2015 10th Asia Joint Conference on Information Security最新文献

{"title":"Discovery of De-identification Policies Considering Re-identification Risks and Information Loss","authors":"He-Ming Ruan, Ming-Hwa Tsai, Yennun Huang, Yen-Hua Liao, C. Lei","doi":"10.1109/AsiaJCIS.2015.23","DOIUrl":"https://doi.org/10.1109/AsiaJCIS.2015.23","url":null,"abstract":"In data analysis, it is always a tough task to strike the balance between the privacy and the applicability of the data. Due to the demand for individual privacy, the data are being more or less obscured before being released or outsourced to avoid possible privacy leakage. This process is so called de-identification. To discuss a de-identification policy, the most important two aspects should be the re-identification risk and the information loss. In this paper, we introduce a novel policy searching method to efficiently find out proper de-identification policies according to acceptable re-identification risk while retaining the information resided in the data. With the UCI Machine Learning Repository as our real world dataset, the re-identification risk can therefore be able to reflect the true risk of the de-identified data under the de-identification policies. Moreover, using the proposed algorithm, one can then efficiently acquire policies with higher information entropy.","PeriodicalId":432783,"journal":{"name":"2015 10th Asia Joint Conference on Information Security","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132756845","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":"Privacy Preserved Rule-Based Risk Analysis through Secure Multi-party Computation","authors":"Yu Liu, Nasato Goto, Akira Kanaoka, E. Okamoto","doi":"10.1109/AsiaJCIS.2015.32","DOIUrl":"https://doi.org/10.1109/AsiaJCIS.2015.32","url":null,"abstract":"Network systems are becoming the core components of technical information infrastructures. The protection of network systems from malicious attacks is an urgent priority in our society. However, considering that all security threats are very complicated, easily missed, and error-prone, dealing with network vulnerabilities has brought about enormous challenges to network management. Therefore, one reasonable solution for a risk analysis is delegating an analysis of a network system to third parties that have more professional knowledge regarding a risk analysis. Highly confidential data such as the network configuration and vulnerabilities, as well as each hosts, are needed when delegating a risk analysis to a third party. Such confidential data may cause information leakage if no protection is provided. In this paper, we proposed a risk analysis system based on a rule-based risk analysis method. The prototype system was developed using Fairplay MP, a secure multi-party computation system, and was evaluated for a small network environment.","PeriodicalId":432783,"journal":{"name":"2015 10th Asia Joint Conference on Information Security","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128915817","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":"Malware Function Classification Using APIs in Initial Behavior","authors":"Naoto Kawaguchi, Kazumasa Omote","doi":"10.1109/AsiaJCIS.2015.15","DOIUrl":"https://doi.org/10.1109/AsiaJCIS.2015.15","url":null,"abstract":"Malware proliferation has become a serious threat to the Internet in recent years. Most of the current malware are subspecies of existing malware that have been automatically generated by illegal tools. To conduct an efficient analysis of malware, estimating their functions in advance is effective when we give priority to analyze. However, estimating malware functions has been difficult due to the increasing sophistication of malware. Although various approaches for malware detection and classification have been considered, the classification accuracy is still low. In this paper, we propose a new classification method which estimates malware's functions from APIs observed by dynamic analysis on a host. We examining whether the proposed method can correctly classify unknown malware based on function by machine learning. The results show that the our new method can classify each malware's function with an average accuracy of 83.4%.","PeriodicalId":432783,"journal":{"name":"2015 10th Asia Joint Conference on Information Security","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116514743","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":"Intelligent Display Auto-Lock Scheme for Mobile Devices","authors":"N. Lo, Chi-Kai Yu, C. Y. Hsu","doi":"10.1109/AsiaJCIS.2015.30","DOIUrl":"https://doi.org/10.1109/AsiaJCIS.2015.30","url":null,"abstract":"In recent years people in modern societies have heavily relied on their own intelligent mobile devices such as smartphones and tablets to get personal services and improve work efficiency. In consequence, quick and simple authentication mechanisms along with energy saving consideration are generally adopted by these smart handheld devices such as screen auto-lock schemes. When a smart device activates its screen lock mode to protect user privacy and data security on this device, its screen auto-lock scheme will be executed at the same time. Device user can setup the length of time period to control when to activate the screen lock mode of a smart device. However, it causes inconvenience for device users when a short time period is set for invoking screen auto-lock. How to get balance between security and convenience for individual users to use their own smart devices has become an interesting issue. In this paper, an intelligent display (screen) auto-lock scheme is proposed for mobile users. It can dynamically adjust the unlock time period setting of an auto-lock scheme based on derived knowledge from past user behaviors.","PeriodicalId":432783,"journal":{"name":"2015 10th Asia Joint Conference on Information Security","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134357986","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":"Attribute-Based Proxy Re-encryption with Dynamic Membership","authors":"Chun-I Fan, Chien-Nan Wu, Chun-Hung Chen, Yi-Fan Tseng, Cheng-Chun Feng","doi":"10.1109/AsiaJCIS.2015.21","DOIUrl":"https://doi.org/10.1109/AsiaJCIS.2015.21","url":null,"abstract":"Cloud computing has been developed rapidly in recent years, and offers novel concepts and innovations in computer use. The applications of cloud computing are that people can put their data on cloud and also can designate a proxy to help them to execute a number of tasks in certain situations. The proxy re-encryption which is a cryptographic primitive has been proposed to solve this problem. In the proxy re-encryption system, when a user (e.g., Alice) wants to send a cipher text that is encrypted by her public key and stored in the cloud to another user (e.g., Bob), she can designate a proxy to transform the cipher text into a different cipher text that can be decrypted by Bob's private key. Recently, Fan et al. Proposed an attribute-based encryption scheme with dynamic membership. However, we found that their scheme may be flawed. In this paper we will modify Fan et al.'s scheme to fix the flaw. Based on our modified scheme and the proxy re-encryption, we also propose an attribute-based proxy re-encryption under bilinear pairing. Furthermore, the proposed scheme has rich access policies and dynamic membership.","PeriodicalId":432783,"journal":{"name":"2015 10th Asia Joint Conference on Information Security","volume":"149 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121774117","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":"Preliminary Design of a Novel Lightweight Authenticated Encryption Scheme Based on the Sponge Function","authors":"Hakju Kim, Kwangjo Kim","doi":"10.1109/AsiaJCIS.2015.24","DOIUrl":"https://doi.org/10.1109/AsiaJCIS.2015.24","url":null,"abstract":"The authenticated encryption plays a key cryptographic primitive that provides confidentiality, integrity, and authenticity in an efficient manner. This paper presents a preliminary design of a novel lightweight authenticated encryption scheme based on the duplex construction of the sponge function supporting the most required features of the authenticated encryption schemes.","PeriodicalId":432783,"journal":{"name":"2015 10th Asia Joint Conference on Information Security","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128013084","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 Approach to Predict Drive-by-Download Attacks by Vulnerability Evaluation and Opcode","authors":"Takashi Adachi, Kazumasa Omote","doi":"10.1109/AsiaJCIS.2015.17","DOIUrl":"https://doi.org/10.1109/AsiaJCIS.2015.17","url":null,"abstract":"Drive-by-download attacks exploit vulnerabilities in Web browsers, and users are unnoticeably downloading malware which accesses to the compromised Web sites. A number of detection approaches and tools against such attacks have been proposed so far. Especially, it is becoming easy to specify vulnerabilities of attacks, because researchers well analyze the trend of various attacks. Unfortunately, in the previous schemes, vulnerability information has not been used in the detection/prediction approaches of drive-by-download attacks. In this paper, we propose a prediction approach of \"malware downloading\" during drive-by-download attacks (approach-I), which uses vulnerability information. Our experimental results show our approach-I achieves the prediction rate (accuracy) of 92%, FNR of 15% and FPR of 1.0% using Naive Bayes. Furthermore, we propose an enhanced approach (approach-II) which embeds Opcode analysis (dynamic analysis) into our approach-I (static approach). We implement our approach-I and II, and compare the three approaches (approach-I, II and Opcode approaches) using the same datasets in our experiment. As a result, our approach-II has the prediction rate of 92%, and improves FNR to 11% using Random Forest, compared with our approach-I.","PeriodicalId":432783,"journal":{"name":"2015 10th Asia Joint Conference on Information Security","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117163536","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":"Privacy-Preserving Epidemiological Analysis for a Distributed Database of Hospitals","authors":"Hiroaki Kikuchi, H. Hashimoto, H. Yasunaga","doi":"10.1109/AsiaJCIS.2015.31","DOIUrl":"https://doi.org/10.1109/AsiaJCIS.2015.31","url":null,"abstract":"The Diagnosis Procedure Combination (DPC) database is a large-scale claim-based database of Japanese hospitals that uses a standardized case-mix patient-classification system for the evaluation of clinical procedures and hospital performance. The dataset does not include confidential information, although content details may allow identification of individual patients. We have developed a secure scheme for preserving patient privacy, which also enables epidemiological analysis that can adjust for patient characteristics to enable unbiased comparisons. We tested its performance with a DPC database sample of 80 hospitals.","PeriodicalId":432783,"journal":{"name":"2015 10th Asia Joint Conference on Information Security","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131809763","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":"On the Traceability of the Accountable Anonymous Channel","authors":"Tomoaki Kosugi, Tomoki Hayafuji, M. Mambo","doi":"10.1109/AsiaJCIS.2015.29","DOIUrl":"https://doi.org/10.1109/AsiaJCIS.2015.29","url":null,"abstract":"Anonymous channels guaranteeing anonymity of senders such as Tor are effective for whistle-blowing and other privacy sensitive scenarios. However, there is a risk of being abused for illegal activities. As a countermeasure to illegal activities using an anonymous channel, it is natural to construct an accountable anonymous channel which can revoke anonymity of senders when an unlawful message was sent out from them. In this paper, we point out that an accountable anonymous channel THEMIS does not provide anonymity in a perfect way and there is a possibility that attackers can identify senders even if messages are not malicious. Feasibility of tracing senders is analyzed by using simulation. Moreover, we give a simple remedy of the flaw in THEMIS.","PeriodicalId":432783,"journal":{"name":"2015 10th Asia Joint Conference on Information Security","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132145113","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":"iF2: An Interpretable Fuzzy Rule Filter for Web Log Post-Compromised Malicious Activity Monitoring","authors":"Chih-Hung Hsieh, Yu-Siang Shen, Chao-Wen Li, Jain-Shing Wu","doi":"10.1109/AsiaJCIS.2015.19","DOIUrl":"https://doi.org/10.1109/AsiaJCIS.2015.19","url":null,"abstract":"To alleviate the loads of tracking web log file by human effort, machine learning methods are now commonly used to analyze log data and to identify the pattern of malicious activities. Traditional kernel based techniques, like the neural network and the support vector machine (SVM), typically can deliver higher prediction accuracy. However, the user of a kernel based techniques normally cannot get an overall picture about the distribution of the data set. On the other hand, logic based techniques, such as the decision tree and the rule-based algorithm, feature the advantage of presenting a good summary about the distinctive characteristics of different classes of data such that they are more suitable to generate interpretable feedbacks to domain experts. In this study, a real web-access log dataset from a certain organization was collected. An efficient interpretable fuzzy rule filter (iF2) was proposed as a filter to analyze the data and to detect suspicious internet addresses from the normal ones. The historical information of each internet address recorded in web log file is summarized as multiple statistics. And the design process of iF2 is elaborately modeled as a parameter optimization problem which simultaneously considers 1) maximizing prediction accuracy, 2) minimizing number of used rules, and 3) minimizing number of selected statistics. Experimental results show that the fuzzy rule filter constructed with the proposed approach is capable of delivering superior prediction accuracy in comparison with the conventional logic based classifiers and the expectation maximization based kernel algorithm. On the other hand, though it cannot match the prediction accuracy delivered by the SVM, however, when facing real web log file where the ratio of positive and negative cases is extremely unbalanced, the proposed iF2 of having optimization flexibility results in a better recall rate and enjoys one major advantage due to providing the user with an overall picture of the underlying distributions.","PeriodicalId":432783,"journal":{"name":"2015 10th Asia Joint Conference on Information Security","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132345341","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}