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This study reports the results of a meta-analysis of empirical studies on Internet addiction published in academic journals for the period 1996-2006. The analysis showed that previous studies have utilized inconsistent criteria to define Internet addicts, applied recruiting methods that may cause serious sampling bias, and examined data using primarily exploratory rather than confirmatory data analysis techniques to investigate the degree of association rather than causal relationships among variables. Recommendations are provided on how researchers can strengthen this growing field of research.

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Hierarchies arise in the context of access control whenever the user population can be modeled as a set of partially ordered classes (represented as a directed graph). A user with access privileges for a class obtains access to objects stored at that class and all descendant classes in the hierarchy. The problem of key management for such hierarchies then consists of assigning a key to each class in the hierarchy so that keys for descendant classes can be obtained via efficient key derivation. We propose a solution to this problem with the following properties: (1) the space complexity of the public information is the same as that of storing the hierarchy; (2) the private information at a class consists of a single key associated with that class; (3) updates (i.e., revocations and additions) are handled locally in the hierarchy; (4) the scheme is provably secure against collusion; and (5) each node can derive the key of any of its descendant with a number of symmetric-key operations bounded by the length of the path between the nodes. Whereas many previous schemes had some of these properties, ours is the first that satisfies all of them. The security of our scheme is based on pseudorandom functions, without reliance on the Random Oracle Model. Another substantial contribution of this work is that we are able to lower the key derivation time at the expense of modestly increasing the public storage associated with the hierarchy. Insertion of additional, so-called shortcut, edges, allows to lower the key derivation to a small constant number of steps for graphs that are total orders and trees by increasing the total number of edges by a small asymptotic factor such as O (log * n ) for an n -node hierarchy. For more general access hierarchies of dimension d , we use a technique that consists of adding dummy nodes and dimension reduction. The key derivation work for such graphs is then linear in d and the increase in the number of edges is by the factor O (log d − 1 n ) compared to the one-dimensional case. Finally, by making simple modifications to our scheme, we show how to handle extensions proposed by Crampton [2003] of the standard hierarchies to “limited depth” and reverse inheritance.

Recent advances in biometric recognition and the increasing use of biometric data prompt significant privacy challenges associated with the possible misuse, loss or theft, of biometric data. Biometric matching is often performed by two mutually suspicious parties, one of which holds one biometric image while the other owns a possibly large biometric collection. Due to privacy and liability considerations, neither party is willing to share its data. This gives rise to the need to develop secure computation techniques over biometric data where no information is revealed to the parties except the outcome of the comparison or search. To address the problem, in this work we develop and implement the first privacy-preserving identification protocol for iris codes. We also design and implement a secure protocol for fingerprint identification based on FingerCodes with a substantial improvement in the performance compared to existing solutions. We show that new techniques and optimizations employed in this work allow us to achieve particularly efficient protocols suitable for large data sets and obtain notable performance gain compared to the state-of-the-art prior work.

This work treats the problem of designing data-oblivious algorithms for classical and widely used graph problems. A data-oblivious algorithm is defined as having the same sequence of operations regardless of the input data and dataindependent memory accesses. Such algorithms are suitable for secure processing in outsourced and similar environments, which serves as the main motivation for this work. We provide data-oblivious algorithms for breadth-first search, single-source single-destination shortest path, minimum spanning tree, and maximum flow, the asymptotic complexities of which are optimal, or close to optimal, for dense graphs.

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Access hierarchies are useful in many applications and are modeled as a set of access classes organized by a partial order. A user who obtains access to a class in such a hierarchy is entitled to access objects stored at that class, as well as objects stored at its descendant classes. Efficient schemes for this framework assign only one key to a class and use key derivation to permit access to descendant classes. Ideally, the key derivation uses simple primitives such as cryptographic hash computations and modular additions. A straightforward key derivation time is then linear in the length of the path between the user's class and the class of the object that the user wants to access.Recently, work presented in [2] has given an efficient solution that significantly lowers this key derivation time, while using only hash functions and modular additions. Two fastkey-derivation techniques in that paper were given for trees, achieving O(log log n) and O(1) key derivation times, respectively, where n is the number of access classes. The present paper presents efficient key derivation techniques for hierarchies that are not trees, using a scheme that is very different from the above-mentioned paper. The construction we give in the present paper is recursive and uses the onedimensional case solution as its base. It makes a novel use of the notion of the dimension d of an access graph, and provides a solution through which no key derivation requires more than 2d + 1 hash function computations, even for "unbalanced" hierarchies whose depth is linear in their number of access classes n.The significance of this result is strengthened by the fact that many access graphs have a low d value (e.g., trees correspond to the case d = 2). Our scheme has the desirable property (as did [2] for trees) that addition and deletion of edges and nodes in the access hierarchy can be "contained" *