Create and release your Profile on Zintellect – Postdoctoral applicants must create an account and complete a profile in the on-line application system. Please note: your resume/CV may not exceed 2 pages.
Complete your application – Enter the rest of the information required for the IC Postdoc Program Research Opportunity. The application itself contains detailed instructions for each one of these components: availability, citizenship, transcripts, dissertation abstract, publication and presentation plan, and information about your Research Advisor co-applicant.
Additional information about the IC Postdoctoral Research Fellowship Program is available on the program website located at: https://orise.orau.gov/icpostdoc/index.html.
If you have questions, send an email to ICPostdoc@orau.org. Please include the reference code for this opportunity in your email.
Research Topic Description, including Problem Statement:
Data, and the insights analysts obtain from it, are crucial for IC agencies to perform their mission. The volume and variety of data are increasing, and they are interconnected so that insights are obtained from the combination of data from many sources. Data classification is traditionally based on the content of the data, although context and metadata may also have an impact on its sensitivity. Typically, classification of the data is based on the potential impact on the national interest, organizations, or individuals if the data is compromised. Classifications range from no business impact for unclassified data to catastrophic impact for top secret data. In some cases, appropriate classification of data is straightforward because either the nature of the data or the way in which it had been collected clearly indicate its level of sensitivity. Increasingly, organizations in the IC are drawing on a variety of data derived from unclassified or low classification sources. In this case, the level of sensitivity of the derived data is not clear, particularly when it is composed of a range of data-types including structured, unstructured, and multimedia data.
The classification level of data has substantial implications for its ability to be shared and analyzed or combined with data from other sources, which can limit its usefulness and the ability of IC agencies to partner with other agencies, industry, or academia. At present the risk-based guidelines do not provide clear guidance on the sensitivity of derived collections of disparate data. Hence, the goal of this project is to use mathematical and statistical principles to establish a framework for classifying disparate collections of security relevant data based on its importance, value, or sensitivity, taking into consideration the need to maximize the availability and usefulness of the data.
Example Approaches:
Graph networks are widely used for social network analysis. When applied to entities extracted from text-based data, for example, they can help to quantify the amount of information within a given dataset, providing guidelines for the scope of potential damage if different types or quantities of data are compromised. There are already many publicly available datasets that can be used to test these methods and develop principles for the potential impact of a data breach. An important aspect of this work will be to identify the type and extent of damage and to relate that back to statistical properties and characteristics of the data.
Machine learning (ML) and artificial intelligence (AI) can be used to classify the content of data collection into relevant groupings and to identify outliers and anomalies. These methods show substantial promise for analyzing aggregated datasets of disparate data to find the sensitive information they may contain. Applying these methods to disparate collections of data will help quantify the level of risk associated with these collections and inform the appropriate classification of the data.
Historic data breaches and unauthorized disclosures provide an opportunity to evaluate the amount of damage that can be attributed to a given volume and type of data. Methods for evaluating identification of sensitive information stemming for privacy research, as well as methods outlined above, can be allied to these datasets to quantify the probability and extent of compromise for a given dataset (which may depend on the type, volume and nature of the data), providing empirical indicators of damage.
An alternative approach could be to consider the potential level of compromise if sensitive attributes were made available at a low classification (for example if shared between agencies or made available to industry partners) with or without context and in either an open or encrypted form as a reference for AI or ML analysis, or for context based searching.
Relevance to the Intelligence Community:
This is an escalating problem for Intelligence Community agencies as there is an increasing need to collaborate across agencies, and with industry and academia. Higher classification of data restricts its availability, usefulness and hence its value. Moreover, the classification of data has an impact on its use for IoT applications, edge technologies and AI. Having a well-defined set of objective principles for classifying disparate collections of security-relevant data would assist in balancing the risks associated with sharing data against the benefits of sharing the data.
Key Words: Information, Classification, Information Security, Data, Classification Standards, Machine Learning, Artificial Intelligence, Prediction, Analytics, Graph Networks
You gave a rating of 0 star(s)
SECURITY/PRIVACY NOTICE
By continuing to use this system you indicate your awareness of and consent to the following terms and conditions of use. LOGOUT IMMEDIATELY if you do not agree to the conditions stated in this warning.
SECURITY NOTICE
This system is part of a Federal information system. This system is monitored for security purposes to ensure it remains available to all users and to protect information in the system. The system employs software programs to monitor network traffic to identify unauthorized activities. By accessing this system, you are expressly consenting to these monitoring activities. Unauthorized attempts to defeat or circumvent security features; to use the system for other than intended purposes; to deny service to authorized users; to access, obtain, alter, damage, or destroy information; to upload or change information; to otherwise cause system or information damage; or otherwise to interfere with the system or its operation, is prohibited. Evidence of such acts may be dis-closed to law enforcement authorities and result in prosecution under the Computer Fraud and Abuse Act of 1986 and the National Information Infrastructure Protection Act of 1996, or other applicable laws.
PRIVACY NOTICE
This system is for authorized use only. Use of this system constitutes consent to security monitoring and testing. All activity is logged with your host name and IP address. Users (authorized or unauthorized) have no explicit or implicit expectation of privacy. Any or all uses of this system and all files on this system may be intercepted, monitored, recorded, copied, audited, inspected, and dis-closed to authorized site and law enforcement personnel, as well as authorized officials of other agencies, both domestic and foreign. By using this system, the user consents to such interception, monitoring, recording, copying, auditing, inspection, and disclosure at the discretion of authorized site or law enforcement personnel. Unauthorized or improper use of this system may result in administrative disciplinary action and civil and criminal penalties.
You have been inactive on this page for . You will be logged out after 03:00:00.
Select an icon below to visit the website and download an appropriate browser.
For help, please email Zintellect@orau.org.
Question: What is the deadline for submitting an application?
Answer: Not all opportunities have application deadlines. Some opportunities remain open until they are filled. If an opportunity has an application deadline, then it will be listed in the opportunity details or in the opportunity catalog.
Question: How do I reset my password?
Answer: If you have forgotten your password or wish to reset your password, use the "Forgot password or username?" tab on the login to reset it.
Question: I forgot my username. How do I retrieve it?
Answer: Use the "Forgot password or username?" tab on the login. You will receive an email containing your username.
Question: What do I need to submit an application?
Answer: Typically, applicants are required to submit a resume or CV, an official copy of their transcripts or academic record, and a minimum of two references at the time they apply. Additional requirements such as a writing sample, thesis or dissertation, etc. may be required. Review the opportunity details for additional information about the requirements for applying for an opportunity.
Question: Where do I upload my transcripts?
Answer: If required, you will be asked to upload your transcript as a part of the application process.
Question: Where do I submit a writing sample?
Answer: If required, you will be asked to upload a writing sample as part of the application process.
Question: Can a family member serve as a reference?
Answer: No; family members may not serve as references. References must be able to speak to your educational and/or professional experience. At least one academic reference is preferred.
Our Zintellect A.I. is constantly learning how to Match you to our opportunities! So, we want to know when we get it right or when we get it wrong. This will help us make our better! Plus, as a potential applicant to one of our many opportunities across the country, we value you and want to help you on your career path!
