978 research outputs found

    List Processing in Real Time on a Serial Computer

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    Key Words and Phrases: real-time, compacting, garbage collection, list processing, virtual memory, file or database management, storage management, storage allocation, LISP, CDR-coding, reference counting. CR Categories: 3.50, 3.60, 373, 3.80, 4.13, 24.32, 433, 4.35, 4.49 This report describes research done at the Artificial Intelligence Laboratory of the Massachusetts Institute of Technology. Support for the laboratory's artificial intelligence research is provided in part by the Advanced Research Projects Agency of the Department of Defense under Office of Naval Research contract N00014-75-C-0522.A real-time list processing system is one in which the time required by each elementary list operation (CONS, CAR, CDR, RPLACA, RPLACD, EQ, and ATOM in LISP) is bounded by a (small) constant. Classical list processing systems such as LISP do not have this property because a call to CONS may invoke the garbage collector which requires time proportional to the number of accessible cells to finish. The space requirement of a classical LISP system with N accessible cells under equilibrium conditions is (1.5+ÎŒ)N or (1+ÎŒ)N, depending upon whether a stack is required for the garbage collector, where ÎŒ>0 is typically less than 2. A list processing system is presented which: 1) is real-time--i.e. T(CONS) is bounded by a constant independent of the number of cells in use; 2) requires space (2+2ÎŒ)N, i.e. not more than twice that of a classical system; 3) runs on a serial computer without a time-sharing clock; 4) handles directed cycles in the data structures; 5) is fast--the average time for each operation is about the same as with normal garbage collection; 6) compacts--minimizes the working set; 7) keeps the free pool in one contiguous block--objects of nonuniform size pose no problem; 8) uses one phase incremental collection--no separate mark, sweep, relocate phases; 9) requires no garbage collector stack; 10) requires no "mark bits", per se; 11) is simple--suitable for microcoded implementation. Extensions of the system to handle a user program stack, compact list representation ("CDR-coding"), arrays of non-uniform size, and hash linking are discussed. CDR-coding is shown to reduce memory requirements for N LISP cells to ≈(I+ÎŒ)N. Our system is also compared with another approach to the real-time storage management problem, reference counting, and reference counting is shown to be neither competitive with our system when speed of allocation is critical, nor compatible, in the sense that a system with both forms of garbage collection is worse than our pure one.MIT Artificial Intelligence Laboratory Department of Defense Advanced Research Projects Agenc

    Oblivion: Mitigating Privacy Leaks by Controlling the Discoverability of Online Information

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    Search engines are the prevalently used tools to collect information about individuals on the Internet. Search results typically comprise a variety of sources that contain personal information -- either intentionally released by the person herself, or unintentionally leaked or published by third parties, often with detrimental effects on the individual's privacy. To grant individuals the ability to regain control over their disseminated personal information, the European Court of Justice recently ruled that EU citizens have a right to be forgotten in the sense that indexing systems, must offer them technical means to request removal of links from search results that point to sources violating their data protection rights. As of now, these technical means consist of a web form that requires a user to manually identify all relevant links upfront and to insert them into the web form, followed by a manual evaluation by employees of the indexing system to assess if the request is eligible and lawful. We propose a universal framework Oblivion to support the automation of the right to be forgotten in a scalable, provable and privacy-preserving manner. First, Oblivion enables a user to automatically find and tag her disseminated personal information using natural language processing and image recognition techniques and file a request in a privacy-preserving manner. Second, Oblivion provides indexing systems with an automated and provable eligibility mechanism, asserting that the author of a request is indeed affected by an online resource. The automated ligibility proof ensures censorship-resistance so that only legitimately affected individuals can request the removal of corresponding links from search results. We have conducted comprehensive evaluations, showing that Oblivion is capable of handling 278 removal requests per second, and is hence suitable for large-scale deployment

    Reflections on the VTP's contributions to science, policymaking and education

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    In the immediate wake of the 2000 presidential election, the Caltech/MIT Voting Technology Project was initiated. The initial and primary concern of the VTP at that moment was to understand the problems that arose in the 2000 American presidential election, in particular with regards to voting technologies, and to develop scientifically-based proposals for reforms and perhaps even to propose new voting technologies. In the past decade, the VTP has moved from that original focus to become an internationally-renown group of researchers who now focus on a broad array of election administration issues

    Encrypted Shared Data Spaces

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    The deployment of Share Data Spaces in open, possibly hostile, environments arises the need of protecting the confidentiality of the data space content. Existing approaches focus on access control mechanisms that protect the data space from untrusted agents. The basic assumption is that the hosts (and their administrators) where the data space is deployed have to be trusted. Encryption schemes can be used to protect the data space content from malicious hosts. However, these schemes do not allow searching on encrypted data. In this paper we present a novel encryption scheme that allows tuple matching on completely encrypted tuples. Since the data space does not need to decrypt tuples to perform the search, tuple confidentiality can be guaranteed even when the data space is deployed on malicious hosts (or an adversary gains access to the host). Our scheme does not require authorised agents to share keys for inserting and retrieving tuples. Each authorised agent can encrypt, decrypt, and search encrypted tuples without having to know other agents’ keys. This is beneficial inasmuch as it simplifies the task of key management. An implementation of an encrypted data space based on this scheme is described and some preliminary performance results are given

    Generation of eigenstates using the phase-estimation algorithm

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    The phase estimation algorithm is so named because it allows the estimation of the eigenvalues associated with an operator. However it has been proposed that the algorithm can also be used to generate eigenstates. Here we extend this proposal for small quantum systems, identifying the conditions under which the phase estimation algorithm can successfully generate eigenstates. We then propose an implementation scheme based on an ion trap quantum computer. This scheme allows us to illustrate two simple examples, one in which the algorithm effectively generates eigenstates, and one in which it does not.Comment: 5 pages, 3 Figures, RevTeX4 Introduction expanded, typos correcte

    Probabilistic Algorithmic Knowledge

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    The framework of algorithmic knowledge assumes that agents use deterministic knowledge algorithms to compute the facts they explicitly know. We extend the framework to allow for randomized knowledge algorithms. We then characterize the information provided by a randomized knowledge algorithm when its answers have some probability of being incorrect. We formalize this information in terms of evidence; a randomized knowledge algorithm returning ``Yes'' to a query about a fact \phi provides evidence for \phi being true. Finally, we discuss the extent to which this evidence can be used as a basis for decisions.Comment: 26 pages. A preliminary version appeared in Proc. 9th Conference on Theoretical Aspects of Rationality and Knowledge (TARK'03

    Learn your opponent's strategy (in polynomial time)!

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    Agents that interact in a distributed environment might increase their utility by behaving optimally given the strategies of the other agents. To do so, agents need to learn about those with whom they share the same world. This paper examines interactions among agents from a game theoretic perspective. In this context, learning has been assumed as a means to reach equilibrium. We analyze the complexity of this learning process. We start with a restricted two-agent model, in which agents are represented by finite automata, and one of the agents plays a fixed strategy. We show that even with this restrictions, the learning process may be exponential in time. We then suggest a criterion of simplicity, that induces a class of automata that are learnable in polynomial time

    Voting: What Has Changed, What Hasn't, & Why: Research Bibliography

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    Since the origins of the Caltech/MIT Voting Technology Project in the fall of 2000, there has been an explosion of research and analysis on election administration and voting technology. As we worked throughout 2012 on our most recent study, Voting: What Has Changed, What Hasn’t, & What Needs Improvement, we found many more research studies. In this research bibliography, we present the research literature that we have found; future revisions of this research bibliography will update this list.Carnegie Corporation of New Yor

    Complexity transitions in global algorithms for sparse linear systems over finite fields

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    We study the computational complexity of a very basic problem, namely that of finding solutions to a very large set of random linear equations in a finite Galois Field modulo q. Using tools from statistical mechanics we are able to identify phase transitions in the structure of the solution space and to connect them to changes in performance of a global algorithm, namely Gaussian elimination. Crossing phase boundaries produces a dramatic increase in memory and CPU requirements necessary to the algorithms. In turn, this causes the saturation of the upper bounds for the running time. We illustrate the results on the specific problem of integer factorization, which is of central interest for deciphering messages encrypted with the RSA cryptosystem.Comment: 23 pages, 8 figure
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