Эпизоды
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Jason Larkin and Daniel Justice come back with Matias Jonsson to give updates on the Quantum Project. The team continues to search for useful NISQ era quantum algorithms! Watch as Matias shares his findings, the team touches on their strategies for research and Justice gets corrected on true nature of the NP-Completeness (or lack thereof) of Shor’s algorithm! (Recorded March 2020)
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Пропущенные эпизоды?
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The ability to augment our abilities by partnering with an AI systems to solve complex problems is very compelling. In this Cyber Talk, SEI researchers Carol Smith, Andrew Mellinger, and Ritwik Gupta discuss the exciting challenges and opportunities for human–machine teaming and artificial intelligence.
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Join us as Tom Longstaff and Rotem Guttman walk through the Software Engineering Institute’s plans for how to advance the science of artificial intelligence engineering. Topics addressed will include both the opportunities expected and challenges foreseen in integrating the promise of AI technology with the needs of the Department of Defense.
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Ritwik Gupta and Elli Kanal explain what ransomware is, what it can do to your computer, and how you can help prevent infections using the concept of cyber hygiene. Ransomware is a type of malware that encrypts the files on a computer, preventing the user from accessing them. The attacker then extorts the user by requesting a ransom in exchange for the key that unlocks the files.
In this Cyber Talk episode, Ritwik Gupta and Elli Kanal explain how ransomware can infect a computer, and they discuss examples of how criminals have targeted single computers as well as large systems to explain what can happen when ransomware infects a system. To prevent ransomware attacks, Gupta and Kanal explain the concept of “cyber hygiene,” which refers to a set of basic practices that users can perform to decrease the risk of getting infected by malware. They stress the importance of developing an awareness for cyber hygiene, especially after the advent of the Internet of things, which has increased the number of devices that are susceptible to infection, including phones, cars, refrigerators, and more. -
Rotem Guttman and Zach Kurtz explain what deepfakes are, how they work, and what kind of content it’s possible to create with current techniques and technology.
The term “deepfake” refers to the use of machine learning to produce content for essays or to modify photos and videos. When it comes to photos and videos, the images are often so realistic that viewers are not able to tell that they are fake. In this Cyber Talk episode, Rotem Guttman and Zach Kurtz explain the kinds of machine learning that people use to create deepfakes, how they work, and what kind of content it’s possible to produce with current technology. Rotem and Zach also cover the techniques people use to create fraudulent content. Such techniques include using an actor to film a video and then replacing the actor’s face with someone else’s, as well as more advanced methods that can reproduce a person’s body movements, voice, speech, and facial expressions to make that person appear to say or do something that he or she did not actually say or do. Finally, they discuss the current limitations of these technologies and techniques, and they forecast advances that might occur in the coming years.
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Tom Longstaff and Grace Lewis discuss how the inclusion of minorities and women in science, technology, engineering, and math (STEM) careers can promote a nation’s progress by increasing its ability to innovate.
The fields of science, technology, engineering, and math (STEM) can contribute to a nation’s progress because they promote innovation and improve many aspects of our lives. However, statistics show there is an imbalance in the workforce because women and minorities are less likely to pursue careers in STEM fields. In this Cyber Talk episode, Tom Longstaff and Grace Lewis discuss how fixing this imbalance can help promote even greater innovation in STEM fields. Grace and Tom examine what true diversity means, and how representation not just in terms of race and gender, but also in terms of culture and backgrounds, can promote different points of view and lead to the discovery of new solutions to problems that STEM researchers are trying to solve. They discuss how to promote diversity by reaching out to students at the right age and involving mentors from underrepresented groups to help break stereotypes about what it means to work in a STEM field. They also explore different kinds of approaches and programs that are effective for schools, universities, and places of work—including FFRDCs like the SEI—to get students interested and involved in STEM fields.
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Today’s airplanes use automation to assist pilots during flights. Airplane computers often take control of navigation, they have the capability of performing landing and takeoff maneuvers, and they can make decisions over many aspects of the flight. As automation continues to expand, however, conflicts can arise if a human pilot needs to take immediate control of an airplane because of an unexpected event, but the computer blocks the pilot from doing so. In this cyber talk episode, Elli Kanal and Mike Philips discuss some of the dangers that can occur during handoff of control between humans and computers. They also discuss how to manage risk during handoffs—especially during unexpected events—to ensure the safe operation of the airplane and its recoverability in the face of a crisis. To address the possibility of better human-computer interaction, they consider a system that uses artificial intelligence to interact with pilots so that they can reach conclusions, make decisions, and help resolve issues more quickly and accurately than pilots or computers could on their own. In addition, they explore design issues that could hamper human-computer interactions.
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Humans have been playing games since pre-historic times. Games has been used throughout history not only for enjoyment, but to build skills in a fun and engaging way. Today’s games are no different. Join us as Tom Longstaff, CTO of the Software Engineering Institute speaks with Rotem Guttman, a cybersecurity and educational gamification researcher on how to design experiences that motivate while they teach.
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Ritwik Gupta and Anusha Sinha discuss SEI work on NetFlow that aims to distinguish human-generated flows from machine-generated flows to identify human actors on networks and potential network threats more easily.
With millions of flows on a given network a day, clustering and labeling them becomes challenging. For analysts to be able to take action on potential network threats, it is critical to label flows as quickly and efficiently as possible—often in near-real time. In this SEI Cyber Talk Episode, Ritwik Gupta and Anusha Sinha discuss SEI work on NetFlow that aims to find the most effective way of clustering flows for determining which are generated by humans and which are generated by machines. The work involves constructing a graph that establishes server IPs as nodes, and then formulates the flow partitioning problem as an instance of max-flow using two super nodes and various similarity metrics between server IPs. Partitioning is then accomplished by finding a minimum cut in the graph. Ritwik and Anusha discuss sparsification of the abstract flow network via spectral similarity of graph Laplacians as a technique for improving the algorithm’s efficiency. The ability to quickly label human-generated flows and machine-generated flows could assist analysts in identifying potential network threats as well as with network profiling efforts.
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Currently, there is an enormous amount of interest in machine learning and artificial intelligence and what these new technologies can create for the present and future. In this SEI Cyber Talk episode, Rotem Guttman and April Galyardt discuss how machine learning fits into the bigger picture of artificial intelligence. They describe some of the current applications for machine learning as well as some of its limitations, including examples of machines reaching unexpected results, producing miscalculations because of contextual changes in the data they analyze, and introducing bias into their calculations. The participants also discuss possible use cases for and changes to machine learning that could occur in the mid to near future, including how machine learning might describe and explain its analyses for users to take appropriate action or to learn why the machine made certain decisions.
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In today’s market, chipmakers design and fabricate chips using supply chains, labor forces, locations, and processes that they don’t always monitor or control as closely as customers with high-security requirements need them to. Without proper security or visibility into how companies fabricate chips, a malicious actor could insert something into the hardware that would provide a way for attackers to target and exploit high-profile organizations that use it. In this SEI Cyber Talk episode, Rotem Guttman and Gabe Somlo discuss the benefits of using open source software and hardware, which can help to prevent such issues because open source products provide visibility into what they contain. Additionally, to give government and commercial organizations confidence that their systems are built correctly, Rotem and Gabe also discuss how they might build a computer on their own to ensure that outside sources have not purposely introduced ways of subverting it.
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In this SEI Cyber Talk episode, Ritwik Gupta, Daniel Justice, and Jason Larkin explain what quantum computing is and how it works, and they discuss the benefits that quantum computing can offer, such as increasing the speed at which computers can solve certain algorithms. In the near term, however, quantum computing is limited because quantum computers still present high error rates. Ritwik, Daniel, and Jason explain how these computers must dedicate some of their architecture to error correction. Given this and other limitations, they discuss the kind of applications that are currently plausible for this technology, such as leveraging quantum chips as co-processors and accelerators for classical computers to speed up certain tasks that the quantum architecture is better equipped to handle. They also discuss possibilities they see for quantum computing in the long term, including improving error correction so that quantum computers can address larger problems, such as Shor’s algorithm.
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For the sake of security and safety, exercise environments where cyber operators train often need to be disconnected from real networks. To make these environments more realistic, the Software Engineering Institute (SEI) developed software that simulates the public Internet to give trainees the sense that they are in a real environment. In this SEI Cyber Talk episode, Rotem Guttman and Gabe Somlo explain how this software works to replicate common websites that users see on the Internet and make them as realistic as possible, which includes the addition of a DNS server infrastructure and making the websites appear as if they are hosted in different geographic locations. Rotem and Gabe also discuss how the software supports less common, but important, use cases like performing cryptocurrency transactions or running onion nodes.
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Recently, the Department of Homeland Security (DHS) released a warning about DNS hijacking and how website owners can protect themselves against it. To explain what DNS hijacking is and how adversaries use it to steal sensitive information, Elli Kanal and Daniel Ruef give a high-level overview of how DNS and network traffic work. They discuss how servers communicate with each other, what kind of information servers send to each other and why, and how adversaries can hijack that information. Finally, Elli and Daniel give some advice about what website owners might do to monitor their websites to make sure that adversaries have not hijacked their DNS.
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In this SEI Cyber Talk, Emerging Technology Center interns Dominick Gurnari and Sandra Sajeev discuss what it’s like to intern at the SEI, a DoD federally funded research and development center. We discuss what’s cool about working in a research lab, what’s not, and how the internship differs from traditional industry internships.
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This SEI Cyber Talk episode explains how inverse reinforcement learning can be effective for teaching agents to perform complex tasks with many states and actions.
Inverse reinforcement learning (IRL) is a formalization of imitation learning, which involves learning a task by observing how it is done. The difference between IRL and simple imitation learning is that, in addition to taking note of the actions and decisions needed to perform a task, IRL also associates those actions with the intrinsic rewards of taking them. By doing so, IRL can teach agents to apply the decisions it makes when performing certain actions to other states that the agent might not yet have observed. The participants in this SEI Cyber Talk episode give an overview of how this learning concept works, and they discuss the potential of using IRL to develop technologies such as self-driving cars as well as some of its limitations.
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This SEI Cyber Talk episode introduces the concept of cyber hygiene, which bears an analogy to the concept of hygiene in the medical profession. Like the practice of washing hands to prevent infections, cyber hygiene addresses simple sets of actions that users can take to help reduce cybersecurity risks. The participants in this Cyber Talk episode discuss what some of those practices are, such as implementing password security protocols, and how organizations can determine which practices to implement. Finally, they discuss the special case of phishing—which is a form of attack that can bypass technical safeguards and exploit people’s weaknesses—and how changes in behavior, understanding, and technology might address this issue.
