Khoury Home
Our faculty members are acknowledged leaders in their fields. They supervise up-and-coming PhD students poised to contribute knowledge and solutions to compelling problems. Together they represent an unusually deep, broad range of expertise.
View a broad sample of research papers (PDF) published by institute faculty.
Our faculty members are acknowledged leaders in their fields. They supervise up-and-coming PhD students poised to contribute knowledge and solutions to compelling problems. Together they represent an unusually deep, broad range of expertise.
View a broad sample of research papers (PDF) published by institute faculty.
Our faculty members are acknowledged leaders in their fields. They supervise up-and-coming PhD students poised to contribute knowledge and solutions to compelling problems. Together they represent an unusually deep, broad range of expertise.
View a broad sample of research papers (PDF) published by institute faculty.
Our faculty members are acknowledged leaders in their fields. They supervise up-and-coming PhD students poised to contribute knowledge and solutions to compelling problems. Together they represent an unusually deep, broad range of expertise.
View a broad sample of research papers (PDF) published by institute faculty.
Daniel Wichs
This project studies how users can securely store encrypted and authenticated data in the cloud in a way that allows the cloud to perform useful computations involving this data without users having to sacrifice security. This work includes designing new cryptosystems such as fully homomorphic encryption and fully homomorphic signatures that enable computation over cryptographically protected data.
Funding: National Science Foundation
Cristina Nita-Rotaru
Software-defined infrastructure (SDI) is a paradigm where the configuration and management of the infrastructure are controlled through software with limited (or no) manual intervention. It generalizes the concept of software-defined networking (SDN) to include application requirements from the infrastructure. Security is critical for SDI given the automated nature of its management and the numerous vulnerabilities introduced by many implementations. This project focuses on understanding the full spectrum of security and fault-tolerance requirements in SDI and propose practical solutions.
This project is a collaboration with MIT Lincoln Labs.
Christo Wilson
A main objective for the European Commission, the executive body of the European Union, is to promote the Digital Single Market, a strategy that aims to make e-commerce and digital goods priced fairly and available to all citizens of the European Union, regardless of a person’s country of origin. In a funded partnership with the commission, this project investigated price discrimination in theme-park tickets, work that led to an enforcement action against Euro Disney and e-books. This partnership is related to work on algorithm auditing.
Funding: National Science Foundation
Jonathan Ullman
Co PI: Abhi Shelat
How can society learn facts about our collective behavior without revealing sensitive information about the behavior of any single individual? Differential privacy is an emerging technology for addressing this question. Existing differentially private implementations either assume the data is held by a trusted central party, or work in a highly restrictive local privacy model. This project aims to develop secure computation techniques for analyzing distributed datasets using differentially private algorithms. We are approaching this challenge in two ways: through a case study of the actual challenges experienced by a web-browser software company, and through a broader technical examination of how to use secure computation techniques in data-collection tasks in order to offer stronger user-privacy guarantees.
Guevara Noubir
Side-channel and cover-channel attack can enable an adversary to track users and ex-filtrate sensitive information from mobile, wearable, and IoT devices. Our goal is to understand their potential, and to mitigate them.
Funding: Google Faculty Research Award
David Choffnes
ReCon uses machine learning and automatically identifies when personal or other sensitive information leaks to other parties in network traffic from mobile devices, apps, and IoT devices. It not only allows individuals and enterprises to detect such leaks, but also to block or modify them.
Project homepage
Mon(IoT)r Research Group
Funding: Department of Homeland Security, Data Transparency Lab
Long Lu
An ongoing evolution in the design of mobile applications (apps) and services, called “app-as-a-platform”, is posing fundamental challenges to mobile security and privacy, exposing consumers, enterprises, and governments to new threats. Existing security technologies were not designed to address apps’ emerging role as micro-platforms and are, therefore, incapable of providing sufficient protections. This research project is developing security foundations in three dimensions of app-as-a-platform architectures: (1) In-app Dimension, where modules within the same app can adversely affect or manipulate one another, (2) App-cloud Dimension, where apps may spy on or abuse integrated cloud services, and vice versa, and (3) App-IoT Dimension, where unauthorized apps can manipulate IoT (Internet-of-Things)-connected devices.
Funding: National Science Foundation
Alina Oprea
As organizations collect increasingly large amounts of security logs, this data can be used proactively for breach prevention and mitigation. Security analytics is defined as the applications of machine learning and data mining in cyber security.This project researches new techniques to extract meaningful intelligence from different data sources, and detect security-related anomalies with high accuracy and low false positive rates. Of particular interest are stealthy attacks such as advanced persistent threats (APTs) and insider threats difficult to detect in general with existing technologies. We are designing analytics-based security services within an organization perimeter that complement existing defenses by analyzing large amounts of security logs in real-time and generating prioritized alerts of suspicious activities.
Abhi Shelat
This project aims to design and fabricate verifiable hardware: application-specific integrated circuits that provide proofs of their correctness for every input-output computation they perform in the field. These proofs must be efficiently verifiable in less time and energy than it takes to re-execute the computation itself.
Building upon exciting recent theoretical and practical advances in verifiable outsourced computation for the cloud, this project is developing new techniques that exploit the unique constraints and adversary models that relate to the verifiable hardware problem. In addition, the project is also devising new practical approaches to the problem of general verifiable computation.
Funding: National Science Foundation
Guevara Noubir
This project aims to comprehensively investigate the resiliency of Wi-Fi networks to smart attacks, and to design and implement robust solutions capable of resisting or countering them. The project additionally focuses on harnessing new capabilities of Wi-Fi radios, such as multiple-input and multiple-output (MIMO) antennas, to protect against powerful adversaries.
Wi-Fi has emerged as the technology of choice for Internet access. Thus, virtually every smartphone or tablet is now equipped with a Wi-Fi card. Concurrently, and as a means to maximize spectral efficiency, Wi-Fi radios are becoming increasingly complex and sensitive to wireless channel conditions. The prevalence of Wi-Fi networks, along with their adaptive behaviors, makes them an ideal target for denial of service attacks at a large, infrastructure level.
This project aims to comprehensively investigate the resiliency of Wi-Fi networks to smart attacks, and to design and implement robust solutions capable of resisting or countering them. The project additionally focuses on harnessing new capabilities of Wi-Fi radios, such as multiple-input and multiple-output (MIMO) antennas, to protect against powerful adversaries. The research blends theory with experimentation and prototyping, and spans a range of disciplines including protocol design and analysis, coding and modulation, on-line algorithms, queuing theory, and emergent behaviors.
The anticipated benefits of the project include: (1) a deep understanding of threats facing Wi-Fi along several dimensions, via experiments and analysis; (2) a set of mitigation techniques and algorithms to strengthen existing Wi-Fi networks and emerging standards; (3) implementation into open-source software that can be deployed on wireless network cards and access points; (4) security training of the next-generation of scientists and engineers involved in radio design and deployment.
Funding: National Science Foundation
Agnes Chan
This project seeks to understand and remedy a persistent shortage of qualified educators in the cybersecurity field. After surveying U.S. Centers of Academic Excellence in Cyber Defense, researchers will take an in-depth look at the results to identify critical needs, constraints, and impediments to the enrollment of professionals in educator-training programs. The project team will recommend strategies and programs for funding agencies, industries, and other stakeholders, with the goal of attracting more cybersecurity professionals to the education mission.
Funding: National Security Agency
Daniel Wichs
This project studies how users can securely store encrypted and authenticated data in the cloud in a way that allows the cloud to perform useful computations involving this data without users having to sacrifice security. This work includes designing new cryptosystems such as fully homomorphic encryption and fully homomorphic signatures that enable computation over cryptographically protected data.
Funding: National Science Foundation
Cristina Nita-Rotaru
Software-defined infrastructure (SDI) is a paradigm where the configuration and management of the infrastructure are controlled through software with limited (or no) manual intervention. It generalizes the concept of software-defined networking (SDN) to include application requirements from the infrastructure. Security is critical for SDI given the automated nature of its management and the numerous vulnerabilities introduced by many implementations. This project focuses on understanding the full spectrum of security and fault-tolerance requirements in SDI and propose practical solutions.
This project is a collaboration with MIT Lincoln Labs.
Christo Wilson
A main objective for the European Commission, the executive body of the European Union, is to promote the Digital Single Market, a strategy that aims to make e-commerce and digital goods priced fairly and available to all citizens of the European Union, regardless of a person’s country of origin. In a funded partnership with the commission, this project investigated price discrimination in theme-park tickets, work that led to an enforcement action against Euro Disney and e-books. This partnership is related to work on algorithm auditing.
Funding: National Science Foundation
Jonathan Ullman
Co PI: Abhi Shelat
How can society learn facts about our collective behavior without revealing sensitive information about the behavior of any single individual? Differential privacy is an emerging technology for addressing this question. Existing differentially private implementations either assume the data is held by a trusted central party, or work in a highly restrictive local privacy model. This project aims to develop secure computation techniques for analyzing distributed datasets using differentially private algorithms. We are approaching this challenge in two ways: through a case study of the actual challenges experienced by a web-browser software company, and through a broader technical examination of how to use secure computation techniques in data-collection tasks in order to offer stronger user-privacy guarantees.
Guevara Noubir
Side-channel and cover-channel attack can enable an adversary to track users and ex-filtrate sensitive information from mobile, wearable, and IoT devices. Our goal is to understand their potential, and to mitigate them.
Funding: Google Faculty Research Award
David Choffnes
ReCon uses machine learning and automatically identifies when personal or other sensitive information leaks to other parties in network traffic from mobile devices, apps, and IoT devices. It not only allows individuals and enterprises to detect such leaks, but also to block or modify them.
Project homepage
Mon(IoT)r Research Group
Funding: Department of Homeland Security, Data Transparency Lab
Long Lu
An ongoing evolution in the design of mobile applications (apps) and services, called “app-as-a-platform”, is posing fundamental challenges to mobile security and privacy, exposing consumers, enterprises, and governments to new threats. Existing security technologies were not designed to address apps’ emerging role as micro-platforms and are, therefore, incapable of providing sufficient protections. This research project is developing security foundations in three dimensions of app-as-a-platform architectures: (1) In-app Dimension, where modules within the same app can adversely affect or manipulate one another, (2) App-cloud Dimension, where apps may spy on or abuse integrated cloud services, and vice versa, and (3) App-IoT Dimension, where unauthorized apps can manipulate IoT (Internet-of-Things)-connected devices.
Funding: National Science Foundation
Alina Oprea
As organizations collect increasingly large amounts of security logs, this data can be used proactively for breach prevention and mitigation. Security analytics is defined as the applications of machine learning and data mining in cyber security.This project researches new techniques to extract meaningful intelligence from different data sources, and detect security-related anomalies with high accuracy and low false positive rates. Of particular interest are stealthy attacks such as advanced persistent threats (APTs) and insider threats difficult to detect in general with existing technologies. We are designing analytics-based security services within an organization perimeter that complement existing defenses by analyzing large amounts of security logs in real-time and generating prioritized alerts of suspicious activities.
Abhi Shelat
This project aims to design and fabricate verifiable hardware: application-specific integrated circuits that provide proofs of their correctness for every input-output computation they perform in the field. These proofs must be efficiently verifiable in less time and energy than it takes to re-execute the computation itself.
Building upon exciting recent theoretical and practical advances in verifiable outsourced computation for the cloud, this project is developing new techniques that exploit the unique constraints and adversary models that relate to the verifiable hardware problem. In addition, the project is also devising new practical approaches to the problem of general verifiable computation.
Funding: National Science Foundation
Guevara Noubir
This project aims to comprehensively investigate the resiliency of Wi-Fi networks to smart attacks, and to design and implement robust solutions capable of resisting or countering them. The project additionally focuses on harnessing new capabilities of Wi-Fi radios, such as multiple-input and multiple-output (MIMO) antennas, to protect against powerful adversaries.
Wi-Fi has emerged as the technology of choice for Internet access. Thus, virtually every smartphone or tablet is now equipped with a Wi-Fi card. Concurrently, and as a means to maximize spectral efficiency, Wi-Fi radios are becoming increasingly complex and sensitive to wireless channel conditions. The prevalence of Wi-Fi networks, along with their adaptive behaviors, makes them an ideal target for denial of service attacks at a large, infrastructure level.
This project aims to comprehensively investigate the resiliency of Wi-Fi networks to smart attacks, and to design and implement robust solutions capable of resisting or countering them. The project additionally focuses on harnessing new capabilities of Wi-Fi radios, such as multiple-input and multiple-output (MIMO) antennas, to protect against powerful adversaries. The research blends theory with experimentation and prototyping, and spans a range of disciplines including protocol design and analysis, coding and modulation, on-line algorithms, queuing theory, and emergent behaviors.
The anticipated benefits of the project include: (1) a deep understanding of threats facing Wi-Fi along several dimensions, via experiments and analysis; (2) a set of mitigation techniques and algorithms to strengthen existing Wi-Fi networks and emerging standards; (3) implementation into open-source software that can be deployed on wireless network cards and access points; (4) security training of the next-generation of scientists and engineers involved in radio design and deployment.
Funding: National Science Foundation
Agnes Chan
This project seeks to understand and remedy a persistent shortage of qualified educators in the cybersecurity field. After surveying U.S. Centers of Academic Excellence in Cyber Defense, researchers will take an in-depth look at the results to identify critical needs, constraints, and impediments to the enrollment of professionals in educator-training programs. The project team will recommend strategies and programs for funding agencies, industries, and other stakeholders, with the goal of attracting more cybersecurity professionals to the education mission.
Funding: National Security Agency
Daniel Wichs
This project studies how users can securely store encrypted and authenticated data in the cloud in a way that allows the cloud to perform useful computations involving this data without users having to sacrifice security. This work includes designing new cryptosystems such as fully homomorphic encryption and fully homomorphic signatures that enable computation over cryptographically protected data.
Funding: National Science Foundation
Cristina Nita-Rotaru
Software-defined infrastructure (SDI) is a paradigm where the configuration and management of the infrastructure are controlled through software with limited (or no) manual intervention. It generalizes the concept of software-defined networking (SDN) to include application requirements from the infrastructure. Security is critical for SDI given the automated nature of its management and the numerous vulnerabilities introduced by many implementations. This project focuses on understanding the full spectrum of security and fault-tolerance requirements in SDI and propose practical solutions.
This project is a collaboration with MIT Lincoln Labs.
Christo Wilson
A main objective for the European Commission, the executive body of the European Union, is to promote the Digital Single Market, a strategy that aims to make e-commerce and digital goods priced fairly and available to all citizens of the European Union, regardless of a person’s country of origin. In a funded partnership with the commission, this project investigated price discrimination in theme-park tickets, work that led to an enforcement action against Euro Disney and e-books. This partnership is related to work on algorithm auditing.
Funding: National Science Foundation
Jonathan Ullman
Co PI: Abhi Shelat
How can society learn facts about our collective behavior without revealing sensitive information about the behavior of any single individual? Differential privacy is an emerging technology for addressing this question. Existing differentially private implementations either assume the data is held by a trusted central party, or work in a highly restrictive local privacy model. This project aims to develop secure computation techniques for analyzing distributed datasets using differentially private algorithms. We are approaching this challenge in two ways: through a case study of the actual challenges experienced by a web-browser software company, and through a broader technical examination of how to use secure computation techniques in data-collection tasks in order to offer stronger user-privacy guarantees.
Guevara Noubir
Side-channel and cover-channel attack can enable an adversary to track users and ex-filtrate sensitive information from mobile, wearable, and IoT devices. Our goal is to understand their potential, and to mitigate them.
Funding: Google Faculty Research Award
David Choffnes
ReCon uses machine learning and automatically identifies when personal or other sensitive information leaks to other parties in network traffic from mobile devices, apps, and IoT devices. It not only allows individuals and enterprises to detect such leaks, but also to block or modify them.
Project homepage
Mon(IoT)r Research Group
Funding: Department of Homeland Security, Data Transparency Lab
Long Lu
An ongoing evolution in the design of mobile applications (apps) and services, called “app-as-a-platform”, is posing fundamental challenges to mobile security and privacy, exposing consumers, enterprises, and governments to new threats. Existing security technologies were not designed to address apps’ emerging role as micro-platforms and are, therefore, incapable of providing sufficient protections. This research project is developing security foundations in three dimensions of app-as-a-platform architectures: (1) In-app Dimension, where modules within the same app can adversely affect or manipulate one another, (2) App-cloud Dimension, where apps may spy on or abuse integrated cloud services, and vice versa, and (3) App-IoT Dimension, where unauthorized apps can manipulate IoT (Internet-of-Things)-connected devices.
Funding: National Science Foundation
Alina Oprea
As organizations collect increasingly large amounts of security logs, this data can be used proactively for breach prevention and mitigation. Security analytics is defined as the applications of machine learning and data mining in cyber security.This project researches new techniques to extract meaningful intelligence from different data sources, and detect security-related anomalies with high accuracy and low false positive rates. Of particular interest are stealthy attacks such as advanced persistent threats (APTs) and insider threats difficult to detect in general with existing technologies. We are designing analytics-based security services within an organization perimeter that complement existing defenses by analyzing large amounts of security logs in real-time and generating prioritized alerts of suspicious activities.
Abhi Shelat
This project aims to design and fabricate verifiable hardware: application-specific integrated circuits that provide proofs of their correctness for every input-output computation they perform in the field. These proofs must be efficiently verifiable in less time and energy than it takes to re-execute the computation itself.
Building upon exciting recent theoretical and practical advances in verifiable outsourced computation for the cloud, this project is developing new techniques that exploit the unique constraints and adversary models that relate to the verifiable hardware problem. In addition, the project is also devising new practical approaches to the problem of general verifiable computation.
Funding: National Science Foundation
Guevara Noubir
This project aims to comprehensively investigate the resiliency of Wi-Fi networks to smart attacks, and to design and implement robust solutions capable of resisting or countering them. The project additionally focuses on harnessing new capabilities of Wi-Fi radios, such as multiple-input and multiple-output (MIMO) antennas, to protect against powerful adversaries.
Wi-Fi has emerged as the technology of choice for Internet access. Thus, virtually every smartphone or tablet is now equipped with a Wi-Fi card. Concurrently, and as a means to maximize spectral efficiency, Wi-Fi radios are becoming increasingly complex and sensitive to wireless channel conditions. The prevalence of Wi-Fi networks, along with their adaptive behaviors, makes them an ideal target for denial of service attacks at a large, infrastructure level.
This project aims to comprehensively investigate the resiliency of Wi-Fi networks to smart attacks, and to design and implement robust solutions capable of resisting or countering them. The project additionally focuses on harnessing new capabilities of Wi-Fi radios, such as multiple-input and multiple-output (MIMO) antennas, to protect against powerful adversaries. The research blends theory with experimentation and prototyping, and spans a range of disciplines including protocol design and analysis, coding and modulation, on-line algorithms, queuing theory, and emergent behaviors.
The anticipated benefits of the project include: (1) a deep understanding of threats facing Wi-Fi along several dimensions, via experiments and analysis; (2) a set of mitigation techniques and algorithms to strengthen existing Wi-Fi networks and emerging standards; (3) implementation into open-source software that can be deployed on wireless network cards and access points; (4) security training of the next-generation of scientists and engineers involved in radio design and deployment.
Funding: National Science Foundation
Agnes Chan
This project seeks to understand and remedy a persistent shortage of qualified educators in the cybersecurity field. After surveying U.S. Centers of Academic Excellence in Cyber Defense, researchers will take an in-depth look at the results to identify critical needs, constraints, and impediments to the enrollment of professionals in educator-training programs. The project team will recommend strategies and programs for funding agencies, industries, and other stakeholders, with the goal of attracting more cybersecurity professionals to the education mission.
Funding: National Security Agency
Daniel Wichs
This project studies how users can securely store encrypted and authenticated data in the cloud in a way that allows the cloud to perform useful computations involving this data without users having to sacrifice security. This work includes designing new cryptosystems such as fully homomorphic encryption and fully homomorphic signatures that enable computation over cryptographically protected data.
Funding: National Science Foundation
Cristina Nita-Rotaru
Software-defined infrastructure (SDI) is a paradigm where the configuration and management of the infrastructure are controlled through software with limited (or no) manual intervention. It generalizes the concept of software-defined networking (SDN) to include application requirements from the infrastructure. Security is critical for SDI given the automated nature of its management and the numerous vulnerabilities introduced by many implementations. This project focuses on understanding the full spectrum of security and fault-tolerance requirements in SDI and propose practical solutions.
This project is a collaboration with MIT Lincoln Labs.
Christo Wilson
A main objective for the European Commission, the executive body of the European Union, is to promote the Digital Single Market, a strategy that aims to make e-commerce and digital goods priced fairly and available to all citizens of the European Union, regardless of a person’s country of origin. In a funded partnership with the commission, this project investigated price discrimination in theme-park tickets, work that led to an enforcement action against Euro Disney and e-books. This partnership is related to work on algorithm auditing.
Funding: National Science Foundation
Jonathan Ullman
Co PI: Abhi Shelat
How can society learn facts about our collective behavior without revealing sensitive information about the behavior of any single individual? Differential privacy is an emerging technology for addressing this question. Existing differentially private implementations either assume the data is held by a trusted central party, or work in a highly restrictive local privacy model. This project aims to develop secure computation techniques for analyzing distributed datasets using differentially private algorithms. We are approaching this challenge in two ways: through a case study of the actual challenges experienced by a web-browser software company, and through a broader technical examination of how to use secure computation techniques in data-collection tasks in order to offer stronger user-privacy guarantees.
Guevara Noubir
Side-channel and cover-channel attack can enable an adversary to track users and ex-filtrate sensitive information from mobile, wearable, and IoT devices. Our goal is to understand their potential, and to mitigate them.
Funding: Google Faculty Research Award
David Choffnes
ReCon uses machine learning and automatically identifies when personal or other sensitive information leaks to other parties in network traffic from mobile devices, apps, and IoT devices. It not only allows individuals and enterprises to detect such leaks, but also to block or modify them.
Project homepage
Mon(IoT)r Research Group
Funding: Department of Homeland Security, Data Transparency Lab
Long Lu
An ongoing evolution in the design of mobile applications (apps) and services, called “app-as-a-platform”, is posing fundamental challenges to mobile security and privacy, exposing consumers, enterprises, and governments to new threats. Existing security technologies were not designed to address apps’ emerging role as micro-platforms and are, therefore, incapable of providing sufficient protections. This research project is developing security foundations in three dimensions of app-as-a-platform architectures: (1) In-app Dimension, where modules within the same app can adversely affect or manipulate one another, (2) App-cloud Dimension, where apps may spy on or abuse integrated cloud services, and vice versa, and (3) App-IoT Dimension, where unauthorized apps can manipulate IoT (Internet-of-Things)-connected devices.
Funding: National Science Foundation
Alina Oprea
As organizations collect increasingly large amounts of security logs, this data can be used proactively for breach prevention and mitigation. Security analytics is defined as the applications of machine learning and data mining in cyber security.This project researches new techniques to extract meaningful intelligence from different data sources, and detect security-related anomalies with high accuracy and low false positive rates. Of particular interest are stealthy attacks such as advanced persistent threats (APTs) and insider threats difficult to detect in general with existing technologies. We are designing analytics-based security services within an organization perimeter that complement existing defenses by analyzing large amounts of security logs in real-time and generating prioritized alerts of suspicious activities.
Abhi Shelat
This project aims to design and fabricate verifiable hardware: application-specific integrated circuits that provide proofs of their correctness for every input-output computation they perform in the field. These proofs must be efficiently verifiable in less time and energy than it takes to re-execute the computation itself.
Building upon exciting recent theoretical and practical advances in verifiable outsourced computation for the cloud, this project is developing new techniques that exploit the unique constraints and adversary models that relate to the verifiable hardware problem. In addition, the project is also devising new practical approaches to the problem of general verifiable computation.
Funding: National Science Foundation
Guevara Noubir
This project aims to comprehensively investigate the resiliency of Wi-Fi networks to smart attacks, and to design and implement robust solutions capable of resisting or countering them. The project additionally focuses on harnessing new capabilities of Wi-Fi radios, such as multiple-input and multiple-output (MIMO) antennas, to protect against powerful adversaries.
Wi-Fi has emerged as the technology of choice for Internet access. Thus, virtually every smartphone or tablet is now equipped with a Wi-Fi card. Concurrently, and as a means to maximize spectral efficiency, Wi-Fi radios are becoming increasingly complex and sensitive to wireless channel conditions. The prevalence of Wi-Fi networks, along with their adaptive behaviors, makes them an ideal target for denial of service attacks at a large, infrastructure level.
This project aims to comprehensively investigate the resiliency of Wi-Fi networks to smart attacks, and to design and implement robust solutions capable of resisting or countering them. The project additionally focuses on harnessing new capabilities of Wi-Fi radios, such as multiple-input and multiple-output (MIMO) antennas, to protect against powerful adversaries. The research blends theory with experimentation and prototyping, and spans a range of disciplines including protocol design and analysis, coding and modulation, on-line algorithms, queuing theory, and emergent behaviors.
The anticipated benefits of the project include: (1) a deep understanding of threats facing Wi-Fi along several dimensions, via experiments and analysis; (2) a set of mitigation techniques and algorithms to strengthen existing Wi-Fi networks and emerging standards; (3) implementation into open-source software that can be deployed on wireless network cards and access points; (4) security training of the next-generation of scientists and engineers involved in radio design and deployment.
Funding: National Science Foundation
Agnes Chan
This project seeks to understand and remedy a persistent shortage of qualified educators in the cybersecurity field. After surveying U.S. Centers of Academic Excellence in Cyber Defense, researchers will take an in-depth look at the results to identify critical needs, constraints, and impediments to the enrollment of professionals in educator-training programs. The project team will recommend strategies and programs for funding agencies, industries, and other stakeholders, with the goal of attracting more cybersecurity professionals to the education mission.
Funding: National Security Agency
Khoury College of Computer Sciences
440 Huntington Avenue, 202 West Village H
Boston, MA 02115
Khoury College of Computer Sciences
440 Huntington Avenue, 202 West Village H
Boston, MA 02115
Khoury College of Computer Sciences
440 Huntington Avenue, 202 West Village H
Boston, MA 02115
Khoury College of Computer Sciences
440 Huntington Avenue, 202 West Village H
Boston, MA 02115