Research at the Cybersecurity and Privacy Institute
When CPI was founded, four CPI areas of expertise were identified (security, privacy, cryptography, quantum-safe communications). As the initial list was too coarse-grained, we initiated an exercise to refine and revamp the list, with input from CPI members. We began with a draft list and solicited feedback from several senior CPI members, as well as the members of the CPI Faculty Advisory Committee which has representation from every faculty.
The list is intended to be descriptive rather than prescriptive and is used to find the right experts whenever an external partner approaches CPI with a request for proficiency. These nine areas are also indicative of the importance CPI places on addressing global cybersecurity risks, as they encompass a comprehensive and interconnected approach to understanding and proactively addressing the spectrum of cybersecurity and privacy concerns of the global community. Additionally, these areas of expertise expand on the specific fields within which the cybersecurity talent gap exists; illustrating the wide range of interdisciplinary skills required to effectively engage with multi-layered cybersecurity and privacy issues, e.g., implementing surveillance technology in the workplace requires hardware, software, legal, public relations, and ethics skillsets to be effective and responsible.
The Cybersecurity and Privacy Institute (CPI) fosters an interdisciplinary and collaborative approach to research and training in cybersecurity and privacy. Our mandate is to nurture and enhance Canada’s leadership position in cybersecurity and privacy research by partnering with industry to collaborate on these core research areas:
Cryptography
Cryptography
Cryptography is the study of secure communications techniques that allow only the sender and intended recipient of information to view its contents. It provides mathematical and algorithmic tools that are critical for protecting the security of information and communication infrastructures (e.g., the Internet).
Modern cryptography concerns itself with the following four objectives:
- Confidentiality: The information cannot be understood by anyone for whom it was unintended
- Integrity: The information cannot be altered in storage or transit between sender and intended receiver without the alteration being detected
- Non-repudiation: The creator/sender of the information cannot deny at a later stage their intentions in the creation or transmission of the information
- Authentication: The sender and receiver can confirm each other's identity and the origin/destination of the information
Research topics | CPI researchers |
---|---|
Blockchain Blockchain is a type of shared database that differs from a typical database in the way that it stores information; blockchains store data in blocks that are then linked together via cryptography. |
|
Cryptography for Differential Privacy Uses cryptographic primitives to bridge the gap between SDP and LDP. In these solutions, the trusted data curator in SDP is replaced by cryptographic primitives that result in more practical trust assumptions than the SDP model, and better utility than under the LDP model. |
Xi He |
Cryptography for Distributed Systems Cryptography to secure a distributed system, which is a computing environment in which various components are spread across multiple computers (or other computing devices) on a network. These devices s plit up the work, coordinating their efforts to complete the job more efficiently than if a single device had been responsible for the task. |
|
Cryptographic Hardware Cryptographic hardware acceleration is the use of hardware to perform cryptographic operations faster than they can be performed in software. Hardware accelerators are designed for computationally intensive software code. |
|
Foundations of Cryptography Foundations of cryptography are the paradigms, approaches and techniques used to conceptualize, define, and provide solutions to natural Cryptographic problems. |
|
Key Establishment Key establishment is the process by which two (or more) entities establish a shared secret key. Essentially, two methods are used to establish cryptographic keying material between parties: key agreement and key transport. |
|
Internet Security Internet Security consists of a range of security tactics for protecting activities and transactions conducted online over the internet. |
|
Isogeny-based Cryptography Isogeny-based encryption uses the shortest keys of any proposed post-quantum encryption methods, requiring keys roughly the same size as are currently in use. |
David Jao |
Lattice-based Cryptography Lattice-based cryptography is the generic term for constructions of cryptographic primitives that involve lattices, either in the construction itself or in the security proof. Lattice-based constructions are currently important candidates for post-quantum cryptography. Unlike more widely used and known public-key schemes such as the RSA, Diffie-Hellman or elliptic-curve cryptosystems, which could, theoretically, be easily attacked by a quantum computer, some lattice-based constructions appear to be resistant to attack by both classical and quantum computers. |
|
Lightweight Cryptography Lightweight cryptography is an encryption method with a small footprint and/or low computational complexity. It is aimed at expanding the applications of cryptography to constrained devices and the IoT, and its related international standardization and guidelines compilation are currently underway. |
Guang Gong |
Multi-party Computation Multi-party computation is a subfield of cryptography with the goal of creating methods for parties to jointly compute a function over their inputs while keeping those inputs private. Unlike traditional cryptographic tasks, where cryptography assures security and integrity of communication or storage and the adversary is outside the system of participants (an eavesdropper on the sender and receiver), the cryptography in this model protects participants' privacy from each other. |
|
Post-quantum Cryptography Post-quantum cryptography is cryptographic algorithms (usually public-key algorithms) that are thought to be secure against a cryptanalytic attack by a quantum computer. The problem with currently popular algorithms is that their security relies on one of three hard mathematical problems: the integer factorization problem, the discrete logarithm problem, or the elliptic-curve discrete logarithm problem. All of these problems can be easily solved on a sufficiently powerful quantum computer running Shor's algorithm. |
|
Privacy-preserving Machine Learning Privacy-preserving ML is privacy-enhancing techniques concentrated on allowing multiple input parties to collaboratively train ML models without releasing their private data in its original form. |
|
Private Capacity of Quantum Channels Private capacity of quantum channels is a formula for the capacity of a quantum channel for transmitting private classical information is derived. This is shown to be equal to the capacity of the channel for generating a secret key, and neither capacity is enhanced by forward public classical communication. |
Debbie Leung |
Private Information Retrieval In cryptography, a private information retrieval protocol is a protocol that allows a user to retrieve an item from a server in possession of a database without revealing which item is retrieved. |
|
Pseudorandom Bit Generation Pseudorandom bit generation is an algorithm for generating a sequence of numbers whose properties approximate the properties of sequences of random numbers, which are important in practice for their speed in number generation and their reproducibility. Cryptographic applications require the output not to be predictable from earlier outputs, and more elaborate algorithms, which do not inherit the linearity of simpler PRNGs, are needed. |
Guang Gong |
Quantum Cryptanalysis |
Michele Mosca |
Data science - security and privacy
Data Science - Security and Privacy
The field of data science is broad in scope, combining multiple fields, such as: artificial intelligence, statistics and data analysis to clarify and extract value from data and derive actionable insights.
‘Big Data’ is fuelling the digital economy and companies are amassing vast amounts of personal data. The exploitation of this data also carries the risk of exposing this data to unauthorized or at least unwanted entities, including business partners and end users. Furthermore, when collecting data from many sources, data integrity is not necessarily ensured. Services relying on data sources can be misled by malicious modification to data thus new protection mechanisms need to be developed.
Selected illustrative challenges include:
- Secure and private collection and combination of data sources
- Differential privacy in machine learning models and databases
- Secure and private inference
Research topics | CPI Researchers |
---|---|
Reliability of Machine Learning Models |
|
Differential Privacy in Machine Learning Models and Databases Developing provably private mechanisms to query databases, visualize data, compute statistics or train machine learning models that improve the privacy vs. accuracy trade-off over existing approaches. Developing and evaluating efficient systems that implement those mechanisms in important applications. |
|
Privately Linking Data Sources Designing cryptographic protocols that can securely and efficiently link data sources and compute functions over their intersection. Developing and evaluating practical deployments for real-world applications in record linkage or fintech. |
|
Economics of Data Collection and Use Understanding the effects of government intervention and policy on the overall societal welfare of industrial data collection and use. Studying mechanisms, such as data markets, to reconcile commercial data use with citizen’s control of private information. |
Anindya Sen |
Mis-/Disinformation Studying the spread of mis/disinformation related to collective risks (such as climate change and global pandemics), surveillance, and privacy across a wide variety of national contexts and political regimes. Developing measures and probabilistic models that enable us to better understand when, why, and how mis/disinformation impacts political culture, cognition, deliberation, and identities. |
John McLevey |
Human & Societal Aspects of Security and Privacy
Human & societal aspects of security and privacy
The current 'Digital Age' has witnessed an exponential technological development that has enabled individuals to access a wide array of innovative services and goods through the internet and interact with one another through different digital spaces. However, these technological advances have also come with societal costs, such as:
- a loss in individual privacy and the potential for being a victim of cyber-crime
- people being increasingly commodified as data inputs by digital platforms
- the pervasive spread of misinformation and fake news that result in societal polarization and weakened democracies
- massive market power and wealth in the hands of a few large firms
- the emergence of cyber-attacks as significant threats to national security
Selected illustrative challenges include:
- Technology design
- Behavioural choices
- Public policy
Legal and Policy Aspects of Security and Privacy
Legal and policy aspects of security and privacy
Legal and Policy Aspects of Security and Privacy research considers how law and policy shape information environments that relate to cybersecurity and privacy across a range of sectors including health, education, government, consumer, the workplace, and law enforcement. As rapid technological innovations outpace regulatory environments, law and policy research considers how existing law and policy may be insufficient or unfit to facilitate meaningful security and privacy. Researchers under this subtheme also often consider how law and policy are employed as a set of tools to improve the design and delivery of security and privacy.
Selected illustrative challenges include:
- Privacy law and policy reform
- Digital human rights
- Governance and regulations by design
Research topics | CPI Researchers |
---|---|
Supervised Machine-Learning for Legal Applications The application and evaluation of supervised ML for use in electronic discovery in litigation, in the curation of government records, and for systematic reviews in evidence-based medicine. |
Maura Grossman |
Ethical, Legal, and Policy Considerations of Artificial Intelligence and Machine-Learning AI systems & ML apply learning techniques to statistics to find patterns in large sets of data and make predictions based on those patterns. Due to the proliferation of AI in high-risk privacy areas, there is an increased focus to design and govern AI to be accountable, equitable, and transparent. This includes studies on how best to serve these goals in legal and policy contexts. |
|
Understanding the Risks and Regulation of Workplace Surveillance in Canada’s Transition to a Digital Economy Employers & employees require guidance navigating and updating transparent equitable policies related to surveillance technologies for employees. These policies must be informed by best practices that protect employee rights, data security, and equitable treatment. |
Adam Molnar |
Responding to Cyber-threats, Cyberattacks, and The Weaponization of Dis/Mis-information Focusing on response methods to cyberattacks and the weaponization of dis/misinformation, this research seeks to establish the potential consequences of the (mis)use of information in a digital sphere, and the ways in which these malicious acts can be prevented or mitigated. |
|
Large-scale Data Governance and Modern Techniques for |
Plinio Morita |
Maintaining Security, Trust, and Privacy in Health Tech Innovations |
|
Surveillance and Privacy in Urban Governance Surveillance and privacy in urban governance is helpful to governments, allowing them to gather information and exercise control, which is necessary to fulfill their roles factoring many variables such as increased mobility/anonymity in modern life. Conversely, unchecked surveillance can lead to inequality, discrimination, and repression, undermining a democratic society. Research in this area seeks to promote oversight, accountability, and balance. |
Phil Boyle |
Network Security
Network security
Network security research aims at building secure network infrastructures and communication protocols to protect end users’ data, applications, devices, as well as networked assets, from a vast landscape of cyber threats. As businesses increasingly rely on distributed software applications that run across networks, the need for developing holistic solutions that incorporate resource monitoring, access control, threat detection, and attack mitigation capabilities in different operational settings has become a central concern for network administrators.
Selected illustrative challenges include:
- Secure protocols for distributed systems
- Data-driven security automation for software-defined networks
- Security in the era of blockchains
- Mobile and IOT security
Research topics | CPI researchers |
---|---|
Secure Protocols for Distributed Systems Distributed systems are a network of computing devices that share information and workload to increase efficiency, with the application of cryptographic schemes to secure the data that is transmitted throughout a distributed system, such as a healthcare network. |
|
Data-driven Security Automation for Software-defined Networks |
|
Security in the Era of Blockchains |
|
Mobile and IoT Security |
Operational Security Aspects
Operational security aspects
Operational security are the organizational processes deployed to prevent sensitive information from being compromised and seeks to identify threats and activities that could result in critical data being leaked or revealed to a hostile actor. These processes are most effective when fully integrated into all planning and operational processes. It includes five steps:
- critical data identification
- threat analysis
- vulnerability analysis
- risk analysis
- integration of appropriate countermeasures
Selected illustrative challenges include:
Information systems assurance involves review, evaluation, and reporting on the integrity of information systems and the information they produce, focusing on the processes used to develop, operate, change, and control those information systems. Information systems assurance services include diagnostic assessments of the strengths and weaknesses of IT governance, assessments of information systems controls, assessments of compliance with management policies, standards and regulatory requirements, assessments of the effectiveness of information systems development, operation and change, and other assessments designed to provide assurance to a variety of stakeholders about the integrity of information systems and the information they produce.
Research topics | CPI researchers |
---|---|
Operational Continuity of Mission-critical Information Systems Operational continuity of mission critical information systems focuses on designing and assessing mechanisms to ensure the operational continuity of mission-critical information systems through the use of comprehensive controls and effective incident response strategies. |
|
Professional Practice in External/Internal Auditing |
|
Information Systems Control Initiatives |
|
Automated Program Analysis/Testing/Verification Tools |
Meng Xu |
Privacy-Enhancing Technologies
Privacy-enhancing technologies
Privacy-enhancing technologies research is aimed at empowering people to individually control who can gain access to personal information about them, what those with access can do with that information, and with whom those with access can share the information. Many companies and governments have assembled massive amounts of data about individuals, or are placing restrictions on what information individuals can access, which acutely threatens people's privacy and calls for the ongoing development of new and stronger technologies.
Selected illustrative challenges include:
- Provable privacy guarantees
- Censorship circumvention
Research topics | CPI researchers |
---|---|
Differential Privacy |
|
Censorship Circumvention |
|
Privacy for Machine Learning |
|
Cryptography |
|
Social Issues |
|
Mobile Privacy |
Quantum-Safe Communication
Quantum-safe communication
Quantum safe communication, also known as quantum-resistant communication, refers to methods of transmitting information that is secure against the potential future use of quantum computers. These computers, which are still in the early stages of development, have the potential to break many of the conventional encryption methods currently used to protect sensitive data.
This research field is concerned with the development of cryptographic primitives and protocols that can withstand attacks even by large-scale quantum computers.
Selected illustrative challenges include:
- Quantum Key Distribution
- Post-Quantum Cryptography
- Quantum Algorithms and Cryptanalysis
Research topics | CPI researchers |
---|---|
Quantum Information Theory |
|
Quantum Algorithms and Cryptanalysis |
|
Standardization of Post-quantum Cryptography and QKD Standardization of post-quantum cryptography and QKD develop new public-key cryptography standards specifying one or more unclassified, publicly disclosed digital signature, public-key encryption, and key-establishment algorithms that are available worldwide, capable of protecting sensitive government information well into the foreseeable future, including after the advent of quantum computers. |
|
Post-quantum Cryptography |
|
Quantum Key Distribution QKD is a secure communication method for exchanging encryption keys only known between shared parties, using properties found in quantum physics to exchange cryptographic keys in a manner that is provable and provides security. QKD enables two parties to create and share a key which is then used to encrypt and decrypt messages; QKD is the method of distributing the key, not the key or the data exchanged. |
Software, Hardware, and Systems Security
Software, hardware, and systems security
Research efforts are aimed at securing computing devices and the software that runs on them from external cyberattacks. With computing systems being an essential component of every Canadian’s life, especially with millions of devices working from home since 2020, it is increasingly important to secure the hardware and software that they depend on.
Selected illustrative challenges include:
- Vulnerability Detection
- Certifying Security Properties of Systems
- Hardware-assisted Software Protection
Research topics | CPI researchers |
---|---|
Hardware-Assisted Run-Time Protection |
|
Ensuring Security Properties with Custom Type Systems |
|
Memory Safety of Low-Level Code Memory safety bugs are often security issues, memory safe languages are more secure. |
|
Embedded Systems Security |
Sebastian Fischmeister |
Software Security |
|
Mobile/IoT Security |
|
Formal Methods in Security Formal methods are a specific type of mathematically rigorous techniques for the specification, development, and verification of software and hardware systems, in this case, with a security focus. |