Smartphone Security and Privacy: A Survey on APTs, Sensor-Based Attacks, Side-Channel Attacks, Google Play Attacks, and Defenses

There is an exponential rise in the use of smartphones in government and private institutions due to business dependencies such as communication, virtual meetings, and access to global information. These smartphones are an attractive target for cybercriminals and are one of the leading causes of cyber espionage and sabotage. A large number of sophisticated malware attacks as well as advanced persistent threats (APTs) have been launched on smartphone users. These attacks are becoming significantly more complex, sophisticated, persistent, and undetected for extended periods. Traditionally, devices are targeted by exploiting a vulnerability in the operating system (OS) or device sensors. Nevertheless, there is a rise in APTs, side-channel attacks, sensor-based attacks, and attacks launched through the Google Play Store. Previous research contributions have lacked contemporary threats, and some have proven ineffective against the latest variants of the mobile operating system. In this paper, we conducted an extensive survey of papers over the last 15 years (2009–2023), covering vulnerabilities, contemporary threats, and corresponding defenses. The research highlights APTs, classifies malware variants, defines how sensors are exploited, visualizes multiple ways that side-channel attacks are launched, and provides a comprehensive list of malware families that spread through the Google Play Store. In addition, the research provides details on threat defense solutions, such as malware detection tools and techniques presented in the last decade. Finally, it highlights open issues and identifies the research gap that needs to be addressed to meet the challenges of next-generation smartphones.

[1]  W. Alhalabi,et al.  Novel Graph-Based Machine Learning Technique to Secure Smart Vehicles in Intelligent Transportation Systems , 2023, IEEE Transactions on Intelligent Transportation Systems.

[2]  B. B. Gupta,et al.  A Novel Data Poisoning Attack in Federated Learning based on Inverted Loss Function , 2023, Comput. Secur..

[3]  S. Wang,et al.  An Overview of Quantum-Safe Approaches: Quantum Key Distribution and Post-Quantum Cryptography , 2023, 2023 57th Annual Conference on Information Sciences and Systems (CISS).

[4]  Weize Yu,et al.  A machine learning low‐dropout regulator‐assisted differential power analysis attack countermeasure with voltage scaling , 2023, Int. J. Circuit Theory Appl..

[5]  Quoc-Viet Pham,et al.  Secure-Enhanced Federated Learning for AI-Empowered Electric Vehicle Energy Prediction , 2023, IEEE Consumer Electronics Magazine.

[6]  Juan Herrero,et al.  Use of smartphone apps for mobile communication and social digital pressure: A longitudinal panel study , 2023, Technological Forecasting and Social Change.

[7]  Zia-Ullah Muhammad,et al.  A cybersecurity risk assessment of electric vehicle mobile applications: findings and recommendations , 2023, 2023 3rd International Conference on Artificial Intelligence (ICAI).

[8]  Hameedur Rahman,et al.  The next generation of cloud security through hypervisor-based virtual machine introspection , 2023, 2023 3rd International Conference on Artificial Intelligence (ICAI).

[9]  A. R. Javed,et al.  Circumventing Google Play vetting policies: a stealthy cyberattack that uses incremental updates to breach privacy , 2023, Journal of Ambient Intelligence and Humanized Computing.

[10]  Zhengzi Xu,et al.  Compatible Remediation on Vulnerabilities from Third-Party Libraries for Java Projects , 2023, 2023 IEEE/ACM 45th International Conference on Software Engineering (ICSE).

[11]  Z. Anwar,et al.  Emerging Cybersecurity and Privacy Threats to Electric Vehicles and Their Impact on Human and Environmental Sustainability , 2023, Energies.

[12]  C. Rupa,et al.  Botnet Attack Intrusion Detection In IoT Enabled Automated Guided Vehicles , 2022, 2022 IEEE International Conference on Big Data (Big Data).

[13]  P. Ensign,et al.  Privatized espionage: NSO Group Technologies and its Pegasus spyware , 2022, Thunderbird International Business Review.

[14]  Teenu S. John,et al.  Intelligent Mobile Malware Detection , 2022 .

[15]  Mehran Mozaffari Kermani,et al.  CRC-Oriented Error Detection Architectures of Post-quantum Cryptography Niederreiter Key Generator on FPGA , 2022, 2022 IEEE Nordic Circuits and Systems Conference (NorCAS).

[16]  Tohfa Niraula,et al.  Quantum Computers’ threat on Current Cryptographic Measures and Possible Solutions , 2022, International Journal of Wireless and Microwave Technologies.

[17]  Nurhayati,et al.  End-To-End Encryption on the Instant Messaging Application Based Android using AES Cryptography Algorithm to a Text Message , 2022, 2022 10th International Conference on Cyber and IT Service Management (CITSM).

[18]  Syed Ibrahim Imtiaz,et al.  Efficient Approach for Anomaly Detection in Internet of Things Traffic Using Deep Learning , 2022, Wireless Communications and Mobile Computing.

[19]  Luca Piras,et al.  Android Source Code Vulnerability Detection: A Systematic Literature Review , 2022, ACM Comput. Surv..

[20]  Sen Chen,et al.  VenomAttack: automated and adaptive activity hijacking in Android , 2022, Frontiers of Computer Science.

[21]  Hari Prabhat Gupta,et al.  Real-Time Activities of Daily Living Recognition Under Long-Tailed Class Distribution , 2022, IEEE Transactions on Emerging Topics in Computational Intelligence.

[22]  T. Moulahi,et al.  Privacy‐preserving federated learning cyber‐threat detection for intelligent transport systems with blockchain‐based security , 2022, Expert Syst. J. Knowl. Eng..

[23]  C. Agrawal,et al.  CFSBFDroid: Android Malware Detection Using CFS + Best First Search-Based Feature Selection , 2022, Mobile Information Systems.

[24]  Jinglong Fang,et al.  Malicious Code Classification Method Based on Deep Residual Network and Hybrid Attention Mechanism for Edge Security , 2022, Wireless Communications and Mobile Computing.

[25]  Roheet Bhatnagar,et al.  A Comprehensive Review of Android Security: Threats, Vulnerabilities, Malware Detection, and Analysis , 2022, Security and Communication Networks.

[26]  Mehran Mozaffari Kermani,et al.  Efficient and Side-Channel Resistant Design of High-Security Ed448 on ARM Cortex-M4 , 2022, 2022 IEEE International Symposium on Hardware Oriented Security and Trust (HOST).

[27]  Mehran Mozaffari Kermani,et al.  Reliable Constructions for the Key Generator of Code-based Post-quantum Cryptosystems on FPGA , 2022, ACM J. Emerg. Technol. Comput. Syst..

[28]  M. Singh,et al.  Exploration of Mobile Device Behavior for Mitigating Advanced Persistent Threats (APT): A Systematic Literature Review and Conceptual Framework , 2022, Sensors.

[29]  E. Knightly,et al.  Metasurface-in-the-Middle Attack: From Theory to Experiment , 2022, WISEC.

[30]  I. Razzak,et al.  Federated Learning for Privacy Preservation of Healthcare Data From Smartphone-Based Side-Channel Attacks , 2022, IEEE Journal of Biomedical and Health Informatics.

[31]  J. Rubin,et al.  Rotten Apples Spoil the Bunch: An Anatomy of Google Play Malware , 2022, 2022 IEEE/ACM 44th International Conference on Software Engineering (ICSE).

[32]  J. Hidary,et al.  Transitioning organizations to post-quantum cryptography , 2022, Nature.

[33]  Shanqing Guo,et al.  Large-scale Security Measurements on the Android Firmware Ecosystem , 2022, 2022 IEEE/ACM 44th International Conference on Software Engineering (ICSE).

[34]  A. R. Javed,et al.  Cellular automata trust-based energy drainage attack detection and prevention in Wireless Sensor Networks , 2022, Comput. Commun..

[35]  Hayretdin Bahsi,et al.  Android malware concept drift using system calls: Detection, characterization and challenges , 2022, Expert Syst. Appl..

[36]  Y. Amer,et al.  SAT: Integrated Multi-agent Blackbox Security Assessment Tool using Machine Learning , 2022, 2022 2nd International Conference on Artificial Intelligence (ICAI).

[37]  N. B. Anuar,et al.  The rise of obfuscated Android malware and impacts on detection methods , 2022, PeerJ Comput. Sci..

[38]  Dong Shen,et al.  Iterative Learning Control: Practical Implementation and Automation , 2022, IEEE Transactions on Industrial Electronics.

[39]  S. Bagui,et al.  Machine Learning for Android Scareware Detection , 2022, J. Inf. Technol. Res..

[40]  Azzam Mourad,et al.  LP-SBA-XACML: Lightweight Semantics Based Scheme Enabling Intelligent Behavior-Aware Privacy for IoT , 2022, IEEE Transactions on Dependable and Secure Computing.

[41]  Moses Ashawa,et al.  Analysis of Mobile Malware: A Systematic Review of Evolution and Infection Strategies , 2021, Journal of Information Security and Cybercrimes Research.

[42]  Qi Zeng,et al.  A Systematic Overview of Android Malware Detection , 2021, Appl. Artif. Intell..

[43]  Mordechai Guri,et al.  GAIROSCOPE: Leaking Data from Air-Gapped Computers to Nearby Smartphones using Speakers-to-Gyro Communication , 2021, 2021 18th International Conference on Privacy, Security and Trust (PST).

[44]  Youssef Nasser,et al.  Attack-Specific Feature Selection for Anomaly Detection in Software-Defined Networks , 2021, 2021 3rd IEEE Middle East and North Africa COMMunications Conference (MENACOMM).

[45]  Andrea Continella,et al.  Reversing and Fuzzing the Google Titan M Chip , 2021, Reversing and Offensive-oriented Trends Symposium.

[46]  Ren Zhang,et al.  Ghost in the Binder: Binder Transaction Redirection Attacks in Android System Services , 2021, CCS.

[47]  Wenjia Li,et al.  DroidEnemy: Battling adversarial example attacks for Android malware detection , 2021, Digit. Commun. Networks.

[48]  Tahreem Yaqoob,et al.  A survey on common criteria (CC) evaluating schemes for security assessment of IT products , 2021, PeerJ Comput. Sci..

[49]  Sara Ricci,et al.  Hardware-based Cryptographic Accelerator for Post Quantum Era , 2021, 2021 13th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT).

[50]  N. J. Avinash,et al.  Providing Knee Movement Assistance using Android and IOT , 2021, 2021 2nd International Conference on Smart Electronics and Communication (ICOSEC).

[51]  Fan Ou,et al.  S3Feature: A Static Sensitive Subgraph-based Feature for Android Malware Detection , 2021, Computers & Security.

[52]  M. F. Amjad,et al.  A Systematic Evaluation of Android Anti-Malware Tools for Detection of Contemporary Malware , 2021, 2021 IEEE 19th International Conference on Embedded and Ubiquitous Computing (EUC).

[53]  Reza Azarderakhsh,et al.  Fast Strategies for the Implementation of SIKE Round 3 on ARM Cortex-M4 , 2021, IEEE Transactions on Circuits and Systems I: Regular Papers.

[54]  M. Fugini,et al.  A Malware Evasion Technique for Auditing Android Anti-Malware Solutions , 2021, 2021 IEEE 30th International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE).

[55]  Berna Örs,et al.  Instruction Extension of RV32I and GCC Back End for Ascon Lightweight Cryptography Algorithm , 2021, 2021 IEEE International Conference on Omni-Layer Intelligent Systems (COINS).

[56]  Francisco Martín-Rodríguez,et al.  Mobile Triage Applications: A Systematic Review in Literature and Play Store , 2021, Journal of Medical Systems.

[57]  Xiapu Luo,et al.  Research on Third-Party Libraries in Android Apps: A Taxonomy and Systematic Literature Review , 2021, IEEE Transactions on Software Engineering.

[58]  Chunfu Jia,et al.  Active Warden Attack: On the (In)Effectiveness of Android App Repackage-Proofing , 2021, IEEE Transactions on Dependable and Secure Computing.

[59]  Ajay Chawla Pegasus Spyware – 'A Privacy Killer' , 2021 .

[60]  B. R. Chandavarkar,et al.  Comparative Analysis of Modern Mobile Operating Systems , 2021, 2021 12th International Conference on Computing Communication and Networking Technologies (ICCCNT).

[61]  Ankita Ankita,et al.  Machine Learning and Deep Learning for Malware and Ransomware Attacks in 6G Network , 2021, 2021 Fourth International Conference on Computational Intelligence and Communication Technologies (CCICT).

[62]  Reza Azarderakhsh,et al.  Cryptographic Accelerators for Digital Signature Based on Ed25519 , 2021, IEEE Transactions on Very Large Scale Integration (VLSI) Systems.

[63]  Adib Akl,et al.  IoT-Driven Workflows for Risk Management and Control of Beehives , 2021, Diversity.

[64]  A. Dmitrienko,et al.  RIP StrandHogg: a practical StrandHogg attack detection method on Android , 2021, WISEC.

[65]  Mamoun Alazab,et al.  Betalogger: Smartphone Sensor-based Side-channel Attack Detection and Text Inference Using Language Modeling and Dense MultiLayer Neural Network , 2021, ACM Trans. Asian Low Resour. Lang. Inf. Process..

[66]  Huawei's Harmony may challenge Android-Apple duopoly , 2021, Emerald Expert Briefings.

[67]  Yongqiang Lyu,et al.  VoltJockey: A New Dynamic Voltage Scaling-Based Fault Injection Attack on Intel SGX , 2021, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems.

[68]  Arash Habibi Lashkari,et al.  EntropLyzer: Android Malware Classification and Characterization Using Entropy Analysis of Dynamic Characteristics , 2021, 2021 Reconciling Data Analytics, Automation, Privacy, and Security: A Big Data Challenge (RDAAPS).

[69]  Niyati Baliyan,et al.  Comparative analysis of Android and iOS from security viewpoint , 2021, Comput. Sci. Rev..

[70]  Satheesh Kumar Sasidharan,et al.  ProDroid - An Android malware detection framework based on profile hidden Markov model , 2021, Pervasive Mob. Comput..

[71]  Mohsen Guizani,et al.  A Survey on Federated Learning: The Journey From Centralized to Distributed On-Site Learning and Beyond , 2021, IEEE Internet of Things Journal.

[72]  O. Alfandi,et al.  A Parallelized Database Damage Assessment Approach after Cyberattack for Healthcare Systems , 2021, Future Internet.

[73]  Azzam Mourad,et al.  FedMCCS: Multicriteria Client Selection Model for Optimal IoT Federated Learning , 2021, IEEE Internet of Things Journal.

[74]  Trent Jaeger,et al.  A Survey on Sensor-Based Threats and Attacks to Smart Devices and Applications , 2021, IEEE Communications Surveys & Tutorials.

[75]  Francesco Palmieri,et al.  Effective classification of android malware families through dynamic features and neural networks , 2021, Connect. Sci..

[76]  Xiapu Luo,et al.  ATVHunter: Reliable Version Detection of Third-Party Libraries for Vulnerability Identification in Android Applications , 2021, 2021 IEEE/ACM 43rd International Conference on Software Engineering (ICSE).

[77]  Tarik Taleb,et al.  Federated Machine Learning: Survey, Multi-Level Classification, Desirable Criteria and Future Directions in Communication and Networking Systems , 2021, IEEE Communications Surveys & Tutorials.

[78]  Gianluca Palermo,et al.  EVEREST: A design environment for extreme-scale big data analytics on heterogeneous platforms , 2021, 2021 Design, Automation & Test in Europe Conference & Exhibition (DATE).

[79]  Knut Ove Eliassen Strandens topologier , 2020, K&K - Kultur og Klasse.

[80]  R. Rokhim,et al.  Big Data Analysis of Paid and Free Applications in Google Playstore and Apple App Store to Know Application Characteristics and Monetization Opportunities for New Startup in Indonesia , 2020 .

[81]  Anfeng Liu,et al.  MAGLeak: A Learning-Based Side-Channel Attack for Password Recognition With Multiple Sensors in IIoT Environment , 2020, IEEE Transactions on Industrial Informatics.

[82]  Reza Azarderakhsh,et al.  Efficient Hardware Implementations for Elliptic Curve Cryptography over Curve448 , 2020, INDOCRYPT.

[83]  Alakananda Giri,et al.  A Study on Efficient Battery Management System Providing Features to Resolve Damage occurring in Mobile Phones , 2020 .

[84]  A. Aminuddin Android Assets Protection Using RSA and AES Cryptography to Prevent App Piracy , 2020, 2020 3rd International Conference on Information and Communications Technology (ICOIACT).

[85]  Debapriya Basu Roy,et al.  Efficient Hardware/Software Co-Design for Post-Quantum Crypto Algorithm SIKE on ARM and RISC-V based Microcontrollers , 2020, 2020 IEEE/ACM International Conference On Computer Aided Design (ICCAD).

[86]  Erin A. Vogel,et al.  Vaping-Related Mobile Apps Available in the Google Play Store After the Apple Ban: Content Review , 2020, Journal of medical Internet research.

[87]  Azzam Mourad,et al.  Internet of Things intrusion Detection: Centralized, On-Device, or Federated Learning? , 2020, IEEE Network.

[88]  Narseo Vallina-Rodriguez,et al.  Understanding Incentivized Mobile App Installs on Google Play Store , 2020, Internet Measurement Conference.

[89]  Walid Saad,et al.  Federated Learning for Internet of Things: Recent Advances, Taxonomy, and Open Challenges , 2020, IEEE Communications Surveys & Tutorials.

[90]  Ekta Gandotra,et al.  Android Malware Detection Techniques: A Literature Review , 2020 .

[91]  Guanhua Yan,et al.  Paging storm attacks against 4G/LTE networks from regional Android botnets: rationale, practicality, and implications , 2020, WISEC.

[92]  Jiaguang Sun,et al.  EM-Fuzz: Augmented Firmware Fuzzing via Memory Checking , 2020, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems.

[93]  R. K. Shyamasundar,et al.  Consistency analysis and flow secure enforcement of SELinux policies , 2020, Comput. Secur..

[94]  Gregory Mone,et al.  The quantum threat , 2020, Commun. ACM.

[95]  Hui Li,et al.  Multifeature-Based Behavior of Privilege Escalation Attack Detection Method for Android Applications , 2020, Mob. Inf. Syst..

[96]  Mamoun Alazab,et al.  Intelligent mobile malware detection using permission requests and API calls , 2020, Future Gener. Comput. Syst..

[97]  Sencun Zhu,et al.  Privacy Risk Analysis and Mitigation of Analytics Libraries in the Android Ecosystem , 2020, IEEE Transactions on Mobile Computing.

[98]  Yogendera Kumar Juice Jacking - The USB Charger Scam , 2020 .

[99]  V. S. Subrahmanian,et al.  A Data-driven Characterization of Modern Android Spyware , 2020, ACM Trans. Manag. Inf. Syst..

[100]  Madhumitha Ramamurthy,et al.  Fraudster Mobile Apps Detector in Google Playstore , 2020 .

[101]  Thar Baker,et al.  AlphaLogger: detecting motion-based side-channel attack using smartphone keystrokes , 2020, Journal of Ambient Intelligence and Humanized Computing.

[102]  Tony Yu-Ju Tu,et al.  On addressing RFID/NFC-based relay attacks: An overview , 2020, Decis. Support Syst..

[103]  Haipeng Cai,et al.  Identifying Mobile Inter-App Communication Risks , 2020, IEEE Transactions on Mobile Computing.

[104]  Yan Wang,et al.  Sentinel: generating GUI tests for sensor leaks in Android and Android wear apps , 2019, Software Quality Journal.

[105]  Bing Zhou,et al.  Are We Really Protected? An Investigation into the Play Protect Service , 2019, 2019 IEEE International Conference on Big Data (Big Data).

[106]  Sriram Sankaran,et al.  Attack Detection based on Statistical Analysis of Smartphone Resource Utilization , 2019, 2019 IEEE 16th India Council International Conference (INDICON).

[107]  Sakir Sezer,et al.  DL-Droid: Deep learning based android malware detection using real devices , 2019, Comput. Secur..

[108]  Long Nguyen-Vu,et al.  Android Fragmentation in Malware Detection , 2019, Comput. Secur..

[109]  Amit Kumar Sikder,et al.  A Context-Aware Framework for Detecting Sensor-Based Threats on Smart Devices , 2019, IEEE Transactions on Mobile Computing.

[110]  Proceedings of the 32nd International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2019) , 2019 .

[111]  Ali Ghrayeb,et al.  Latency and Reliability-Aware Workload Assignment in IoT Networks With Mobile Edge Clouds , 2019, IEEE Transactions on Network and Service Management.

[112]  Halim Halimi,et al.  Comparison of Algorithms and Technologies 2G, 3G, 4G and 5G , 2019, 2019 3rd International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT).

[113]  Bettina Schnor,et al.  Evaluation of Intrusion Detection Systems in IPv6 Networks , 2019, ICETE.

[114]  P. Crosta,et al.  Authentication of GNSS Orbital and Clock Parameters at Android Application Layer , 2019, Proceedings of the 32nd International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2019).

[115]  Sheng Wen,et al.  Who Activated My Voice Assistant? A Stealthy Attack on Android Phones Without Users' Awareness , 2019, ML4CS.

[116]  Zahi Nakad,et al.  Partial grid false data injection attacks against state estimation , 2019, International Journal of Electrical Power & Energy Systems.

[117]  lei wang,et al.  I Know What You Type on Your Phone: Keystroke Inference on Android Device Using Deep Learning , 2019 .

[118]  Jean-Pierre Hubaux,et al.  HideMyApp: Hiding the Presence of Sensitive Apps on Android , 2019, USENIX Security Symposium.

[119]  Iman Almomani,et al.  Ransomware Detection System for Android Applications , 2019, Electronics.

[120]  Ke Xu,et al.  DroidEvolver: Self-Evolving Android Malware Detection System , 2019, 2019 IEEE European Symposium on Security and Privacy (EuroS&P).

[121]  Tejas S. Borkar,et al.  Defending Against Universal Attacks Through Selective Feature Regeneration , 2019, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[122]  Jeehoon Kang,et al.  Promising-ARM/RISC-V: a simpler and faster operational concurrency model , 2019, PLDI.

[123]  Jean-Pierre Seifert,et al.  New vulnerabilities in 4G and 5G cellular access network protocols: exposing device capabilities , 2019, WiSec.

[124]  Anupam Joshi,et al.  RelExt: Relation Extraction using Deep Learning approaches for Cybersecurity Knowledge Graph Improvement , 2019, 2019 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM).

[125]  René Mayrhofer,et al.  The Android Platform Security Model , 2019, ACM Trans. Priv. Secur..

[126]  Iman Almomani,et al.  Android Applications Scanning: The Guide , 2019, 2019 International Conference on Computer and Information Sciences (ICCIS).

[127]  Zhang Wen,et al.  A Novel Hotfix Scheme for System Vulnerability Based on the Android Application Layer , 2019, Chinese Journal of Electronics.

[128]  Jacques Klein,et al.  Should You Consider Adware as Malware in Your Study? , 2019, 2019 IEEE 26th International Conference on Software Analysis, Evolution and Reengineering (SANER).

[129]  Kamlesh Dutta,et al.  A Survey on Various Threats and Current State of Security in Android Platform , 2019, ACM Comput. Surv..

[130]  Philip Raschke,et al.  Privacy implications of accelerometer data: a review of possible inferences , 2019, ICCSP.

[131]  Anil K. Jain,et al.  Fingerprint Presentation Attack Detection: Generalization and Efficiency , 2018, 2019 International Conference on Biometrics (ICB).

[132]  Li Li,et al.  Towards Mining Comprehensive Android Sandboxes , 2018, 2018 23rd International Conference on Engineering of Complex Computer Systems (ICECCS).

[133]  Shang Gao,et al.  I Know What You Type: Leaking User Privacy via Novel Frequency-Based Side-Channel Attacks , 2018, 2018 IEEE Global Communications Conference (GLOBECOM).

[134]  Azzam Mourad,et al.  Towards a Lightweight Policy-Based Privacy Enforcing Approach for IoT , 2018, 2018 International Conference on Computational Science and Computational Intelligence (CSCI).

[135]  Samer S. Saab,et al.  A Neural Network Approach for Indoor Fingerprinting-Based Localization , 2018, 2018 9th IEEE Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON).

[136]  Lishan Ke,et al.  RoughDroid: Operative Scheme for Functional Android Malware Detection , 2018, Secur. Commun. Networks.

[137]  A. Khazzaka,et al.  The role of smartphone game applications in improving laparoscopic skills , 2018, Advances in medical education and practice.

[138]  Xiaojiang Chen,et al.  A Video-based Attack for Android Pattern Lock , 2018, ACM Trans. Priv. Secur..

[139]  Kun Yang,et al.  A Security Sandbox Approach of Android Based on Hook Mechanism , 2018, Secur. Commun. Networks.

[140]  Qinyuan Li,et al.  An Active Android Application Repacking Detection Approach , 2018, 2018 13th APCA International Conference on Control and Soft Computing (CONTROLO).

[141]  Cong Zheng,et al.  Identifying and Evading Android Sandbox Through Usage-Profile Based Fingerprints , 2018 .

[142]  Zhen Han,et al.  Dynamic Privacy Leakage Analysis of Android Third-Party Libraries , 2018, 2018 1st International Conference on Data Intelligence and Security (ICDIS).

[143]  Sumit Kumar,et al.  Context Aware Dynamic Permission Model: A Retrospect of Privacy and Security in Android System , 2018, 2018 International Conference on Intelligent Circuits and Systems (ICICS).

[144]  P Sihombing,et al.  Development of building security integration system using sensors, microcontroller and GPS (Global Positioning System) based android smartphone , 2018 .

[145]  Gianluca Dini,et al.  Risk analysis of Android applications: A user-centric solution , 2018, Future Gener. Comput. Syst..

[146]  Abdelouahid Derhab,et al.  MalDozer: Automatic framework for android malware detection using deep learning , 2018, Digit. Investig..

[147]  Γεώργιος Κασαγιάννης,et al.  Security evaluation of Android Keystore , 2018 .

[148]  Hyung-Woo Lee,et al.  Mobile Forged App Identification System with Centralized Signature Self-verification Method , 2018, Lecture Notes in Electrical Engineering.

[149]  Aron Laszka,et al.  An Economic Study of the Effect of Android Platform Fragmentation on Security Updates , 2017, Financial Cryptography.

[150]  Jalal B. Hur,et al.  A survey on security issues, vulnerabilities and attacks in Android based smartphone , 2017, 2017 International Conference on Information and Communication Technologies (ICICT).

[151]  Igor Bilogrevic,et al.  Side-Channel Inference Attacks on Mobile Keypads Using Smartwatches , 2017, IEEE Transactions on Mobile Computing.

[152]  Alex X. Liu,et al.  Behavior Based Human Authentication on Touch Screen Devices Using Gestures and Signatures , 2017, IEEE Transactions on Mobile Computing.

[153]  Wenyuan Xu,et al.  DolphinAttack: Inaudible Voice Commands , 2017, CCS.

[154]  Michael Eichberg,et al.  CodeMatch: obfuscation won't conceal your repackaged app , 2017, ESEC/SIGSOFT FSE.

[155]  Yanfang Ye,et al.  HinDroid: An Intelligent Android Malware Detection System Based on Structured Heterogeneous Information Network , 2017, KDD.

[156]  Jacques Klein,et al.  Static analysis of android apps: A systematic literature review , 2017, Inf. Softw. Technol..

[157]  Shahid Alam,et al.  DyDroid: Measuring Dynamic Code Loading and Its Security Implications in Android Applications , 2017, 2017 47th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN).

[158]  Gang Wang,et al.  MR-Droid: A Scalable and Prioritized Analysis of Inter-App Communication Risks , 2017, 2017 IEEE Security and Privacy Workshops (SPW).

[159]  Nenad Medvidovic,et al.  A SEALANT for Inter-App Security Holes in Android , 2017, 2017 IEEE/ACM 39th International Conference on Software Engineering (ICSE).

[160]  Reza Azarderakhsh,et al.  Fault Diagnosis Schemes for Low-Energy Block Cipher Midori Benchmarked on FPGA , 2017, IEEE Transactions on Very Large Scale Integration (VLSI) Systems.

[161]  Reza Azarderakhsh,et al.  Fault Detection Architectures for Post-Quantum Cryptographic Stateless Hash-Based Secure Signatures Benchmarked on ASIC , 2016, ACM Trans. Embed. Comput. Syst..

[162]  Vijay Laxmi,et al.  Android inter-app communication threats and detection techniques , 2016, Comput. Secur..

[163]  Sharad Goykar,et al.  A Survey on a ICC-Based Malware Detection on Android , 2016 .

[164]  Jacques Traoré,et al.  Breaking into the KeyStore: A Practical Forgery Attack Against Android KeyStore , 2016, ESORICS.

[165]  Mauro Conti,et al.  No Free Charge Theorem: A Covert Channel via USB Charging Cable on Mobile Devices , 2016, ACNS.

[166]  Sébastien Marcel,et al.  The Replay-Mobile Face Presentation-Attack Database , 2016, 2016 International Conference of the Biometrics Special Interest Group (BIOSIG).

[167]  Yepang Liu,et al.  Taming Android fragmentation: Characterizing and detecting compatibility issues for Android apps , 2016, 2016 31st IEEE/ACM International Conference on Automated Software Engineering (ASE).

[168]  Chenxiong Qian,et al.  Toward Engineering a Secure Android Ecosystem , 2016, ACM Comput. Surv..

[169]  Sakir Sezer,et al.  Dynalog: an automated dynamic analysis framework for characterizing android applications , 2016, 2016 International Conference On Cyber Security And Protection Of Digital Services (Cyber Security).

[170]  Haoyu Wang,et al.  LibRadar: Fast and Accurate Detection of Third-Party Libraries in Android Apps , 2016, 2016 IEEE/ACM 38th International Conference on Software Engineering Companion (ICSE-C).

[171]  Jignesh Joshi,et al.  Android smartphone vulnerabilities: A survey , 2016, 2016 International Conference on Advances in Computing, Communication, & Automation (ICACCA) (Spring).

[172]  Vijay Laxmi,et al.  Intersection Automata Based Model for Android Application Collusion , 2016, 2016 IEEE 30th International Conference on Advanced Information Networking and Applications (AINA).

[173]  David Lie,et al.  IntelliDroid: A Targeted Input Generator for the Dynamic Analysis of Android Malware , 2016, NDSS.

[174]  Ke Xu,et al.  ICCDetector: ICC-Based Malware Detection on Android , 2016, IEEE Transactions on Information Forensics and Security.

[175]  Kyoji Shibutani,et al.  Midori: A Block Cipher for Low Energy , 2015, ASIACRYPT.

[176]  Dongdai Lin,et al.  RECTANGLE: a bit-slice lightweight block cipher suitable for multiple platforms , 2015, Science China Information Sciences.

[177]  Kabakus Abdullah Talha,et al.  APK Auditor: Permission-based Android malware detection system , 2015 .

[178]  Vrizlynn L. L. Thing,et al.  Securing Android , 2015, ACM Comput. Surv..

[179]  Muttukrishnan Rajarajan,et al.  Android Security: A Survey of Issues, Malware Penetration, and Defenses , 2015, IEEE Communications Surveys & Tutorials.

[180]  Reza Azarderakhsh,et al.  Reliable and Error Detection Architectures of Pomaranch for False-Alarm-Sensitive Cryptographic Applications , 2015, IEEE Transactions on Very Large Scale Integration (VLSI) Systems.

[181]  Peng Ning,et al.  Samsung KNOX and Enterprise Mobile Security , 2014, SPSM@CCS.

[182]  Ping Chen,et al.  A Study on Advanced Persistent Threats , 2014, Communications and Multimedia Security.

[183]  Yu Chen,et al.  A study of SSL Proxy attacks on Android and iOS mobile applications , 2014, 2014 IEEE 11th Consumer Communications and Networking Conference (CCNC).

[184]  Jacques Klein,et al.  FlowDroid: precise context, flow, field, object-sensitive and lifecycle-aware taint analysis for Android apps , 2014, PLDI.

[185]  Yuan Zhang,et al.  Vetting undesirable behaviors in android apps with permission use analysis , 2013, CCS.

[186]  Alex X. Liu,et al.  Secure unlocking of mobile touch screen devices by simple gestures: you can see it but you can not do it , 2013, MobiCom.

[187]  Yang Wang,et al.  Quantitative Security Risk Assessment of Android Permissions and Applications , 2013, DBSec.

[188]  Je-Ho Park,et al.  Fragmentation Problem in Android , 2013, 2013 International Conference on Information Science and Applications (ICISA).

[189]  Jean-Luc Danger,et al.  Evaluation of Delays PUFs on CMOS 65 nm Technology: ASIC vs FPGA , 2013 .

[190]  Daniele Sgandurra,et al.  A Survey on Security for Mobile Devices , 2013, IEEE Communications Surveys & Tutorials.

[191]  Christian A. Reuter,et al.  Differential Fault Analysis on Grøstl , 2012, 2012 Workshop on Fault Diagnosis and Tolerance in Cryptography.

[192]  Hahn-Ming Lee,et al.  DroidMat: Android Malware Detection through Manifest and API Calls Tracing , 2012, 2012 Seventh Asia Joint Conference on Information Security.

[193]  Jun Han,et al.  ACCessory: password inference using accelerometers on smartphones , 2012, HotMobile '12.

[194]  Zahid Anwar,et al.  Enhancing Stealthiness & Efficiency of Android Trojans and Defense Possibilities (EnSEAD) - Android's Malware Attack, Stealthiness and Defense: An Improvement , 2011, 2011 Frontiers of Information Technology.

[195]  Arash Reyhani-Masoleh,et al.  Reliable Hardware Architectures for the Third-Round SHA-3 Finalist Grostl Benchmarked on FPGA Platform , 2011, 2011 IEEE International Symposium on Defect and Fault Tolerance in VLSI and Nanotechnology Systems.

[196]  Nicolas Christin,et al.  All Your Droid Are Belong to Us: A Survey of Current Android Attacks , 2011, WOOT.

[197]  Swarat Chaudhuri,et al.  A Study of Android Application Security , 2011, USENIX Security Symposium.

[198]  Colin Tankard,et al.  Advanced Persistent threats and how to monitor and deter them , 2011, Netw. Secur..

[199]  Felix C. Freiling,et al.  Mobile Security Catching Up? Revealing the Nuts and Bolts of the Security of Mobile Devices , 2011, 2011 IEEE Symposium on Security and Privacy.

[200]  Adam J. Aviv,et al.  Smudge Attacks on Smartphone Touch Screens , 2010, WOOT.

[201]  Yuval Elovici,et al.  Securing Android-Powered Mobile Devices Using SELinux , 2010, IEEE Security & Privacy.

[202]  Alan Goode,et al.  Managing mobile security: How are we doing? , 2010, Netw. Secur..

[203]  Yuval Elovici,et al.  Google Android: A State-of-the-Art Review of Security Mechanisms , 2009, ArXiv.

[204]  Hao Chen,et al.  Defending against sensor-sniffing attacks on mobile phones , 2009, MobiHeld '09.

[205]  Gary McGraw,et al.  Static Analysis for Security , 2004, IEEE Secur. Priv..

[206]  Dimitrios Vamvatsikos,et al.  Incremental dynamic analysis , 2002 .

[207]  Thomas Ball,et al.  The concept of dynamic analysis , 1999, ESEC/FSE-7.

[208]  William Landi,et al.  Undecidability of static analysis , 1992, LOPL.

[209]  K. Suzaki,et al.  Trusted Execution Environment Hardware by Isolated Heterogeneous Architecture for Key Scheduling , 2022, IEEE Access.

[210]  A. R. Javed,et al.  Privacy of Web Browsers: A Challenge in Digital Forensics , 2022, Lecture Notes in Electrical Engineering.

[211]  Mehran Mozaffari Kermani,et al.  Time-Efficient Finite Field Microarchitecture Design for Curve448 and Ed448 on Cortex-M4 , 2022, IACR Cryptol. ePrint Arch..

[212]  Xuemei Wang Security Threats and Protection Based on Android Platform , 2022, 2021 International Conference on Big Data Analytics for Cyber-Physical System in Smart City.

[213]  Abel Z. Agghey,et al.  FakeAP Detector: An Android-Based Client-Side Application for Detecting Wi-Fi Hotspot Spoofing , 2022, IEEE Access.

[214]  Zheng Zhang,et al.  A Survey of Android Malware Detection Based on Deep Learning , 2022, ML4CS.

[215]  R. Azarderakhsh,et al.  Faster Isogenies for Post-quantum Cryptography: SIKE , 2022, CT-RSA.

[216]  G. Sudha Sadasivam,et al.  A Review on Android Malware: Attacks, Countermeasures and Challenges Ahead , 2021, J. Cyber Secur. Mobil..

[217]  Hui Li,et al.  Risk Measurement Method of Collusion Privilege Escalation Attacks for Android Apps Based on Feature Weight and Behavior Determination , 2021, Secur. Commun. Networks.

[218]  Takamichi Saito,et al.  Investigation of Power Consumption Attack on Android Devices , 2021, AINA.

[219]  Dennis Agyemanh Nana Gookyi,et al.  NIST Lightweight Cryptography Standardization Process: Classification of Second Round Candidates, Open Challenges, and Recommendations , 2021, J. Inf. Process. Syst..

[220]  Hwajeong Seo,et al.  Look-up the Rainbow: Efficient Table-based Parallel Implementation of Rainbow Signature on 64-bit ARMv8 Processors , 2021, IACR Cryptol. ePrint Arch..

[221]  Shivi Garg,et al.  Android security assessment: A review, taxonomy and research gap study , 2021, Comput. Secur..

[222]  Reza Azarderakhsh,et al.  Compressed SIKE Round 3 on ARM Cortex-M4 , 2021, SecureComm.

[223]  Hwajeong Seo,et al.  Kyber on ARM64: Compact Implementations of Kyber on 64-bit ARM Cortex-A Processors , 2021, IACR Cryptol. ePrint Arch..

[224]  Muhammad Alshurideh,et al.  Combating Against Potentially Harmful Mobile Apps , 2021, AICV.

[225]  Antonella Santone,et al.  Android Collusion Detection by means of Audio Signal Analysis with Machine Learning techniques , 2021, KES.

[226]  Mathy Vanhoef,et al.  Fragment and Forge: Breaking Wi-Fi Through Frame Aggregation and Fragmentation , 2021, IACR Cryptol. ePrint Arch..

[227]  Peter Schartner,et al.  Generic Parity-Based Concurrent Error Detection for Lightweight ARX Ciphers , 2020, IEEE Access.

[228]  K. Muthumanickam,et al.  A Security Scheme for Discovering Battery Draining Attacks in Android Smartphone , 2020 .

[229]  Toshihiro Yamauchi,et al.  Accessibility Service Utilization Rates in Android Applications Shared on Twitter , 2020, WISA.

[230]  Ugo Buy,et al.  Automated Test Selection for Android Apps Based on APK and Activity Classification , 2020, IEEE Access.

[231]  Arwa Alrawais Security Issues in Near Field Communications (NFC) , 2020 .

[232]  Richard E. Harang,et al.  SeqDroid: Obfuscated Android Malware Detection Using Stacked Convolutional and Recurrent Neural Networks , 2019, Deep Learning Applications for Cyber Security.

[233]  Jason S. Seibel,et al.  MOTION-BASED SIDE-CHANNEL ATTACK ON MOBILE KEYSTROKES , 2019 .

[234]  Mahmoud Rasras,et al.  Vulnerability of MEMS Gyroscopes to Targeted Acoustic Attacks , 2019, IEEE Access.

[235]  Julian Fiérrez,et al.  Introduction to Iris Presentation Attack Detection , 2019, Handbook of Biometric Anti-Spoofing, 2nd Ed..

[236]  Byung-seok Lee,et al.  Changes in the Android App Support Model , 2019 .

[237]  Graham Steel,et al.  Mind Your Keys? A Security Evaluation of Java Keystores , 2018, NDSS.

[238]  Ku Aina Afiqah Ku Adzman,et al.  Near Field Communication (NFC) Technology Security Vulnerabilities and Countermeasures , 2018 .

[239]  Azzam Mourad,et al.  Few are as Good as Many: An Ontology-Based Tweet Spam Detection Approach , 2018, IEEE Access.

[240]  Persin Kaur Granthi,et al.  Android Security: A Survey of Security Issues And Defenses , 2017 .

[241]  I Lakshmi,et al.  A generation of android: An emerging software platform for mobile devices , 2017 .

[242]  F. Jancy An FPGA Implementation of Fault Diagnosis Architecture of S-Box For Cryptographic Application , 2016 .

[243]  Abdullah Talha Kabakus,et al.  APK Auditor: Permission-based Android malware detection system , 2015, Digit. Investig..

[244]  Carol J. Fung,et al.  A Survey of Android Security Threats and Defenses , 2015, J. Wirel. Mob. Networks Ubiquitous Comput. Dependable Appl..

[245]  Dhananjay M. Dakhane,et al.  MOBILE MALWARE DETECTION , 2013 .

[246]  Ahmad-Reza Sadeghi,et al.  Towards Taming Privilege-Escalation Attacks on Android , 2012, NDSS.

[247]  Danny Iland,et al.  Detecting Android Malware on Network Level , 2011 .

[248]  Stefan Br,et al.  Analysis of the Android Architecture , 2010 .

[249]  Frank Maker,et al.  A Survey on Android vs . Linux , 2009 .