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MU Engineering researchers are trailblazers in cyber security, and are creating bold innovations and fostering student learning experiences as well as community outreach activities. The Cybersecurity Initiative at the University of Missouri (CSI@MU) has a number of affiliated faculty with active collaborations across diverse units that include: engineering, information technology, business, law, medicine, social science and mathematics.

Research Rating

The University of Missouri possesses an R1 Carnegie Classification (Doctoral University: Very high research activity). A link to its 2018 classification can be found here.

The College of Engineering is an NSA Center for Academic Excellence. The National Security Agency (NSA) and the Department of Homeland Security (DHS) jointly sponsor the National Centers of Academic Excellence in Cyber Defense (CAE-CD) program. The goal of the program is to reduce vulnerability in our national information infrastructure by promoting higher education and research in cyber defense and producing professionals with cyber defense expertise.

As a member of the Association of American Universities (AAU), the College of Engineering is on the leading edge of innovation, scholarship, and solutions that contribute to scientific progress, economic development, security, and well-being.

Focusing on research in the US National Interest is a priority for CSI@MU researchers. Several research grants and contracts have been secured for many cyber security projects with US DOD and Intelligence agencies including US Naval Research Laboratory, US Army Research Laboratory and National Security Agency, as well as National Science Foundation and US Department of Energy. CSI@MU faculty and students have a strong publication record in competitive, top conferences and journals in interdisciplinary cyber security (e.g., Journal of Computer Security, ACM Computer and Communications Security, among others).

Research Topics

CSI@MU faculty and students are working on usable cybersecurity in order to systematically study the synergies as well as constraints in balancing resilience (security) and user experience (performance/usability). At MU, projects funded by National Science Foundation are underway to investigate new foundations and architectures for usable cybersecurity by considering the CIA triad (Confidentiality, Integrity and Availability) requirements. Our goal is to advance the state-of- the-art in usable cybersecurity relating to access control, anomaly detection, defense using pretense, and other cyber defense concepts. We particularly focus on the context of cloud-hosted application architectures and services delivery within operational environments of media content providers (e.g., just-in-time news feeds, video streaming, health information sharing, video gaming, social virtual reality).

CSI@MU faculty and students are working on model-checking and formal methods in the automated verification of safety and security of programs/protocols/database solutions. The automated analysis of such computer programs/protocols/database solutions pose difficult challenges that are part of on-going investigations. Our focus is on techniques that employ randomization and our goal is to develop novel practical formal analysis methods that reflect the partial observability on the part of the attacker in order to faithfully analyze such systems safety and security. These projects are funded by National Science Foundation. 

CSI@MU faculty and students are working on the cyber-physical system (CPS) /Internet of Things (IoT) security, and robustness analysis of machine learning (ML) algorithms for Industry 4.0 applications. Industry 4.0 is the latest industrial revolution powered by state-of-the-art ML algorithms and IoT sensors. However, sensors and ML algorithms, both are known for their vulnerabilities to cyber-physical attacks. In the context of such complex CPS, these attacks can have catastrophic consequences as they are hard to detect. Our research focuses on analyzing the robustness of such systems at the design phase, and the detection of cyber-physical attacks at runtime.

CSI@MU faculty and students are working on privacy issues in social networks. In ongoing projects funded by National Science Foundation, investigations are underway to help preserve privacy during online image sharing. Our objective is to design a comprehensive framework namely iPrivacy (image Privacy), which leverages multiple factors to automatically recommend personalized privacy settings for photo sharing, and hence releases users burden and provides better privacy practice. Unlike existing works on privacy recommendation that focus only on the privacy aspect, the iPrivacy system is the first one that seamlessly integrates techniques from two different domains: the image processing and privacy management, to provide a complete policy recommendation system that is automatic, easy to use and efficient in the real social networking environment whereby huge amounts of photos are shared. 

to come from Wei (Wei, Gergei, Rohit)

CSI@MU faculty and students are working on a sound logical representation of complexity-theoretic, probabilistic formulation of security (provable security). Such a representation is amenable to automated verification, and can also be used to find attacks when proving security fails. Efforts are underway to build a library of first-order axioms that express various standard hardness assumptions such as the discrete-logarithm, or Diffie-Hellman assumptions, as well as axioms of standard complexity-theoretic properties of cryptographic primitives, such as security against chosen plaintext or ciphertext attacks. We employ such axioms to verify various properties of protocols, such as secrecy, anonymity, authentication, etc, even of complex ones such as voting protocols. Effectiveness of our approach can be seen from our discovery of new attacks in even simple protocols such as the Needham-Schroeder-Lowe protocol. 

to come from Grant (Grant, Prasad, Dan)

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