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The importance of updating, expanding and improving what is taught in cybersecurity curricula is increasing as the security threat landscape becomes more dangerous, breaches become more frequent, and the number of deployed Internet of Things (IoT) devices, known for their security challenges, grows exponentially. This paper argues that a profile of "T-shaped" skills, which is known to be desirable in many consulting and design professions, is being reflected in the latest manifestations of cybersecurity curriculum design and accreditation. A model of learning that yields "T-shaped" professionals combines the ability to apply knowledge across domains (breadth) with the ability to apply functional and disciplinary skills (depth). We present the design of a junior- or senior-level cybersecurity course in which the horizontal stroke of the "T" (representing breadth) spans knowledge areas that cut across the people, process and technology triad. The vertical stroke of the "T" (representing depth) is provided by two aspects of the course design: first, learning the foundational principles of cybersecurity, including practical examples from cryptography and network security; and second, applying the principles of cybersecurity to a semester project, allowing students to expand the core "T" of the course to satisfy their own passions and interests. Our paper concludes with student and instructor reflections on the implementation of this cybersecurity course, as well as broader implications of the lessons learned after the initial offering of this course.

The article reports that fed up with spam from a computer science conference soliciting papers, Jeremy Stribling and two other graduate students, Dan Aguayo and Max Krohn, at the Massachusetts Institute of Technology in Cambridge, Massachusetts, hit pay dirt by successfully submitting computer-generated gibberish. The technique uses context-free grammar, which rearranges sentences in a way that is grammatically correct but makes no sense. Following media coverage of the prank, the organizers of the World Multiconference on Systemics, Cybernetics and Informatics, to be held this summer in Orlando, Florida, rejected their paper "Rooter: A Methodology for the Typical Unification of Access Points and Redundancy," and refunded the authors' registration fee.

Disease surveillance for hepatitis C in the United States is limited by the occult nature of many of these infections, the large volume of cases, and limited public health resources. Through a series of discrete processes, the Massachusetts Department of Public Health modified its surveillance system in an attempt to improve timeliness and completeness of reporting and case follow-up of hepatitis C. These processes included clinician-based reporting, electronic laboratory reporting, deployment of a Web-based disease surveillance system, automated triage of pertinent data, and automated character recognition software for case-report processing. These changes have resulted in an increase in the timeliness of reporting. [ABSTRACT FROM AUTHOR]

Background: Gaps in disease surveillance capacity, particularly for emerging infections and bioterrorist attack, highlight a need for efficient, real time identification of diseases.Methods: We studied automated records from 1996 through 1999 of approximately 250,000 health plan members in greater Boston.Results: We identified 152,435 lower respiratory infection illness visits, comprising 106,670 episodes during 1,143,208 person-years. Three diagnoses, cough (ICD9CM 786.2), pneumonia not otherwise specified (ICD9CM 486) and acute bronchitis (ICD9CM 466.0) accounted for 91% of these visits, with expected age and sex distributions. Variation of weekly occurrences corresponded closely to national pneumonia and influenza mortality data. There was substantial variation in geographic location of the cases.Conclusion: This information complements existing surveillance programs by assessing the large majority of episodes of illness for which no etiologic agents are identified. Additional advantages include: a) sensitivity, uniformity and efficiency, since detection of events does not depend on clinicians' to actively report diagnoses, b) timeliness, the data are available within a day of the clinical event; and c) ease of integration into automated surveillance systems. These features facilitate early detection of conditions of public health importance, including regularly occurring events like seasonal respiratory illness, as well as unusual occurrences, such as a bioterrorist attack that first manifests as respiratory symptoms. These methods should also be applicable to other infectious and non-infectious conditions. Knowledge of disease patterns in real time may also help clinicians to manage patients, and assist health plan administrators in allocating resources efficiently. [ABSTRACT FROM AUTHOR]