Loukas Lazos

Interests

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Courses

Scholarly Contributions

Chapters

• Burd, G. D., Tomanek, D. J., Blowers, P., Bolger, M. S., Cox, J., Elfring, L. K., Grubbs, E. A., Hunter, J., Johns, K. A., Lazos, L., Lysecky, R. L., Milsom, J. A., Novodvorsky, I., Pollard, J. R., Prather, E. E., Talanquer, V. A., Thamvichai, R., Tharp, H. S., & Wallace, C. (2016). Developing faculty cultures for evidence-based teaching practices in STEM: A progress report.. In Transforming Institutions: 21st Century Undergraduate STEM. West Lafayette, IN.: Purdue University Press.
• Blowers, P., Burd, G. D., Bolger, M. S., Johns, K. A., Lazos, L., Lysecky, R. L., Milsom, J. A., Novodvorsky, I., Pollard, J. R., Prather, E. E., Talanquer, V. A., Thamvichai, R., Tharp, H. S., Wallace, C. S., Cox, J., Elfring, L., Grubbs, E., & Hunter, J. (2015). Developing Faculty Cultures for Evidence-Based Teaching Practices in STEM: A Progress Report. In Transforming Institutions, Undergraduate STEM Education for the 21st Century(pp 90-102). Indianapolis, IN: Purdue University Press,.
• Burd, G. D., Tomanek, D. J., Blowers, P., Bolger, M. S., Cox, J., Elfring, L. K., Grubbs, E. A., Hunter, J., Johns, K. A., Lazos, L., Lysecky, R. L., Milsom, J. A., Novodvorsky, I., Pollard, J. R., Prather, E. E., Talanquer, V. A., Thamvichai, R., Tharp, H. S., Wallace, C., , Burd, G. D., et al. (2015). Developing faculty cultures for evidence-based teaching practices in STEM: A progress report.. In Transforming Institutions: 21st Century Undergraduate STEM. West Lafayette, IN.: Purdue University Press.
• Blowers, P., Burd, G. D., Bolger, M. S., Johns, K. A., Lazos, L., Lysecky, R. L., Milsom, J. A., Novodvorsky, I., Pollard, J. R., Prather, E. E., Talanquer, V. A., Thamvichai, R., Tharp, H. S., Wallace, C. S., Cox, J., Elfring, L., Grubbs, E., Hunter, J., Blowers, P., , Burd, G. D., et al. (2014). Developing Faculty Cultures for Evidence-Based Teaching Practices in STEM: A Progress Report. In Transforming Institution: 21st Century STEM Undergraduate Education Conference. Indianapolis, IN: AAU-STEM.

Journals/Publications

• Calis, G., Shivaramaiah, S., Koyluoglu, O., & Lazos, L. (2019). Repair Strategies for Mobile Storage Systems. IEEE Transactions on Cloud Computing (TCC), 16 Pages. doi:10.1109/TCC.2019.2914436
• Ghose, N., Lazos, L., Rozenblit, J. W., & Breiger, R. L. (2019). Proofs of Physical Reliability for Cloud Storage Systems. IEEE Transactions on Parallel and Distributed Systems (TPDS).
  More info

  With the limited information on the cyber-attacks available in an unclassified regime, it is difficult to standardize the analysis of these attacks. In addition, this limitation makes the implementation of this analysis on any future attack challenging. In this work, we address the problem of modeling and analyzing cyber attacks using a multimodal graph approach. The main idea is to formulate the stages, actors, victims, and outcomes of cyber attacks as a multimodal graph, where several graphs of various modalities are combined to represent the attributes of the attack. Multimodal graph nodes include cyberattack victims, adversaries, autonomous systems (ASes) use to perpetrate the attacks, and the observed cyber events. To formulate multimodal graphs, single-modality graphs are interconnected according to their interaction during the cyber attack. Once the graph model is constructed, we apply community and centrality analysis to obtain in-depth insights into the attack. In community analysis, we cluster those multimodal graph nodes that exhibit “strong” inter-modal ties. We further use centrality to rank the graph nodes according to their importance in the attack. By classifying nodes according to centrality, we can deduce the progression of the attack from the attacker nodes to the targeted nodes. Using these results, we apply our methods to two popular case studies, namely GhostNet and Putter Panda and demonstrate a clear distinction in the attack stages. http://www2.engr.arizona.edu/~nghose/GHOSE_SpringSim19.pdf
• Salama, A. M., Li, M., Lazos, L., Krunz, M. M., & Xiao, Y. (2019). Trading Privacy for Utility in Database-assisted Dynamic Spectrum Access. IEEE Transactions on Cognitive Communications and Networking, 14. doi:10.1109/TCCN.2019.2919731
• Ghose, N., Hu, B., Zhang, Y., & Lazos, L. (2018). Secure Physical Layer Voting. IEEE Transactions on Mobile Computing, 17(3), 688-702.
• Zhang, Y., & Lazos, L. (2018). Misbehavior in Multi-channel MAC Protocols. IEEE Transactions on Dependable and Secure Computing (TDSC), 1-14. doi:10.1109/TDSC.2018.2819170
• A., P., Lazos, L., & Krunz, M. (2017). Traffic Decorrelation Techniques for Countering Colluding Eavesdroppers in WSNs. IEEE Transactions on Mobile Computing, 16(3), 857-874. doi:10.1109/TMC.2016.2573304
• Zhang, Y., Lazos, L., Chen, K., Hu, B., & Shivaramaiah, S. (2017). Multi-channel Medium Access Without Control Channels: A Full Duplex MAC Design. IEEE Transactions on Mobile Computing, 16(4), 1032-1046. doi:10.1109/TMC.2016.2582170
• Zhang, Y., Lazos, L., & Kozma, W. (2016). AMD: Audit-based Misbehavior Detection in Wireless Ad Hoc Networks. IEEE Transactions on Mobile Computing (TMC), 15(8), 1893 - 1907. doi:10.1109/TMC.2012.257
• Liu, S., Lazos, L., & Krunz, M. (2014). Time-Delayed Broadcasting for Defeating Inside Jammers. IEEE Transactions on Dependable and Secure Computing, 12(3), 351 - 365. doi:10.1109/TDSC.2014.2334308
• Liu, S., Lazos, L., & Krunz, M. (2015). Time-delayed broadcasting for defeating inside jammers. IEEE Transactions on Dependable and Secure Computing, 12(3), 351--365.
• Liu, S., Lazos, L., & Krunz, M. M. (2015). Time-Delayed Broadcasting for Defeating Inside Jammers. IEEE Transactions on Dependable and Secure Computing (TDSC),, 12, 351-365.
• Rahbari, H., Krunz, M. M., & Lazos, L. (2015). Swift Jamming Attack on Frequency Offset Estimation: The Achilles’ Heel of OFDM Systems. IEEE Transactions on Mobile Computing (TMC), 12(3), 351 - 365. doi:10.1109/TMC.2015.2456916
• Zhang, Y., & Lazos, L. (2013). Vulnerabilities of cognitive radio MAC protocols and countermeasures. IEEE Network, 27(3), 40-45.
• Bradonji\'c, M., & Lazos, L. (2012). Graph-based Criteria for Spectrum-aware Clustering in Cognitive Radio Networks. Ad Hoc Networks, 10(1), 75 - 94.
• Liu, S., Lazos, L., & Krunz, M. (2012). Cluster-Based Control Channel Allocation in Opportunistic Cognitive Radio Networks. IEEE Transactions on Mobile Computing, 11(10), 1436 -1449.
• Liu, S., Lazos, L., & Krunz, M. (2012). Thwarting Control-Channel Jamming Attacks from Inside Jammers. IEEE Transactions on Mobile Computing, 11(9), 1545 -1558.
• Proano, A., & Lazos, L. (2012). Packet Hiding Methods for Preventing Selective jamming Attacks. IEEE Transactions on Dependable and Secure Computing, 9(1), 101 -114.

Proceedings Publications

• Han, X., Samy, I., & Lazos, L. (2020, Spring 2020). Energy-efficient LTE/Wi-Fi Coexistence. In IEEE International Conference on Communications (IEEE ICC), 1-7.
• Salama, A. M., Li, M., Lazos, L., Xiao, Y., & Krunz, M. (2020, Spring 2020). “Privacy-Utility Tradeoff in Dynamic Spectrum Sharing with Non-Cooperative Incumbent Users. In IEEE International Conference on Communications (IEEE ICC), 1-7.
• Breiger, R. L., Breiger, R. L., Rozenblit, J. W., Rozenblit, J. W., Lazos, L., Lazos, L., Ghose, N., Ghose, N., Breiger, R. L., Rozenblit, J. W., Lazos, L., & Ghose, N. (2019, May). Multimodal Graph Analysis of Cyber Attacks. In Society for Modeling & Simulation International (SpringSim 2019), Proceedings of the Annual Simulation Symposium (ANSS '19), 1-12.
  More info

  With the limited information on the cyber-attacks available in an unclassified regime, it is difficult to standardize the analysis of these attacks. In addition, this limitation makes the implementation of this analysis on any future attack challenging. In this work, we address the problem of modeling and analyzing cyber attacks using a multimodal graph approach. The main idea is to formulate the stages, actors, victims, and outcomes of cyber attacks as a multimodal graph, where several graphs of various modalities are combined to represent the attributes of the attack. Multimodal graph nodes include cyberattack victims, adversaries, autonomous systems (ASes) use to perpetrate the attacks, and the observed cyber events. To formulate multimodal graphs, single-modality graphs are interconnected according to their interaction during the cyber attack. Once the graph model is constructed, we apply community and centrality analysis to obtain in-depth insights into the attack. In community analysis, we cluster those multimodal graph nodes that exhibit “strong” inter-modal ties. We further use centrality to rank the graph nodes according to their importance in the attack. By classifying nodes according to centrality, we can deduce the progression of the attack from the attacker nodes to the targeted nodes. Using these results, we apply our methods to two popular case studies, namely GhostNet and Putter Panda and demonstrate a clear distinction in the attack stages. https://dl.acm.org/citation.cfm?id=3338044
• Ghose, N., Lazos, L., Rozenblit, J. W., & Brieger, R. (2019, Spring 2019). Multimodal Graph Analysis of Cyber Attacks. In Proceedings of the SpringSim 2019 Conference, 1-9.
• Lazos, L., Tandon, R., & Samy, I. (2019, July). On the Capacity of Leaky Private Information Retrieval. In IEEE International Symposium on Information Theory (ISIT), Paris, France, July 2019..
• Samy, I., & Lazos, L. (2019, Spring 2019). Optimum Priority Class Selection under Wi-Fi/LTE Coexistence. In IEEE International Conference on Communications (IEEE ICC),, 1-7.
• Samy, I., Tandon, R., & Lazos, L. (2019, Spring 2020). On the Capacity of Leaky Private Information Retrieval. In IEEE International Symposium on Information Theory (IEEE ISIT), 1-6.
• Ghose, N., Lazos, L., & Li, M. (2018, Spring 2018). SFIRE: Secret-Free In-band Trust Establishment for COTS Wireless Devices. In Proceedings of the INFOCOM Conference, 1-9.
• Ghose, N., Lazos, L., & Tandon, R. (2018, Spring 2018). Secure Device Bootstrapping without Secrets Resistant to Signal Manipulation Attacks. In Proceedings of the Security and Privacy Symposium (Oakland, S&P), 1-15.
• Salama, A., Lazos, L., Li, M., Xiao, Y., & Krunz, M. M. (2018, Spring 2018). On the Privacy and Utility Tradeoff in Database-Assisted Dynamic Spectrum Access. In Proceedings of the IEEE International Symposium on Dynamic Spectrum Access Networks (DySpan), 1-10.
• Samy, I., Lazos, L., Xiao, Y., Li, M., & Krunz, M. M. (2018, Spring 2018). LTE Misbehavior Detection in Wi-Fi/LTE Coexistence Under the LAA-LTE Standard. In Proceedings of the 11th ACM Conference on Security and Privacy in Wireless and Mobile Networks (WiSec), 87-98.
• Ghose, N., Hu, B., Zhang, Y., & Lazos, L. (2017, Spring 2018). HELP: Helper-Enabled In-Band Device Pairing Resistant Against Signal Cancellation. In IEEE Transactions on Mobile Computing, 17, 688-702.
• Liu, S., Lysecky, R. L., & Lazos, L. (2017, Spring 2017). FEAL: Fine-Grained Evaluation of Active Learning in Collaborative Learning Spaces. In Proceedings of the 2017 ASEE Annual Conference & Exposition, 1-18.
• Calis, G., Shivaramaiah, S., Koyluoglu, O. O., & Lazos, L. (2016, December/Fall). Threshold-based File Maintenance Strategies for Mobile Cloud Storage Systems. In IEEE IEEE Global Communications Conference (GLOBECOM)., 7.
• Ghose, N., & Lazos, L. (2015, Spring). Verifying ADS-B Navigation Information Through Doppler Shift Measurements (2nd place best graduate student paper award). In 34th IEEE/AIAA Digital Avionics Systems Conference (DASC).
• Hu, B., Zhang, Y., & Lazos, L. (2015, Spring). PHYVOS: Physical Layer Voting for Secure and Fast Cooperation. In IEEE Conference on Communications and Network Security (CNS).
• Fowler, J., Johnson, T., Simonetto, P., Schneider, M., Acedo, C., Kobourov, S., & L., L. (2014). IMap: Visualizing Network Activity over Internet Maps. In Proceedings of the Eleventh Workshop on Visualization for Cyber Security (VIZSEC 2014).
• Johnson, T., & L., L. (2014). Network Anomaly Detection Using Autonomous System Flow Aggregates. In Proceedings of the IEEE Global Communications Conference (GLOBECOM 2014).
• Rahbari, H., Krunz, M., & Lazos, L. (2014). Security Vulnerability and Countermeasures of Frequency Offset Correction in 802.11a Systems. In Proceedings of the 33rd IEEE International Conference on Computer Communications (INFOCOM), 1015 - 1023.
• Y., Z., Lazos, L., Chen, K., Hu, B., & Shivaramaiah, S. (2014). FD-MMAC: Combating Multi-Channel Hidden and Exposed Terminals Using a Single Transceiver. In Proceedings of the 33rd IEEE International Conference on Computer Communications (INFOCOM), 2742 - 2750.
• Zhang, Q., & Lazos, L. (2014). Collusion-Resistant Query Anonymization for Location-Based Services. In Proceedings of the IEEE International Conference on Communications (ICC), 768 - 774.
• Proano, A., & Lazos., L. (2013). Perfect Contextual Information Privacy in WSN under Colluding Eavesdroppers. In Proceedings of the 6th ACM Conference on Security and Privacy in Wireless and Mobile Networks (WiSec), 89-94.
• Zhang, Y., & Lazos, L. (2013). Countering Selfish Misbehavior in Multi-channel MAC Protocols. In Proceedings of the 32nd IEEE International Conference on Computer Communications (INFOCOM), 2787-2795.
• Proano, A., & Lazos, L. (2012). Hiding contextual information in WSNs. In Proceedings of the 2012 IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM), 1-6.

Presentations

• Ghose, N., Lazos, L., Rozenblit, J. W., & Breiger, R. L. (2019, May). Multimodal Graph Analysis of Cyber Attacks. Society for Modeling & Simulation International (SpringSim 2019). Tucson, AZ.
  More info

  With the limited information on the cyber-attacks available in an unclassified regime, it is difficult to standardize the analysis of these attacks. In addition, this limitation makes the implementation of this analysis on any future attack challenging. In this work, we address the problem of modeling and analyzing cyber attacks using a multimodal graph approach. The main idea is to formulate the stages, actors, victims, and outcomes of cyber attacks as a multimodal graph, where several graphs of various modalities are combined to represent the attributes of the attack. Multimodal graph nodes include cyberattack victims, adversaries, autonomous systems (ASes) use to perpetrate the attacks, and the observed cyber events. To formulate multimodal graphs, single-modality graphs are interconnected according to their interaction during the cyber attack. Once the graph model is constructed, we apply community and centrality analysis to obtain in-depth insights into the attack. In community analysis, we cluster those multimodal graph nodes that exhibit “strong” inter-modal ties. We further use centrality to rank the graph nodes according to their importance in the attack. By classifying nodes according to centrality, we can deduce the progression of the attack from the attacker nodes to the targeted nodes. Using these results, we apply our methods to two popular case studies, namely GhostNet and Putter Panda and demonstrate a clear distinction in the attack stages. http://www2.engr.arizona.edu/~nghose/GHOSE_SpringSim19.pdf
• Blowers, P., Burd, G. D., Bolger, M. S., Johns, K. A., Lazos, L., Lysecky, R. L., Milsom, J. A., Novodvorsky, I., Pollard, J. R., Prather, E. E., Talanquer, V. A., Thamvichai, R., Tharp, H. S., Wallace, C. S., Cox, J., Elfring, L., Grubbs, E., & Hunter, J. (2014). Developing Faculty Cultures for Evidence-Based Teaching Practices in STEM: A Progress Report. Transforming Institution: 21st Century STEM Undergraduate Education Conference. Indianapolis, IN: AAU-STEM.
• Blowers, P., Burd, G. D., Bolger, M. S., Johns, K. A., Lazos, L., Lysecky, R. L., Milsom, J. A., Novodvorsky, I., Pollard, J. R., Prather, E. E., Talanquer, V. A., Thamvichai, R., Tharp, H. S., Wallace, C. S., Cox, J., Elfring, L., Grubbs, E., Hunter, J., Blowers, P., , Burd, G. D., et al. (2014, Oct). Developing Faculty Cultures for Evidence-Based Teaching Practices in STEM: A Progress Report. Transforming Institution: 21st Century STEM Undergraduate Education Conference. Indianapolis, IN: AAU-STEM.