2019 7th International Symposium on Digital Forensics and Security (ISDFS)最新文献_第5页

A New Approach for Exiting from Parking Lot based on Artificial Neural Network 基于人工神经网络的停车场出站新方法

2019 7th International Symposium on Digital Forensics and Security (ISDFS) Pub Date : 2019-06-01 DOI: 10.1109/ISDFS.2019.8757529

H. Ozturk, Sevginur Teke, M. Karabatak

引用次数: 0

Thwarting C2 Communication of DGA-Based Malware using Process-level DNS Traffic Tracking 利用进程级DNS流量跟踪阻止基于dga的恶意软件的C2通信

2019 7th International Symposium on Digital Forensics and Security (ISDFS) Pub Date : 2019-06-01 DOI: 10.1109/ISDFS.2019.8757555

Anjali Menon

{"title":"Thwarting C2 Communication of DGA-Based Malware using Process-level DNS Traffic Tracking","authors":"Anjali Menon","doi":"10.1109/ISDFS.2019.8757555","DOIUrl":"https://doi.org/10.1109/ISDFS.2019.8757555","url":null,"abstract":"Many modern botnet malwares use Domain Generation Algorithms (DGAs) to dynamically generate the domain names that resolve to their command and control (C2) centers. This approach allows these malwares to subvert traditional detection systems which rely on blacklists of known domains associated with malicious activities to block malware communications. Since the advent of DGA-based malwares, the efforts to prevent the said malwares from contacting their command and control centers (C2) server have been centered around detecting Algorithmically Generated Domain Names through lexicographic analysis, isolating entire infected devices or both. Recent research has emerged, which more accurately identifies infected devices in a network, by monitoring the volumes of domain resolution failures. While effective, these techniques are slow to identify DGA generated domain names. Even after the delayed identification, the only preliminary mitigation known today is a complete shutdown of a device that is suspected to be infected. In this paper, we present a new method to counter DGA-based malwares by limiting the impact of mitigation. Instead of isolating the entire infected device from the network we limit network activity of the malicious process alone. Our objective is to prevent DGA-based malwares from communicating with their C2 centers while allowing an infected device to maintain its normal functionality. We achieve this by tracking Domain Name Service (DNS) responses of individual processes and blacklisting those processes for which DNS traffic have abnormally large numbers of domain resolution failures. The blacklisting at a process level ensures that non-malicious processes in the infected device can continue functioning.","PeriodicalId":247412,"journal":{"name":"2019 7th International Symposium on Digital Forensics and Security (ISDFS)","volume":"225 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126123836","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}

引用次数: 1

Multidimensional signal interpolation based on parametric space dimension reduction 基于参数空间降维的多维信号插值

2019 7th International Symposium on Digital Forensics and Security (ISDFS) Pub Date : 2019-06-01 DOI: 10.1109/ISDFS.2019.8757491

M. Gashnikov

引用次数: 1

Predicting Daily Activities Effectiveness Using Base-level and Meta level Classifiers 使用基础级和元级分类器预测日常活动的有效性

2019 7th International Symposium on Digital Forensics and Security (ISDFS) Pub Date : 2019-06-01 DOI: 10.1109/ISDFS.2019.8757487

Mohammed Akour, Shadi Banitaan, Hiba Alsghaier, Khalid Al Radaideh

{"title":"Predicting Daily Activities Effectiveness Using Base-level and Meta level Classifiers","authors":"Mohammed Akour, Shadi Banitaan, Hiba Alsghaier, Khalid Al Radaideh","doi":"10.1109/ISDFS.2019.8757487","DOIUrl":"https://doi.org/10.1109/ISDFS.2019.8757487","url":null,"abstract":"Collecting and analyzing Activities of Daily Living (ADL) could supplement elder care and long-term care services with very sensitive information about elder people and what they do during the day and what challenges they face. Providing care for elder people based on their ADL could let them live actively, independently and healthy. In this paper, we studied the effectiveness of base learners against ensemble methods for predicting ADL. The selected base learners are Naïve Bayes, Bayesian Network, Sequential Minimal Optimization, Decision Table and J48 while the selected ensemble learners are boosting, bagging, decorate and random forest. The dataset was gathered from a wearable accelerometer attached on the chest. The data used in this study is collected from fifteen participants conducting seven activities namely standing up, working at the computer, going up downstairs, standing, walking, walking and talking with someone and talking while standing, walking and going up downstairs. For base learners, J48 achieved the best results in terms of F-measure, precision and recall. Results also showed that Boosting using decision table as the base classifier achieved the best improvement over base classifier. In addition, Bagging was the only ensemble approach that improved the results using all classifiers as base learners. Moreover, Bagging was able to predict five activities out of seven more efficiently than the other approaches while the rotation forest approach was able to predict the remaining two activities more efficiently than the rest. The results also indicated that all approaches took a reasonable time to build the model except Decorate.","PeriodicalId":247412,"journal":{"name":"2019 7th International Symposium on Digital Forensics and Security (ISDFS)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130770885","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}

引用次数: 4

[Copyright notice] (版权)

2019 7th International Symposium on Digital Forensics and Security (ISDFS) Pub Date : 2019-06-01 DOI: 10.1109/isdfs.2019.8757518

引用次数: 0

Face Verification and Recognition for Digital Forensics and Information Security 数字取证和信息安全中的人脸验证和识别

2019 7th International Symposium on Digital Forensics and Security (ISDFS) Pub Date : 2019-06-01 DOI: 10.1109/ISDFS.2019.8757511

Giuseppe Amato, F. Falchi, C. Gennaro, F. V. Massoli, N. Passalis, A. Tefas, Alessandro Trivilini, C. Vairo

引用次数: 19

SmartThings Event Export using SmartApps 使用SmartApps导出SmartThings事件

2019 7th International Symposium on Digital Forensics and Security (ISDFS) Pub Date : 2019-06-01 DOI: 10.1109/ISDFS.2019.8757519

Jose Garcia, C. Varol

引用次数: 2

Augmenting Gabor-based Face Recognition with Global Soft Biometrics 基于gabor的全局软生物识别增强人脸识别

2019 7th International Symposium on Digital Forensics and Security (ISDFS) Pub Date : 2019-06-01 DOI: 10.1109/ISDFS.2019.8757553

E. S. Jaha

{"title":"Augmenting Gabor-based Face Recognition with Global Soft Biometrics","authors":"E. S. Jaha","doi":"10.1109/ISDFS.2019.8757553","DOIUrl":"https://doi.org/10.1109/ISDFS.2019.8757553","url":null,"abstract":"Though face recognition using traditional (hard) biometrics has attracted massive research interest and received extensive studies, it still confronts degrading variability challenges and notably achieves lower performance compared with other biometric recognition forms like fingerprint and iris. Recently, a number of research studies have been interested in enhancing face recognition performance by all means of supplementary facial biometric traits or other biometric modalities. Thus, soft biometrics have been emerged as a new promising modality of biometrics and highlighted as likely viable and fusible traits for augmenting traditional/hard biometrics. This is due to the expected advantages of soft biometrics over the traditional biometric traits, such as the high collectability and invariance properties. Other than fusing different kinds of traditional traits to augment face recognition, adding soft biometrics to augment various traditional facial traits has yet gained little research attention. Hence, in this research, unlike the majority of existing work, we investigate the viability of global soft face biometrics in supplementing traditional (hard) biometrics and the efficacy of concurrently using absolute and relative descriptions as soft biometrics. We conduct a new soft biometric-based fusion scheme in feature-level for augmenting a traditional Gabor-based face identification/verification in different potential forensic scenarios, considering performance variability evaluation and comparison with the baseline performance of Gabor features in isolation.","PeriodicalId":247412,"journal":{"name":"2019 7th International Symposium on Digital Forensics and Security (ISDFS)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127301738","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}

引用次数: 7

Defending Against Cyber-Attacks on the Internet of Things 防范物联网网络攻击

2019 7th International Symposium on Digital Forensics and Security (ISDFS) Pub Date : 2019-06-01 DOI: 10.1109/ISDFS.2019.8757478

Ghazi Abdalla Abdalrahman, H. Varol

引用次数: 8

Scientific Committee Members 科学委员会成员

2019 7th International Symposium on Digital Forensics and Security (ISDFS) Pub Date : 2019-06-01 DOI: 10.1109/isdfs.2019.8757548

L. Ambrosio

引用次数: 0