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| Jonathan K. Millen retired from his position as senior principal computer scientist in the cybersecurity division of The MITRE Corporation in 2012.
Jon obtained his PhD in mathematics from Rensselaer Polytechnic Institute in 1969; it came a year before RPI established a doctoral degree program in computer science. His initial programming experience was earlier, on Harvard’s UNIVAC II, writing binary machine language instructions on a form that was sent to punched-card machine typists. Working at The MITRE Corporation, in 1970, he was a member of a team that developed a COBOL program to produce Grade 2 Braille output for the MIT Sensory Aids Evaluation and Development Center. He has also used a Symbolics Lisp machine, acquired for MITRE artificial intelligence (AI) projects.
His work in computer security has involved various kinds of formal, symbolic analysis. It began with methods of information flow analysis to detect covert channels in operating system security kernels. These systems were being developed to satisfy government evaluation criteria for high-confidence multilevel security, as specified in the so-called Orange Book published by the National Computer Security Center in 1985. Jon was one of the authors of the subsequent Red Book for network security. During this period, he also developed a symbolic analysis tool to find security vulnerabilities in cryptographic key distribution protocols.
In 1988, Jon founded the Computer Security Foundations Workshop for the IEEE Computer Society. This workshop became the CSF Conference in 2008. He served terms as chair of the IEEE Technical Committee on Security and Privacy, and as general chair of its annual symposium. He cofounded the Journal of Computer Security, in 1991, and was co-editor-in-chief until retirement.
From 1997 to 2004, Jon worked at the SRI International Computer Science Laboratory as a senior computer scientist. It was there that he developed an improved protocol analyzer: the constraint solver. After returning to MITRE in 2004, he joined a team working on analysis of trusted platform modules. He was an editorial board member of ACM Transactions on Information and System Security from 1997 to 2006, and received an ACM SIGSAC Outstanding Innovation award in 2009.
Jon has been a reviewer for Computing Reviews since 1993.
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1 - 10 of 38
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Fifty years of P vs. NP and the possibility of the impossible Fortnow L., Fortnow L. Communications of the ACM 65(1): 76-85, 2021. Type: Article
The P versus NP problem is one of the most fundamental and well-known unresolved questions in computer science. In comparison with the 2009 Communications article by the same author [1], the current survey is less about progress...
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Jun 27 2022 |
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General video game artificial intelligence Pérez Liébana D., Lucas S., Gaina R., Togelius J., Khalifa A., Liu J., Morgan & Claypool, San Rafael, CA, 2020. 192 pp. Type: Book (978-1-681736-46-4)
It’s a jungle out there: exploding asteroids, fire-breathing dragons, and maniacal cultists, among other lethal threats. What and how can you teach newborn babies, somehow fitted with a hero’s body and magical weapo...
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Dec 29 2020 |
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The effects of mixing machine learning and human judgment Vaccaro M., Waldo J. Communications of the ACM 62(11): 104-110, 2019. Type: Article
Automated risk assessment systems are often used in situations that require human judgment. One motivation for doing this is to remove human bias. Even when the automated system has been shown to be more accurate than human assessments...
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Aug 7 2020 |
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A survey of methods for explaining black box models Guidotti R., Monreale A., Ruggieri S., Turini F., Giannotti F., Pedreschi D. ACM Computing Surveys 51(5): 1-42, 2019. Type: Article
Computerized decision support systems have significant social consequences, and yet they are capable of mistakes or bias. Can an autonomous driving system be trusted, for example, when its visual scene recognition was implemented as a ...
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Jan 25 2019 |
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Minimally sufficient conditions for the evolution of social learning and the emergence of non-genetic evolutionary systems Gonzalez M., Watson R., Bullock S. Artificial Life 23(4): 493-517, 2017. Type: Article
Social learning is defined here as the imitation of behaviors exhibited by other members of a population. In a population of humans, we might be talking about memes, or more broadly, culture. The authors mention animal examples such as...
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May 17 2018 |
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The cognitive domain of a glider in the game of life Beer R. Artificial Life 20(2): 183-206, 2014. Type: Article
The term “cognitive domain” is used in a “somewhat unusual and controversial” way (quoting the paper). It is to be interpreted in the context of autopoietic systems, a framework originating in a ...
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Apr 16 2015 |
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A historical examination of the social factors affecting female participation in computing Patitsas E., Craig M., Easterbrook S. ITiCSE 2014 (Proceedings of the 2014 Conference on Innovation & Technology in Computer Science Education, Uppsala, Sweden, Jun 21-25, 2014) 111-116, 2014. Type: Proceedings
Barriers to women in computing have existed at least since Ada Lovelace programmed Babbage’s analytical engine. This brief historical survey, bolstered by 55 references, traces the evolution of women’s opportunities...
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Jan 13 2015 |
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Lessons in learning Smith J. IEEE MultiMedia 20(3): 2-3, 2013. Type: Article
It is a time-honored approach in machine intelligence to study the way humans manage intellectual tasks. In this two-page essay, Smith notes that the way machines learn still differs significantly from how humans and animals learn. He ...
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Apr 14 2014 |
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Superlinear performance in real-time parallel computation Akl S. The Journal of Supercomputing 29(1): 89-111, 2004. Type: Article
In this paper, several examples are presented to debunk the belief, or folk theorem, that the speedup achieved by a parallel algorithm using n processors over a sequential algorithm is at most equal to n
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Oct 19 2004 |
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First experiences using XACML for access control in distributed systems Lorch M., Proctor S., Lepro R., Kafura D., Shah S. XML security (Proceedings of the 2003 ACM workshop on XML security, Fairfax, Virginia, Oct 31, 2003) 25-37, 2003. Type: Proceedings
Extensible Access Control Markup Language (XACML) is a language, defined using Extensible Markup Language (XML), for expressing distributed or loosely federated system access control policies. It has been ratified by the Organization f...
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Aug 12 2004 |
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