User Authentication for Smart Home Networks based on Mobile Apps Usage

被引:4
作者
Ashibani, Yosef [1 ]
Mahmoud, Qusay H. [1 ]
机构
[1] Ontario Tech Univ, Dept Elect Comp & Software Engn, Oshawa, ON L1G 0C5, Canada
来源
2019 28TH INTERNATIONAL CONFERENCE ON COMPUTER COMMUNICATION AND NETWORKS (ICCCN) | 2019年
关键词
continuous authentication; smart homes; multi-user authentication; classification; mobile phone app usage;
D O I
10.1109/icccn.2019.8847149
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
End-user devices, such as mobile phones and tablets, have become essential tools for accessing smart homes. Consequently, user authentication, one of the most important security factors, needs to be considered to prevent unauthorized access to home devices. Although mobile phones are equipped with different means of authentication such as fingerprint readers, these methods are only employed at the time of access; hence, countermeasures should be developed to overcome potential threats. This paper presents a continuous user authentication model based on apps access usage on mobile devices. To validate the presented model, two public real-world datasets collected from real users over a long period, are used. The model is evaluated for its ability to differentiate between users utilizing shared apps at the same daily intervals. Moreover, various classification approaches regarding legitimate user classification in compliance with the history of apps usage are evaluated. The results demonstrate the capacity of the presented method to authenticate users with high true positive and true negative rates.
引用
收藏
页数:6
相关论文
共 19 条
  • [1] To Combat Multi-Class Imbalanced Problems by Means of Over-Sampling Techniques
    Abdi, Lida
    Hashemi, Sattar
    [J]. IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, 2016, 28 (01) : 238 - 251
  • [2] Classifier Ensembles with the Extended Space Forest
    Amasyali, Mehmet Fatih
    Ersoy, Okan K.
    [J]. IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, 2014, 26 (03) : 549 - 562
  • [3] [Anonymous], 1998, ARXIVQUANTPH9808061V
  • [4] Design and Implementation of a Contextual-Based Continuous Authentication Framework for Smart Homes
    Ashibani, Yosef
    Kauling, Dylan
    Mahmoud, Qusay H.
    [J]. APPLIED SYSTEM INNOVATION, 2019, 2 (01) : 1 - 20
  • [5] Ashibani Y, 2018, 2018 IEEE 9TH ANNUAL INFORMATION TECHNOLOGY, ELECTRONICS AND MOBILE COMMUNICATION CONFERENCE (IEMCON), P632, DOI 10.1109/IEMCON.2018.8614892
  • [6] Ashibani Y, 2018, IEEE IND ELEC, P2841, DOI 10.1109/IECON.2018.8592761
  • [7] Hold & Sign: A Novel Behavioral Biometrics for Smartphone User Authentication
    Buriro, Attaullah
    Crispo, Bruno
    DelFrari, Filippo
    Wrona, Konrad
    [J]. 2016 IEEE SYMPOSIUM ON SECURITY AND PRIVACY WORKSHOPS (SPW 2016), 2016, : 276 - 285
  • [8] Improving Accuracy, Applicability and Usability of Keystroke Biometrics on Mobile Touchscreen Devices
    Buschek, Daniel
    De Luca, Alexander
    Alt, Florian
    [J]. CHI 2015: PROCEEDINGS OF THE 33RD ANNUAL CHI CONFERENCE ON HUMAN FACTORS IN COMPUTING SYSTEMS, 2015, : 1393 - 1402
  • [9] Evaluation of anomaly-based IDS for mobile devices using machine learning classifiers
    Damopoulos, Dimitrios
    Menesidou, Sofia A.
    Kambourakis, Georgios
    Papadaki, Maria
    Clarke, Nathan
    Gritzalis, Stefanos
    [J]. SECURITY AND COMMUNICATION NETWORKS, 2012, 5 (01) : 3 - 14
  • [10] Kalamandeen Andre., 2010, Proc. of MobiSys '10, P331, DOI DOI 10.1145/1814433.1814466