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Publications

Affiliated (recent) Publications

  1. I. Zografopoulos, C. Konstantinou, N. G. Tsoutsos, D. Zhu, and R. Broadwater, “Security assessment and impact analysis of cyberattacks in integrated T&D power systems,” arXiv preprint arXiv:2102.03215, 2021.
  2. F. Meng, F. S. Hosseini, and C. Yang, “A Self-Test Framework for Detecting Fault-induced Accuracy Drop in Neural Network Accelerators,” in Proceedings of the 26th Asia and South Pacific Design Automation Conference, 2021, pp. 722–727.
  3. C. H. Mendoza-Cardenas and A. J. Brockmeier, “Searching for waveforms on spatially-filtered epileptic ECoG,” arXiv preprint arXiv:2103.13853, 2021.
  4. J. Kim, P. K. Biswas, S. Bohacek, S. J. Mackey, S. Samoohi, and M. P. Patel, “Advanced protocols for the mitigation of friendly jamming in mobile ad-hoc networks,” Journal of Network and Computer Applications, p. 103037, 2021.
  5. P. Cronin, X. Gao, C. Yang, and H. Wang, “Charger-Surfing: Exploiting a Power Line Side-Channel for Smartphone Information Leakage,” 2021.
  6. L. Budaghyan, M. Calderini, C. Carlet, R. Coulter, and I. Villa, “Generalized isotopic shift construction for APN functions,” Designs, Codes and Cryptography, vol. 89, no. 1, pp. 19–32, 2021.
  7. B. Zhu, X. Lan, X. Guo, K. E. Barner, and C. Boncelet, “Multi-rate Attention Based GRU Model for Engagement Prediction,” in ICMI ’20: International Conference on Multimodal Interaction, Virtual Event, The Netherlands, October 25-29, 2020, 2020, pp. 841–848, doi: 10.1145/3382507.3417965.
  8. X. Zhang, C. Patterson, Y. Liu, C. Yang, C. J. Xue, and J. Hu, “Low Overhead Online Data Flow Tracking for Intermittently Powered Non-Volatile FPGAs,” ACM Journal on Emerging Technologies in Computing Systems (JETC), vol. 16, no. 3, pp. 1–20, 2020.
  9. C. Yang, P. Cronin, A. Agambayev, S. Ozev, A. E. Cetin, and A. Orailoglu, “A crowd-based explosive detection system with two-level feedback sensor calibration,” in Proceedings of the 39th International Conference on Computer-Aided Design, 2020, pp. 1–9.
  10. N. G. Tsoutsos, N. Gupta, and R. Karri, “Cybersecurity Road Map for Digital Manufacturing,” Computer, vol. 53, no. 9, pp. 80–84, 2020.
  11. I. Priyadarshini, H. Wang, and C. Cotton, “Some Cyberpsychology Techniques to Distinguish Humans and Bots for Authentication,” in Proceedings of the Future Technologies Conference (FTC) 2019, Cham, 2020, pp. 306–323.
  12. I. Priyadarshini and C. Cotton, “Internet Memes: A Novel Approach to Distinguish Humans and Bots for Authentication,” in Proceedings of the Future Technologies Conference (FTC) 2019, Cham, 2020, pp. 204–222.
  13. I. Priyadarshini and C. Cotton, “Intelligence in cyberspace: the road to cyber singularity,” Journal of Experimental & Theoretical Artificial Intelligence, pp. 1–35, 2020.
  14. D. Mouris and N. G. Tsoutsos, “Pythia: Intellectual Property Verification in Zero-Knowledge,” in Design Automation Conference (DAC), 2020, pp. 1–6.
  15. D. Mouris, C. Gouert, N. Gupta, and N. G. Tsoutsos, “Peak your Frequency: Advanced Search of 3D CAD Files in the Fourier Domain,” IEEE Access, vol. 8, pp. 1–16, 2020.
  16. O. Mazonka, E. Sarkar, E. Chielle, N. G. Tsoutsos, and M. Maniatakos, “Practical Data-in-Use Protection Using Binary Decision Diagrams,” IEEE Access, vol. 8, pp. 23847–23862, 2020.
  17. S. Matiz and K. E. Barner, “Conformal prediction based active learning by linear regression optimization,” Neurocomputing, vol. 388, pp. 157–169, 2020, doi: 10.1016/j.neucom.2020.01.018.
  18. M. J. D. Lucia and C. Cotton, “A network security classifier defense: against adversarial machine learning attacks,” in Proceedings of the 2nd ACM Workshop on Wireless Security and Machine Learning, WiseML@WiSec 2020, Linz, Austria, July 13, 2020, 2020, pp. 67–73, doi: 10.1145/3395352.3402627.
  19. W. Liu et al., “DEPS: Exploiting a Dynamic Error Prechecking Scheme to Improve the Read Performance of SSD,” IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 2020.
  20. Q. Liu, T. Liu, Z. Liu, W. Wen, and C. Yang, “Monitoring the health of emerging neural network accelerators with cost-effective concurrent test,” in 2020 57th ACM/IEEE Design Automation Conference (DAC), 2020, pp. 1–6.
  21. W. Li, G. Mac, N. G. Tsoutsos, N. Gupta, and R. Karri, “Computer aided design (CAD) model search and retrieval using frequency domain file conversion,” Additive Manufacturing, vol. 36, p. 101554, 2020.
  22. T. Li, D. Han, Y. Chen, R. Zhang, Y. Zhang, and T. Hedgpeth, “IndoorWaze: A Crowdsourcing-Based Context-Aware Indoor Navigation System,” IEEE Trans. Wirel. Commun., vol. 19, no. 8, pp. 5461–5472, 2020, doi: 10.1109/TWC.2020.2993545.
  23. J. Li et al., “RF-Rhythm: Secure and Usable Two-Factor RFID Authentication,” in 39th IEEE Conference on Computer Communications, INFOCOM 2020, Toronto, ON, Canada, July 6-9, 2020, 2020, pp. 2194–2203, doi: 10.1109/INFOCOM41043.2020.9155427.
  24. A. Lasisi and N. Attoh-Okine, “An unsupervised learning framework for track quality index and safety,” Transportation Infrastructure Geotechnology, vol. 7, no. 1, pp. 1–12, 2020.
  25. X. Lan, X. Guo, and K. E. Barner, “PAC-Bayesian Generalization Bounds for MultiLayer Perceptrons,” CoRR, vol. abs/2006.08888, 2020, [Online]. Available: https://arxiv.org/abs/2006.08888.
  26. X. Lan and K. E. Barner, “A Probabilistic Representation of Deep Learning for Improving The Information Theoretic Interpretability,” CoRR, vol. abs/2010.14054, 2020, [Online]. Available: https://arxiv.org/abs/2010.14054.
  27. Y. Hu, R. Zhang, and Y. Zhang, “KV-Fresh: Freshness Authentication for Outsourced Multi-Version Key-Value Stores,” in 39th IEEE Conference on Computer Communications, INFOCOM 2020, Toronto, ON, Canada, July 6-9, 2020, 2020, pp. 1638–1647, doi: 10.1109/INFOCOM41043.2020.9155270.
  28. Y. Hu and R. Zhang, “A Spatiotemporal Approach for Secure Crowdsourced Radio Environment Map Construction,” IEEE/ACM Trans. Netw., vol. 28, no. 4, pp. 1790–1803, 2020, doi: 10.1109/TNET.2020.2992939.
  29. F. S. Hosseini and C. Yang, “A Compile-time Framework for Tolerating Read Disturbance in STT-RAM,” IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 2020.
  30. E. N. Hamulyák, A. J. Brockmeier, J. D. Killas, S. Ananiadou, S. Middeldorp, and A. M. Leroi, “Women’s health in The BMJ: a data science history,” BMJ open, vol. 10, no. 10, p. e039759, 2020.
  31. X. Guo et al., “Continual Learning Long Short Term Memory,” in Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing: Findings, EMNLP 2020, Online Event, 16-20 November 2020, 2020, pp. 1817–1822, doi: 10.18653/v1/2020.findings-emnlp.164.
  32. X. Guo, L. F. Polanía, B. Zhu, C. Boncelet, and K. E. Barner, “Graph Neural Networks for Image Understanding Based on Multiple Cues: Group Emotion Recognition and Event Recognition as Use Cases,” in IEEE Winter Conference on Applications of Computer Vision, WACV 2020, Snowmass Village, CO, USA, March 1-5, 2020, 2020, pp. 2910–2919, doi: 10.1109/WACV45572.2020.9093547.
  33. X. Guo, L. F. Polanía, and K. E. Barner, “Audio-video Emotion Recognition in the Wild using Deep Hybrid Networks,” CoRR, vol. abs/2002.09023, 2020, [Online]. Available: https://arxiv.org/abs/2002.09023.
  34. C. Gouert and N. G. Tsoutsos, “ROMEO: Conversion and Evaluation of HDL Designs in the Encrypted Domain,” in Design Automation Conference (DAC), 2020, pp. 1–6.
  35. X. Evangelopoulos, A. J. Brockmeier, T. Mu, and J. Y. Goulermas, “Circular object arrangement using spherical embeddings,” Pattern Recognition, vol. 103, p. 107192, 2020.
  36. G. P. Cimellaro and N. O. Attoh-Okine, Special Collection on Resilience Quantification and Modeling for Decision Making. American Society of Civil Engineers, 2020.
  37. E. Chielle, N. G. Tsoutsos, O. Mazonka, and M. Maniatakos, “E3X: Encrypt-Everything-Everywhere ISA eXtensions for Private Computation,” IEEE Transactions on Dependable and Secure Computing, pp. 1–14, 2020.
  38. E. Chielle, O. Mazonka, H. Gamil, S. Kastratovic, N. G. Tsoutsos, and M. Maniatakos, “E3: Accelerating Fully Homomorphic Encryption by Bridging Modular and Bit-Level Arithmetic,” Cryptology ePrint Archive, Report 2018/1013, pp. 1–30, 2020.
  39. R. Cammarota et al., “Trustworthy AI Inference Systems: An Industry Research View,” arXiv preprint arXiv:2008.04449, 2020.
  40. L. Budaghyan, M. Calderini, C. Carlet, R. S. Coulter, and I. Villa, “Constructing APN functions through isotopic shifts,” IEEE Transactions on Information Theory, vol. 66, no. 8, pp. 5299–5309, 2020.
  41. A. Bogdanova, N. Attoh-Okine, and T. Sakurai, “Risk and Advantages of Federated Learning for Health Care Data Collaboration,” ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, vol. 6, no. 3, p. 04020031, 2020.
  42. N. G. Tsoutsos, N. Gupta, and M. Maniatakos, System and method for malware detection in additive manufactured parts. Google Patents, 2019.
  43. P. Zingo, A. Brockmeier, and A. Novocin, “Transfusion: Reproducibility Study and Analysis,” 2019.
  44. B. Zhu, X. Guo, K. E. Barner, and C. Boncelet, “Automatic Group Cohesiveness Detection With Multi-modal Features,” CoRR, vol. abs/1910.01197, 2019, [Online]. Available: http://arxiv.org/abs/1910.01197.
  45. C. Yang and Y. Xue, “A Scalable and Process Variation Aware NVM-FPGA Placement Algorithm,” in Proceedings of the 2019 on Great Lakes Symposium on VLSI, 2019, pp. 165–170.
  46. C. Yang and Z. Chen, “A Processing-In-Memory Implementation of SHA-3 Using a Voltage-Gated Spin Hall-Effect Driven MTJ-based Crossbar,” in Proceedings of the 2019 on Great Lakes Symposium on VLSI, 2019, pp. 195–200.
  47. S. Wang, F. Wu, C. Yang, J. Zhou, C. Xie, and J. Wan, “WAS: Wear Aware Superblock Management for Prolonging SSD Lifetime,” in Proceedings of the 56th Annual Design Automation Conference 2019, 2019, pp. 1–6.
  48. N. G. Tsoutsos and M. Maniatakos, “Lightweight Fault Tolerance for Secure Aggregation of Homomorphic Data,” in Security and Fault Tolerance in Internet of Things, Springer, 2019, pp. 87–110.
  49. P. Przyby\la, A. J. Brockmeier, and S. Ananiadou, “Quantifying risk factors in medical reports with a context-aware linear model,” Journal of the American Medical Informatics Association, vol. 26, no. 6, pp. 537–546, 2019.
  50. M. Nabeel, M. Ashraf, E. Chielle, N. G. Tsoutsos, and M. Maniatakos, Technical report: CoPHEE: Co-processor for Partially Homomorphic Encrypted Execution. 2019.
  51. M. Nabeel, M. Ashraf, E. Chielle, N. G. Tsoutsos, and M. Maniatakos, “CoPHEE: Co-processor for Partially Homomorphic Encrypted Execution,” in 2019 IEEE International Symposium on Hardware Oriented Security and Trust (HOST), 2019, pp. 131–140.
  52. S. Matiz and K. E. Barner, “Inductive Conformal Predictor for Sparse Coding Classifiers: Applications to Image Classification,” in IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2019, Brighton, United Kingdom, May 12-17, 2019, 2019, pp. 3307–3311, doi: 10.1109/ICASSP.2019.8682740.
  53. S. Matiz and K. E. Barner, “Inductive conformal predictor for convolutional neural networks: Applications to active learning for image classification,” Pattern Recognit., vol. 90, pp. 172–182, 2019, doi: 10.1016/j.patcog.2019.01.035.
  54. M. J. D. Lucia and C. Cotton, “Detection of Encrypted Malicious Network Traffic using Machine Learning,” in 2019 IEEE Military Communications Conference, MILCOM 2019, Norfolk, VA, USA, November 12-14, 2019, 2019, pp. 1–6, doi: 10.1109/MILCOM47813.2019.9020856.
  55. T. Liu, W. Wen, L. Jiang, Y. Wang, C. Yang, and G. Quan, “A fault-tolerant neural network architecture,” in 2019 56th ACM/IEEE Design Automation Conference (DAC), 2019, pp. 1–6.
  56. Y. Li, Y. Hu, R. Zhang, Y. Zhang, and T. Hedgpeth, “Secure indoor positioning against signal strength attacks via optimized multi-voting,” in Proceedings of the International Symposium on Quality of Service, IWQoS 2019, Phoenix, AZ, USA, June 24-25, 2019, 2019, p. 33:1-33:10, doi: 10.1145/3326285.3329068.
  57. A. Lasisi, M. O. Sadiq, I. Balogun, A. Tunde-Lawal, and N. O. Attoh-Okine, “A Boosted Tree Machine Learning Alternative to Predictive Evaluation of Nondestructive Concrete Compressive Strength,” in 18th IEEE International Conference On Machine Learning And Applications, ICMLA 2019, Boca Raton, FL, USA, December 16-19, 2019, 2019, pp. 321–324, doi: 10.1109/ICMLA.2019.00060.
  58. A. Lasisi, A. Merheb, A. Zarembski, and N. O. Attoh-Okine, “Rail Track Quality and T-Stochastic Neighbor Embedding for Hybrid Track Index,” in 2019 IEEE International Conference on Big Data (Big Data), Los Angeles, CA, USA, December 9-12, 2019, 2019, pp. 1470–1477, doi: 10.1109/BigData47090.2019.9006236.
  59. X. Lan and K. E. Barner, “Regularization Learning for Image Recognition,” in 18th IEEE International Conference On Machine Learning And Applications, ICMLA 2019, Boca Raton, FL, USA, December 16-19, 2019, 2019, pp. 1–7, doi: 10.1109/ICMLA.2019.00010.
  60. X. Lan and K. E. Barner, “Explicitly Bayesian Regularizations in Deep Learning,” CoRR, vol. abs/1910.09732, 2019, [Online]. Available: http://arxiv.org/abs/1910.09732.
  61. X. Lan and K. E. Barner, “A Probabilistic Representation of Deep Learning,” CoRR, vol. abs/1908.09772, 2019, [Online]. Available: http://arxiv.org/abs/1908.09772.
  62. J. Kim and S. Bohacek, “Efficient modeling of network flooding performance with proactive retransmissions in mobile ad hoc networks,” Wireless Networks, vol. 25, no. 5, pp. 2423–2436, 2019.
  63. L. Jin, S. Hao, H. Wang, and C. Cotton, “Unveil the Hidden Presence: Characterizing the Backend Interface of Content Delivery Networks,” in 27th IEEE International Conference on Network Protocols, ICNP 2019, Chicago, IL, USA, October 8-10, 2019, 2019, pp. 1–11, doi: 10.1109/ICNP.2019.8888058.
  64. R. Houser, Z. Li, C. Cotton, and H. Wang, “An investigation on information leakage of DNS over TLS,” in Proceedings of the 15th International Conference on Emerging Networking Experiments And Technologies, 2019, pp. 123–137.
  65. F. S. Hosseini and C. Yang, “Comprehensive Evaluation of Program Reliability with ComFIDet: An Integrated Fault Injection and Detection Framework for Embedded Systems,” in 2019 IEEE International Conference on Embedded Software and Systems (ICESS), 2019, pp. 1–8.
  66. F. S. Hosseini and C. Yang, “Compiler-Directed and Architecture-Independent Mitigation of Read Disturbance Errors in STT-RAM,” in 2019 Design, Automation & Test in Europe Conference & Exhibition (DATE), 2019, pp. 222–227.
  67. X. Guo, L. F. Polanía, B. Zhu, C. Boncelet, and K. E. Barner, “Graph Neural Networks for Image Understanding Based on Multiple Cues: Group Emotion Recognition and Event Recognition as Use Cases,” CoRR, vol. abs/1909.12911, 2019, [Online]. Available: http://arxiv.org/abs/1909.12911.
  68. X. Guo, L. F. Polanía, J. Garcia-Frías, and K. E. Barner, “Social Relationship Recognition Based on A Hybrid Deep Neural Network,” in 14th IEEE International Conference on Automatic Face & Gesture Recognition, FG 2019, Lille, France, May 14-18, 2019, 2019, pp. 1–5, doi: 10.1109/FG.2019.8756602.
  69. M. J. De Lucia and C. Cotton, “Detection of encrypted malicious network traffic using machine learning,” in MILCOM 2019-2019 IEEE Military Communications Conference (MILCOM), 2019, pp. 1–6.
  70. M. J. De Lucia and C. Cotton, “Adversarial machine learning for cyber security,” Journal of Information Systems Applied Research, vol. 12, no. 1, p. 26, 2019.
  71. P. Cronin and C. Yang, “A Fetching Tale: Covert Communication with the Hardware Prefetcher,” in 2019 IEEE International Symposium on Hardware Oriented Security and Trust (HOST), 2019, pp. 101–110.
  72. P. Cronin, C. Gouert, D. Mouris, N. G. Tsoutsos, and C. Yang, “Covert Data Exfiltration Using Light and Power Channels,” in 2019 IEEE 37th International Conference on Computer Design (ICCD), 2019, pp. 301–304.
  73. P. Cronin, C. Gouert, D. Mouris, N. G. Tsoutsos, and C. Yang, “Covert Data Exfiltration Using Light and Power Channels,” in 2019 IEEE 37th International Conference on Computer Design (ICCD), 2019, pp. 301–304.
  74. R. S. Coulter, S. De Winter, A. Kodess, and F. Lazebnik, “A result on polynomials derived via graph theory,” Mathematics Magazine, vol. 92, no. 4, pp. 288–295, 2019.
  75. R. S. Coulter, “COORDINATISING PLANES OF PRIME POWER ORDER USING FINITE FIELDS,” Journal of the Australian Mathematical Society, vol. 106, no. 2, pp. 184–199, 2019.
  76. S. M. Cioaba, R. Coulter, E. Fiorini, and Q. Xiang, “Preface to the Special Issue of Discrete Mathematics: Dedicated to the Algebraic and Extremal Graph Theory Conference, August 7-10, 2017, University of Delaware, Newark, USA.,” Discret. Math., vol. 342, no. 10, p. 2759, 2019.
  77. F. Chen, Y. Luo, N. G. Tsoutsos, M. Maniatakos, K. Shahin, and N. Gupta, “Embedding tracking codes in additive manufactured parts for product authentication,” Advanced Engineering Materials, vol. 21, no. 4, p. 1800495, 2019.
  78. P. G. Cesarz and R. S. Coulter, “Image sets with regularity of differences,” Cryptography and Communications, vol. 11, no. 6, pp. 1307–1337, 2019.
  79. L. Budaghyan, M. Calderini, C. Carlet, R. S. Coulter, and I. Villa, “On Isotopic Shift Construction for Planar Functions,” in IEEE International Symposium on Information Theory, ISIT 2019, Paris, France, July 7-12, 2019, 2019, pp. 2962–2966, doi: 10.1109/ISIT.2019.8849339.
  80. L. Budaghyan, M. Calderini, C. Carlet, R. Coulter, and I. I Villa, “Generalized Isotopic Shift of Gold Functions,” 2019.
  81. A. J. Brockmeier, M. Ju, P. Przyby\la, and S. Ananiadou, “Improving reference prioritisation with PICO recognition,” BMC medical informatics and decision making, vol. 19, no. 1, pp. 1–14, 2019.
  82. R. Bian, S. Hao, H. Wang, A. Dhamdere, A. Dainotti, and C. Cotton, “Towards passive analysis of anycast in global routing: Unintended impact of remote peering,” ACM SIGCOMM Computer Communication Review, vol. 49, no. 3, pp. 18–25, 2019.
  83. D. Badawi, S. Ozev, J. B. Christen, C. Yang, A. Orailoglu, and A. E. Çetin, “Detecting Gas Vapor Leaks through Uncalibrated Sensor Based CPS,” in ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2019, pp. 8296–8300.
  84. D. Badawi, T. Ayhan, S. Ozev, C. Yang, A. Orailoglu, and A. E. Cetin, “Detecting Gas Vapor Leaks Using Uncalibrated Sensors,” IEEE Access, vol. 7, pp. 155701–155710, 2019.
  85. H. Aghaei Khouzani and C. Yang, “Tuning Track-based NVM Caches for Low-Power IoT Devices,” in Proceedings of the 2019 on Great Lakes Symposium on VLSI, 2019, pp. 513–518.
  86. X. Zhang, C. Patterson, Y. Liu, C. Yang, C. J. Xue, and J. Hu, “Low Overhead Online Checkpoint for Intermittently Powered Non-volatile FPGAs,” in 2018 IEEE Computer Society Annual Symposium on VLSI (ISVLSI), 2018, pp. 238–244.
  87. J. Zhang, R. Zhang, Y. Zhang, and G. Yan, “The Rise of Social Botnets: Attacks and Countermeasures,” IEEE Trans. Dependable Secur. Comput., vol. 15, no. 6, pp. 1068–1082, 2018, doi: 10.1109/TDSC.2016.2641441.
  88. J. Zhang, J. Sun, R. Zhang, Y. Zhang, and X. Hu, “Privacy-Preserving Social Media Data Outsourcing,” in 2018 IEEE Conference on Computer Communications, INFOCOM 2018, Honolulu, HI, USA, April 16-19, 2018, 2018, pp. 1106–1114, doi: 10.1109/INFOCOM.2018.8486242.
  89. H. Zhang, C. Zhang, Q. Hu, C. Yang, and J. Shu, “Performance analysis on structure of racetrack memory,” in 2018 23rd Asia and South Pacific Design Automation Conference (ASP-DAC), 2018, pp. 367–374.
  90. L. Yuan, Y. Hu, Y. Li, R. Zhang, Y. Zhang, and T. Hedgpeth, “Secure RSS-Fingerprint-Based Indoor Positioning: Attacks and Countermeasures,” in 2018 IEEE Conference on Communications and Network Security, CNS 2018, Beijing, China, May 30 – June 1, 2018, 2018, pp. 1–9, doi: 10.1109/CNS.2018.8433131.
  91. X. Yao, Y. Chen, R. Zhang, Y. Zhang, and Y. Lin, “Beware of What You Share: Inferring User Locations in Venmo,” IEEE Internet Things J., vol. 5, no. 6, pp. 5109–5118, 2018, doi: 10.1109/JIOT.2018.2844218.
  92. F. Wu, J. Zhou, S. Wang, Y. Du, C. Yang, and C. Xie, “FastGC: accelerate garbage collection via an efficient copyback-based data migration in SSDs,” in 2018 55th ACM/ESDA/IEEE Design Automation Conference (DAC), 2018, pp. 1–6.
  93. F. B. Wala and C. Cotton, “Unconstrained Endpoint Security System: UEPTSS,” International Journal of Network Security & Its Applications (IJNSA) Vol, vol. 10, 2018.
  94. N. G. Tsoutsos and M. Maniatakos, “Anatomy of Memory Corruption Attacks and Mitigations in Embedded Systems,” IEEE Embedded Systems Letters, vol. 10, no. 3, pp. 95–98, 2018.
  95. F. Meng, Y. Xue, and C. Yang, “Power-and Endurance-Aware Neural Network Training in NVM-Based Platforms,” IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, vol. 37, no. 11, pp. 2709–2719, 2018.
  96. S. M. Mathews, C. Kambhamettu, and K. E. Barner, “A novel application of deep learning for single-lead ECG classification,” Comput. Biol. Medicine, vol. 99, pp. 53–62, 2018, doi: 10.1016/j.compbiomed.2018.05.013.
  97. T. Li, Y. Chen, R. Zhang, Y. Zhang, and T. Hedgpeth, “Secure Crowdsourced Indoor Positioning Systems,” in 2018 IEEE Conference on Computer Communications, INFOCOM 2018, Honolulu, HI, USA, April 16-19, 2018, 2018, pp. 1034–1042, doi: 10.1109/INFOCOM.2018.8486398.
  98. A. Lasisi, E. N. Martey, D. Guillot, and N. O. Attoh-Okine, “A three-step agglomerated Machine Learning: An alternative to Weibull Defect Analysis of Rail Infrastructure,” in IEEE International Conference on Big Data, Big Data 2018, Seattle, WA, USA, December 10-13, 2018, 2018, pp. 4508–4515, doi: 10.1109/BigData.2018.8622322.
  99. X. Lan and K. E. Barner, “From MRFS to CNNS: A novel image restoration method,” in 52nd Annual Conference on Information Sciences and Systems, CISS 2018, Princeton, NJ, USA, March 21-23, 2018, 2018, pp. 1–5, doi: 10.1109/CISS.2018.8362260.
  100. J. Kim, S. Bohacek, P. K. Biswas, S. Samoohi, S. Mackey, and M. Patel, “Friendly-Jamming-Aware Routing Protocols for Tactical Networks,” in 2018 IEEE 37th International Performance Computing and Communications Conference (IPCCC), 2018, pp. 1–6.
  101. H. A. Khouzani, C. Liu, and C. Yang, “Architecting data placement in ssds for efficient secure deletion implementation,” in 2018 IEEE/ACM International Conference on Computer-Aided Design (ICCAD), 2018, pp. 1–6.
  102. X. Jin, J. Sun, R. Zhang, Y. Zhang, and C. Zhang, “SpecGuard: Spectrum Misuse Detection in Dynamic Spectrum Access Systems,” IEEE Trans. Mob. Comput., vol. 17, no. 12, pp. 2925–2938, 2018, doi: 10.1109/TMC.2018.2823314.
  103. L. Jin, S. Hao, H. Wang, and C. Cotton, “Your Remnant Tells Secret: Residual Resolution in DDoS Protection Services,” in 48th Annual IEEE/IFIP International Conference on Dependable Systems and Networks, DSN 2018, Luxembourg City, Luxembourg, June 25-28, 2018, 2018, pp. 362–373, doi: 10.1109/DSN.2018.00046.
  104. D. Han, Y. Chen, T. Li, R. Zhang, Y. Zhang, and T. Hedgpeth, “Proximity-Proof: Secure and Usable Mobile Two-Factor Authentication,” in Proceedings of the 24th Annual International Conference on Mobile Computing and Networking, MobiCom 2018, New Delhi, India, October 29 – November 02, 2018, 2018, pp. 401–415, doi: 10.1145/3241539.3241574.
  105. X. Guo, B. Zhu, L. F. Polanía, C. Boncelet, and K. E. Barner, “Group-Level Emotion Recognition Using Hybrid Deep Models Based on Faces, Scenes, Skeletons and Visual Attentions,” in Proceedings of the 2018 on International Conference on Multimodal Interaction, ICMI 2018, Boulder, CO, USA, October 16-20, 2018, 2018, pp. 635–639, doi: 10.1145/3242969.3264990.
  106. X. Guo, L. F. Polanía, and K. E. Barner, “Smile Detection in the Wild Based on Transfer Learning,” in 13th IEEE International Conference on Automatic Face & Gesture Recognition, FG 2018, Xi’an, China, May 15-19, 2018, 2018, pp. 679–686, doi: 10.1109/FG.2018.00107.
  107. M. J. De Luciaa and C. Cottonb, “Importance of features in adversarial machine learning for cyber security,” in Proceedings of the Conference on Information Systems Applied Research ISSN, 2018, vol. 2167, p. 1508.
  108. M. J. De Lucia and C. Cotton, “Identifying and detecting applications within TLS traffic,” in Cyber Sensing 2018, 2018, vol. 10630, p. 106300U.
  109. P. Cronin, C. Yang, and Y. Liu, “Reliability and Security in Non-volatile Processors, Two Sides of the Same Coin,” in 2018 IEEE Computer Society Annual Symposium on VLSI (ISVLSI), 2018, pp. 112–117.
  110. P. Cronin, C. Yang, and Y. Liu, “A collaborative defense against wear out attacks in non-volatile processors,” in 2018 55th ACM/ESDA/IEEE Design Automation Conference (DAC), 2018, pp. 1–6.
  111. P. Cronin and C. Yang, “Lowering the barrier to online malware detection through low frequency sampling of HPCs,” in 2018 IEEE International Symposium on Hardware Oriented Security and Trust (HOST), 2018, pp. 177–180.
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