This paper presents an access control algorithm which bases on artificial neural network (ANN). It uses selected roles as input vectors. Then, considering role inheritance, the matching roles that may mutual exclude a...
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This paper presents an access control algorithm which bases on artificial neural network (ANN). It uses selected roles as input vectors. Then, considering role inheritance, the matching roles that may mutual exclude are picked as the output vectors to train the role-role ANN. After that, it removes all conflicts from the output of the former ANN and makes them as the new input vectors. And it employs users' final permissions as the output vectors to train the role- permission ANN according to users' current sessions. This algorithm has high efficiency and can assign users various permissions in different session. It need not re-compute trained ANN if we add or delete users in the system without changing the mapping between the roles and permissions. It exploits bit strings to express roles and permissions, which reduces the data transmission and fits for low bandwidth networks.
Multi-objective flowshop scheduling problems have gained wide attention both in practical and academic fields. In this paper, a hybrid multi-objective genetic algorithm is proposed to solve multi-objective no-wait flo...
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Multi-objective flowshop scheduling problems have gained wide attention both in practical and academic fields. In this paper, a hybrid multi-objective genetic algorithm is proposed to solve multi-objective no-wait flowshop scheduling problems with both the makespan and the total flow time minimization. The proposed algorithm makes use of the principle of non-dominated sorting, coupled with the use of elitist solutions strategy. To improve efficiency, two effective multi-objective local search procedures based on objective increment are applied on each chromosome in the archive. Experimental results show that the proposal outperforms the other three heuristics both on effectiveness and efficiency.
No-wait flowshops with flowtime minimization are typical NP-Complete combinatorial optimization problems, widely existing in practical manufacturing systems. Different from traditional methods by which objective of a ...
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No-wait flowshops with flowtime minimization are typical NP-Complete combinatorial optimization problems, widely existing in practical manufacturing systems. Different from traditional methods by which objective of a new schedule being completely computed objective increment methods are presented in this paper by which the objective of an offspring being obtained just by objective increments and computational time can be considerably reduced. HGAI (Hybrid GA based on objective Increment) is proposed by integrating genetic algorithm with a local search method. A heuristic is constructed to generate an individual of initial population and a crossover operator is introduced for mating process. HGAI is compared with two best so far algorithms for the considered problem on 110 benchmark instances. Computational results show that HGAI outperforms the existing two in effectiveness with a little more computation time.
In this paper we propose an efficient Fair Exchange Signature Scheme(FESS) that allows two players to exchange digital signatures in a fair way. It may be considered as an interesting extension of concurrent signature...
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In this paper we propose an efficient Fair Exchange Signature Scheme(FESS) that allows two players to exchange digital signatures in a fair way. It may be considered as an interesting extension of concurrent signature presented in EURO CRYPT 2004 that is constructed from ring signatures. In our scheme, two unwakened signatures signed separately by two participants can be verified easily by the other player, but it would not go into effect until an extra piece of commitment keystone is released by one of the players. Once the keystone revealed, two signatures are both aroused and become effective. A key feature of the proposed scheme is that two players can exchange digital signatures simultaneously through a secret commitment keystone without involvement of any Trusted Third Party. Moreover, the efficiency of our signature scheme is higher than that of concurrent signature.
A multi-participant trust relationship is essential to implement a successful business transaction in DRM (digital rights management)-enabling digital contents industry. The simple adoption of several increasingly enh...
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A multi-participant trust relationship is essential to implement a successful business transaction in DRM (digital rights management)-enabling digital contents industry. The simple adoption of several increasingly enhanced security policies does not necessarily establish the mutual trust relationship ultimately, and even has a negative effect on the usability and acceptability of DRM system. Therefore, various participantspsila benefits should be emphasized in the contents value chain. First, a general DRM contents value chain ecosystem was presented without a loss of generality. Then, a benefits-centric multi-participant trust architecture (abbr. MPTA), which is based on game-theoretic rational adoptions of security policies for participants, was proposed through an anatomy of existing value chain ecosystems. Finally, we formalized the definitions of the security component and service, the security policy and its utility, as well as the Nash equilibriums of the multi-participant game under pure and mixed security policy profile. Due to the introduction to game theory, MPTA enables participants to acquire optimal benefits balance when fundamental security requirements are met, and Nash equilibrium of the game is the chosen security policies combinations from the participantspsila perspectives.
Sensor networks are resource-constrained, which makes developing efficient key distribution scheme a challenging problem. In general, many key distribution techniques are designed to address the trade-off between limi...
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Motivated by a key agreement scheme proposed by Leighton and Micali (LM-KDS), we present a key establishment mechanism for heterogeneous sensor networks which combines random key pre-distribution schemes and LM-KDS. U...
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In order to speed up the propagating process, the worms need to scan many IP addresses to target vulnerable hosts. However, the distribution of IP addresses is highly nonuniform, which results in many scans wasted on ...
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In order to speed up the propagating process, the worms need to scan many IP addresses to target vulnerable hosts. However, the distribution of IP addresses is highly nonuniform, which results in many scans wasted on invulnerable addresses. Inspired by the theory of good point set, this paper proposes a new scanning strategy, referred to as good point set scanning (GPSS), for worms. Experimental results show that GPSS can generate more distinct IP addresses and less unused IP addresses than the permutation scanning. Combined with group distribution, a static optimal GPSS is derived. Since the information can not be easily collected before a worm is released, a self-learning worm with GPSS is designed. Such worm can accurately estimate the underlying vulnerable-host distribution when a sufficient number of IP addresses of infected hosts are collected. We use a modified Analytical Active Worm Propagation (AAWP) to simulate data of Code Red and the performance of different scanning strategies. Experimental results show that once the distribution of vulnerable hosts is accurately estimated, a self- learning worm can propagate much faster than other worms.
In order to ensure the tasks of emergency passage are scheduled first and avoid priority inversion by the switches of system states in CORBA (common object request broker architecture) system, a real-time scheduling s...
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In order to ensure the tasks of emergency passage are scheduled first and avoid priority inversion by the switches of system states in CORBA (common object request broker architecture) system, a real-time scheduling scheme is proposed and analyzed which adopts an adaptive dynamic priority scheduling algorithm. The scheme considers the switches of system states. It also takes account of connection management and thread pool management. Analysis shows that the tasks of emergency passage can take priority over others, and the probability is negligible that inconsistent system states result in low-priority tasks blocking high-priority ones. Besides, tasks of emergency passage will never wait under this algorithm, so their execution is ensured on each node, which meets the needs of application.
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