","DOIUrl":"https://doi.org/10.1109/ISI.2017.8004893","url":null,"abstract":"Because of the characteristics of the availability and practicability, mobile media technology had got a rapid development in the whole world. So, people now often use mobile devices through a mobile application (APP). Based on this, this study established a mobile application customer engagement model to carry on the investigation and research about mobile application of customers' recommendation. The results showed that mobile customer perceived support and commitment affected the continuous customer engagement, and customer commitment was the intermediary variable of customer perceived support and customer recommendation.","PeriodicalId":423696,"journal":{"name":"2017 IEEE International Conference on Intelligence and Security Informatics (ISI)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128978647","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}
Pub Date : 2017-07-01DOI: 10.1109/ISI.2017.8004886
Carlos Caminha, Vasco Furtado
Motivated by recent findings that human mobility influences crime behavior in big cities and that there is a superlinear relationship between the population movement and crime, this article aims to evaluate the impact of how these findings influence police allocation. More precisely, we shed light on the differences between an allocation strategy, in which the resources are distributed by clusters of floating population, and conventional allocation strategies, in which the police resources are distributed by an Administrative Area (typically based on resident population). We observed a substantial difference in the distributions of police resources allocated following these strategies, which demonstrates the imprecision of conventional police allocation methods.
{"title":"Impact of human mobility on police allocation","authors":"Carlos Caminha, Vasco Furtado","doi":"10.1109/ISI.2017.8004886","DOIUrl":"https://doi.org/10.1109/ISI.2017.8004886","url":null,"abstract":"Motivated by recent findings that human mobility influences crime behavior in big cities and that there is a superlinear relationship between the population movement and crime, this article aims to evaluate the impact of how these findings influence police allocation. More precisely, we shed light on the differences between an allocation strategy, in which the resources are distributed by clusters of floating population, and conventional allocation strategies, in which the police resources are distributed by an Administrative Area (typically based on resident population). We observed a substantial difference in the distributions of police resources allocated following these strategies, which demonstrates the imprecision of conventional police allocation methods.","PeriodicalId":423696,"journal":{"name":"2017 IEEE International Conference on Intelligence and Security Informatics (ISI)","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127943023","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}
Pub Date : 2017-07-01DOI: 10.1109/ISI.2017.8004885
Yuhao Zhang, W. Mao, D. Zeng
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 problem. Recently proposed topic evolution models are more suitable for short texts, but they need to manually specify topic number which is fixed during different time period. To address these issues, in this paper, we propose a nonparametric topic evolution model for social media short texts. We first propose the recurrent semantic dependent Chinese restaurant process (rsdCRP), which is a nonparametric process incorporating word embeddings to capture semantic similarity information. Then we combine rsdCRP with word co-occurrence modeling and build our short-text oriented topic evolution model sdTEM. We carry out experimental studies on Twitter dataset. The results demonstrate the effectiveness of our method to monitor social media topic evolution compared to the baseline methods.
{"title":"Topic evolution modeling in social media short texts based on recurrent semantic dependent CRP","authors":"Yuhao Zhang, W. Mao, D. Zeng","doi":"10.1109/ISI.2017.8004885","DOIUrl":"https://doi.org/10.1109/ISI.2017.8004885","url":null,"abstract":"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 problem. Recently proposed topic evolution models are more suitable for short texts, but they need to manually specify topic number which is fixed during different time period. To address these issues, in this paper, we propose a nonparametric topic evolution model for social media short texts. We first propose the recurrent semantic dependent Chinese restaurant process (rsdCRP), which is a nonparametric process incorporating word embeddings to capture semantic similarity information. Then we combine rsdCRP with word co-occurrence modeling and build our short-text oriented topic evolution model sdTEM. We carry out experimental studies on Twitter dataset. The results demonstrate the effectiveness of our method to monitor social media topic evolution compared to the baseline methods.","PeriodicalId":423696,"journal":{"name":"2017 IEEE International Conference on Intelligence and Security Informatics (ISI)","volume":"121 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132485150","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}
Pub Date : 2017-07-01DOI: 10.1109/ISI.2017.8004901
Aaron Zimba, Zhaoshun Wang
Device synchronization is a new technology integrated into the cloud which has seen widespread implementation from major cloud vendors but has not been spared of attacks by MITC attacks directed towards cloud synchronization achieved via a myriad of attack vectors. These target the synchronization token which lacks authenticity validation of the token bearer. We explore MITC in Linux systems by partitioning the cloud into abstract layers and employing a conceptual finite state machine for system security modeling and attack trees for analysis. We further deduce MITC attack properties and contrast them against conventional attacks and thus recommend mitigation techniques.
{"title":"On Man-In-The-Cloud (MITC) attacks: The analytical case of Linux","authors":"Aaron Zimba, Zhaoshun Wang","doi":"10.1109/ISI.2017.8004901","DOIUrl":"https://doi.org/10.1109/ISI.2017.8004901","url":null,"abstract":"Device synchronization is a new technology integrated into the cloud which has seen widespread implementation from major cloud vendors but has not been spared of attacks by MITC attacks directed towards cloud synchronization achieved via a myriad of attack vectors. These target the synchronization token which lacks authenticity validation of the token bearer. We explore MITC in Linux systems by partitioning the cloud into abstract layers and employing a conceptual finite state machine for system security modeling and attack trees for analysis. We further deduce MITC attack properties and contrast them against conventional attacks and thus recommend mitigation techniques.","PeriodicalId":423696,"journal":{"name":"2017 IEEE International Conference on Intelligence and Security Informatics (ISI)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130444284","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}
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