75 research outputs found

    Chaotic Compilation for Encrypted Computing: Obfuscation but Not in Name

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    An `obfuscation' for encrypted computing is quantified exactly here, leading to an argument that security against polynomial-time attacks has been achieved for user data via the deliberately `chaotic' compilation required for security properties in that environment. Encrypted computing is the emerging science and technology of processors that take encrypted inputs to encrypted outputs via encrypted intermediate values (at nearly conventional speeds). The aim is to make user data in general-purpose computing secure against the operator and operating system as potential adversaries. A stumbling block has always been that memory addresses are data and good encryption means the encrypted value varies randomly, and that makes hitting any target in memory problematic without address decryption, yet decryption anywhere on the memory path would open up many easily exploitable vulnerabilities. This paper `solves (chaotic) compilation' for processors without address decryption, covering all of ANSI C while satisfying the required security properties and opening up the field for the standard software tool-chain and infrastructure. That produces the argument referred to above, which may also hold without encryption.Comment: 31 pages. Version update adds "Chaotic" in title and throughout paper, and recasts abstract and Intro and other sections of the text for better access by cryptologists. To the same end it introduces the polynomial time defense argument explicitly in the final section, having now set that denouement out in the abstract and intr

    Safe Compilation for Encrypted Computing

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    Encrypted computing is an emerging field in which inputs, outputs and intermediates are maintained in encrypted form in a processor, conferring security on user data against the operator and operating system as adversaries, which run unencrypted in the same machine. Systems that pass encrypted addresses to memory without decryption close a major attack vector and allow off-the-shelf memory to be used. But that makes memory unreliable from the program\u27s perspective, as the many different encryptions of a plaintext address access different memory locations that the program sees as the same with varying contents. A clever `obfuscating\u27 compiler solves the problem, opening up the field

    Secure application partitioning for intellectual property protection

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    Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2005.Includes bibliographical references (p. 79-83).Intellectual property protection is a major concern for both hardware and software architects today. Recently secure platforms have been proposed to protect the privacy of application code and enforce that an application can only be run or accessed by authorized hosts. Unfortunately, these capabilities incur a sizeable performance overhead. Partitioning an application into secure and insecure regions can help diminish overheads but invalidates guarantees of privacy and access control. This work examines the problem of securely partitioning an application into public and private regions so that private code confidentiality is guaranteed and only authorized hosts can execute the application. This problem must be framed within the context of whole application execution for any solution to have meaning, which is a critical point when evaluating software security. The adversarial model presented balances practical generality with concrete security guarantees, and it is shown that under this model the best attack possible is a Memoization Attack." A practical Memoization Attack is implemented, and experimentation reveals that naive partitioning strategies can expose the functionality of hidden code in real applications, allowing unauthorized execution. To protect against such an attack, a set of indicators are presented that enable an application designer to identify these insecure application code regions. Finally, a partitioning methodology is discussed that uses these indicators to partition an application in a manner that protects the privacy of intellectual property and prohibits unauthorized execution.by Charles W. O'Donnell.S.M

    Autonomic context-dependent architecture for malware detection

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    3rd SC@RUG 2006 proceedings:Student Colloquium 2005-2006

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    3rd SC@RUG 2006 proceedings:Student Colloquium 2005-2006

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    3rd SC@RUG 2006 proceedings:Student Colloquium 2005-2006

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