Visible to the public Biblio

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Li, X., Deng, M., Wang, X., Li, H., Yu, M..  2019.  Synthesis and magnetic properties of Fe-doped CdS nanorods. Micro Nano Letters. 14:275–279.
Hexagonal CdS and Fe-doped CdS nanorods were synthesised by a facile hydrothermal method and characterised by X-ray diffraction, energy dispersive X-ray spectroscopy, UV-vis absorption, photoluminescence, and X-ray photoelectron spectroscopy. The magnetic properties of undoped and Fe-doped CdS nanorods were investigated at room temperature. The experimental results demonstrate that the ferromagnetism of the Fe-doped CdS nanorods differs from that of the undoped CdS nanorods. The remanence magnetisation (Mr) and the coercive field (Hc) of the Fe-doped CdS nanorods were 4.9 × 10-3 emu/g and 270.6 Oe, respectively, while photoluminescence properties were not influenced by doping. First-principle calculations show that the ferromagnetism in Fe-doped CdS nanocrystal arose not only from the Fe dopants but also from the Cd vacancies, although the main contribution was due to the Fe dopants.
Yu, M., Halak, B., Zwolinski, M..  2019.  Using Hardware Performance Counters to Detect Control Hijacking Attacks. 2019 IEEE 4th International Verification and Security Workshop (IVSW). :1–6.

Code reuse techniques can circumvent existing security measures. For example, attacks such as Return Oriented Programming (ROP) use fragments of the existing code base to create an attack. Since this code is already in the system, the Data Execution Prevention methods cannot prevent the execution of this reorganised code. Existing software-based Control Flow Integrity can prevent this attack, but the overhead is enormous. Most of the improved methods utilise reduced granularity in exchange for a small performance overhead. Hardware-based detection also faces the same performance overhead and accuracy issues. Benefit from HPC's large-area loading on modern CPU chips, we propose a detection method based on the monitoring of hardware performance counters, which is a lightweight system-level detection for malicious code execution to solve the restrictions of other software and hardware security measures, and is not as complicated as Control Flow Integrity.

Li, S., Yu, M., Yang, C.-S., Avestimehr, A. S., Kannan, S., Viswanath, P..  2020.  PolyShard: Coded Sharding Achieves Linearly Scaling Efficiency and Security Simultaneously. 2020 IEEE International Symposium on Information Theory (ISIT). :203—208.
Today's blockchain designs suffer from a trilemma claiming that no blockchain system can simultaneously achieve decentralization, security, and performance scalability. For current blockchain systems, as more nodes join the network, the efficiency of the system (computation, communication, and storage) stays constant at best. A leading idea for enabling blockchains to scale efficiency is the notion of sharding: different subsets of nodes handle different portions of the blockchain, thereby reducing the load for each individual node. However, existing sharding proposals achieve efficiency scaling by compromising on trust - corrupting the nodes in a given shard will lead to the permanent loss of the corresponding portion of data. In this paper, we settle the trilemma by demonstrating a new protocol for coded storage and computation in blockchains. In particular, we propose PolyShard: "polynomially coded sharding" scheme that achieves information-theoretic upper bounds on the efficiency of the storage, system throughput, as well as on trust, thus enabling a truly scalable system.
Yu, M., He, T., McDaniel, P., Burke, Q. K..  2020.  Flow Table Security in SDN: Adversarial Reconnaissance and Intelligent Attacks. IEEE INFOCOM 2020 - IEEE Conference on Computer Communications. :1519—1528.

The performance-driven design of SDN architectures leaves many security vulnerabilities, a notable one being the communication bottleneck between the controller and the switches. Functioning as a cache between the controller and the switches, the flow table mitigates this bottleneck by caching flow rules received from the controller at each switch, but is very limited in size due to the high cost and power consumption of the underlying storage medium. It thus presents an easy target for attacks. Observing that many existing defenses are based on simplistic attack models, we develop a model of intelligent attacks that exploit specific cache-like behaviors of the flow table to infer its internal configuration and state, and then design attack parameters accordingly. Our evaluations show that such attacks can accurately expose the internal parameters of the target flow table and cause measurable damage with the minimum effort.