77 research outputs found

    Generating social capital in first-generation students through a first-year seminar at a midwest university

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    Graduating college is an important milestone, but, for first-generation students (FGS), this can be more of a challenge than continuing-generation students. First-year seminars (FYS) aim to integrate students academically and socially to university life. The literature has not measured how social capital may differ based on parental education or in different types of FYS. No evidence was found for considering FGS-none (students where neither parent has had any education beyond high school) and FGS-some (students where at least one parent has had some education beyond high school, but did not complete a four-year degree) distinct populations. Social capital at the end of the semester for FGS-none was significantly smaller than continuing-generation students. There were significant increases in total social capital for FGS-none and continuing-generation students but not FGS-some. Factor analysis revealed five dimensions of social capital in the survey instrument: advisor, faculty, institutional, family, and peer. All FGS groups increased advisor social capital; FGS-some and continuing-generation students increased faculty social capital; FGS-some increased peer social capital; and continuing-generation students increased institutional social capital.Includes bibliographical reference

    Ouachita Office of Communications staff earn IABC Awards of Excellence

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    Ouachita Baptist University’s Office of Communications staff was honored with three Bronze Quill Awards of Excellence during the recent Bronze Quill Awards Ceremony hosted by the Arkansas chapter of the International Association of Business Communications

    Assumptions and guarantees for compositional noninterference

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    The idea of building secure systems by plugging together "secure" components is appealing, but this requires a definition of security which, in addition to taking care of top-level security goals, is strengthened appropriately in order to be compositional. This approach has been previously studied for information-flow security of shared-variable concurrent programs, but the price for compositionality is very high: a thread must be extremely pessimistic about what an environment might do with shared resources. This pessimism leads to many intuitively secure threads being labelled as insecure. Since in practice it is only meaningful to compose threads which follow an agreed protocol for data access, we take advantage of this to develop a more liberal compositional security condition. The idea is to give the security definition access to the intended pattern of data usage, as expressed by assumption-guarantee style conditions associated with each thread. We illustrate the improved precision by developing the first flow-sensitive security type system that provably enforces a noninterference-like property for concurrent programs. \ua9 2011 IEEE

    Compositional and Scheduler-Independent Information Flow Security

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    Software pervades our society deeper with every year. This trend makes software security more and more important. For instance, software systems running critical infrastructures like power plants must withstand criminal or even terrorist attacks, but also smartphone apps used by consumers in their daily routine are usually expected to operate securely. In particular, before entrusting a program with confidential information (such as, e.g., image or audio data recorded by a smartphone), one wants to be sure that the program is trustworthy and does not leak the secrets to untrusted sinks (such as, e.g., an untrusted server on the Internet). Information flow properties characterize such confidentiality requirements by restricting the flow of confidential information, and an information flow analysis permits to check that a program respects those restrictions. The problem of information flow in multi-threaded programs is particularly challenging, because information flows can originate in subtle ways from the interplay between threads. Moreover, the existence of such information flows depends on the scheduler, which might not even be known when analyzing a program. To obtain high assurance that no leak is overlooked in an information flow analysis, formally well-founded analyses provide a rigorous solution. Such analyses are proven sound with respect to formal information flow properties that specify precisely what restrictions on information flow mean. In this thesis, we develop two novel information flow properties for multi-threaded programs, FSI-security and SIFUM-security. These properties are scheduler-independent, i.e., they characterize secure information flow for different schedulers simultaneously. Moreover, they are compositional, i.e., they permit to break down the analysis of a multi-threaded program to single threads. For both properties we develop a security analysis based on a security type system that is proven sound with respect to the property. Compared to existing scheduler-independent information flow properties, FSI-security is less restrictive. In particular, FSI-security is the first scheduler-independent information flow property that permits programs with nondeterministic behavior and programs whose control flow depends on secrets. The security analysis based on SIFUM-security is the first provably sound flow-sensitive information flow analysis for multi-threaded programs in the form of a security type system. Flow-sensitivity results in increased analysis precision by taking the order of program statements into account. The key in our development of SIFUM-security and the corresponding flow-sensitive analysis for multi-threaded programs was to adopt assumption-guarantee style reasoning to information flow security. We integrate FSI-security and SIFUM-security into the novel property FSIFUM-security, and we integrate the security analyses for FSI- and SIFUM-security into a security analysis for FSIFUM-security. Thereby, FSIFUM-security and the corresponding analysis inherit the advantages of both FSI- and SIFUM-security. In addition to developing novel type-based information flow analyses we also explore information flow analysis for multi-threaded programs with program dependence graphs (PDGs) which is used successfully to analyze sequential programs. To this end, we develop a formal connection between PDG-based and type-based information flow analysis for sequential programs. We exploit the connection to transfer concepts from our type-based analysis for multi-threaded programs to PDGs, resulting in a provably sound PDG-based information flow analysis for multi-threaded programs. Beyond this, we also use the connection to transfer concepts from PDGs to type systems and to precisely compare the precision of a type-based and a PDG-based information flow analysis. Our results provide foundations for more precise and more widely applicable information flow analysis for multi-threaded programs, and we hope that they contribute to a more wide-spread certification of information flow security for concurrent programs

    Generating Social Capital in First-Generation Students Through a First-Year Seminar at a Midwest University

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    Graduating college is an important milestone, but, for first-generation students (FGS), this can be more of a challenge than continuing-generation students. First-year seminars (FYS) aim to integrate students academically and socially to university life. The literature has not measured how social capital may differ based on parental education or in different types of FYS. No evidence was found for considering FGS-none (students where neither parent has had any education beyond high school) and FGS-some (students where at least one parent has had some education beyond high school, but did not complete a four-year degree) distinct populations. Social capital at the end of the semester for FGS-none was significantly smaller than continuing-generation students. There were significant increases in total social capital for FGS-none and continuing-generation students but not FGS-some. Factor analysis revealed five dimensions of social capital in the survey instrument: advisor, faculty, institutional, family, and peer. All FGS groups increased advisor social capital; FGS-some and continuing-generation students increased faculty social capital; FGS-some increased peer social capital; and continuing-generation students increased institutional social capital
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