Software agents

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A Heuristic Approach for Firewall Policy Optimization

A primary goal of this paper is to develop a heuristic approach based on genetic algorithms to enhance the firewall performance. Typical firewall policies may have thousands of rules and determining an optimal rule order that minimizes the average number of rule comparisons while maintaining the policy integrity is proven to be NP-hard. This problem is formulated as a binary integer program for which an optimal solution is obtained using the branch-and-bound technique. Then an alternative solution approach is devised based on genetic algorithms. Several experiments are conducted to evaluate the effectiveness of the proposed approach as compared to other rule-ordering techniques. Empirical results show the potential and flexibility of the proposed approach

A review of network security

book revie

A general look at building applications for mobile devices

book revie

On Optimal Firewall Rule Ordering

In today's online connected world, almost all corporate networks use some form of perimeter firewalls to manage Internet connections and enforce a security policy at the corporate gateway. Although it can considerably enhance network security and protect business-critical information, a firewall with thousands of rules can become a bottleneck for network performance. The primary goal of this paper is to present a new rule order optimizer based on simulated annealing to find optimal configurations that minimize the average number of rule comparisons while preserving precedence relationships among disjoint rules. The proposed approach is evaluated and its effectiveness is compared with another approximate solution under several firewall configurations and policy profiles

CHEMICAL INVESTIGATION OF BAUHINIA VAHLII WIGHT AND ARNOTT LEAVES GROWN IN EGYPT

Objective: Plants of genus Bauhinia are famous for their rich flavonoid content. Several phytochemical and biological investigations affirmed the role of flavonoids in the different biological impacts exerted by Bauhinia plants. The present study aims to investigate the major phytoconstituents of the leaves of B. vahlii Wight and Arnott.Methods: Powdered leaves were extracted with n-hexane (HE) and the defatted marc was extracted with 70% ethanol. The defatted ethanolic extract (DEE) was further partitioned with solvents of increasing polarities. The HE and polar fractions of DEE were purified using different chromatographic techniques and isolated compounds were identified through their melting points, 1D and 2D NMR, UV and MS spectral data.Results: A total of nine compounds were isolated and identified. Taraxerol (1), a pentacyclic triterpene, and β-sitosterol (2) were isolated from HE. Investigation of polar fractions of DEE yielded six flavonoids and a phenolic acid, namely luteolin (3), quercetin (4), gallic acid (5), avicularin (6), quercitrin (7), hyperoside (8) and quercetin-3-O-β-sophoroside (9).Conclusion: Flavonols of the quercetin nucleus were the major detected constituents in B. vahlii leaves. Taraxerol, avicularin and quercetin-3-O-β-sophoroside are isolated for the first time from the genus Bauhinia. Results of this study encourage future pharmacological investigation of B. vahlii due to the presence of biologically active flavonoids and phytosterols.Keywords: Bauhinia vahlii Wight, Arnott., Polar extractives, Flavonols, Quercetin, TaraxerolÂ

A learning approach for prioritized handoff channel allocation in mobile multimedia networks

An efficient channel allocation policy that prioritizes handoffs is an indispensable ingredient in future cellular networks in order to support multimedia traffic while ensuring quality of service requirements (QoS). In this paper we study the application of a reinforcement-learning algorithm to develop an alternative channel allocation scheme in mobile cellular networks that supports multiple heterogeneous traffic classes. The proposed scheme prioritizes handoff call requests over new calls and provides differentiated services for different traffic classes with diverse characteristics and quality of service requirements. Furthermore, it is asymptotically optimal, computationally inexpensive, model-free, and can adapt to changing traffic conditions. Simulations are provided to compare the effectiveness of the proposed algorithm with other known resource-sharing policies such as complete sharing and reservation policies

In Vitro Uptake of 140 kDa Bacillus thuringiensis Nematicidal Crystal Proteins by the Second Stage Juvenile of Meloidogyne hapla

Plant-parasitic nematodes (PPNs) are piercing/sucking pests, which cause severe damage to crops worldwide, and are difficult to control. The cyst and root-knot nematodes (RKN) are sedentary endoparasites that develop specialized multinucleate feeding structures from the plant cells called syncytia or giant cells respectively. Within these structures the nematodes produce feeding tubes, which act as molecular sieves with exclusion limits. For example, Heterodera schachtii is reportedly unable to ingest proteins larger than 28 kDa. However, it is unknown yet what is the molecular exclusion limit of the Meloidogyne hapla. Several types of Bacillus thuringiensis crystal proteins showed toxicity to M. hapla. To monitor the entry pathway of crystal proteins into M. hapla, second-stage juveniles (J2) were treated with NHS-rhodamine labeled nematicidal crystal proteins (Cry55Aa, Cry6Aa, and Cry5Ba). Confocal microscopic observation showed that these crystal proteins were initially detected in the stylet and esophageal lumen, and subsequently in the gut. Western blot analysis revealed that these crystal proteins were modified to different molecular sizes after being ingested. The uptake efficiency of the crystal proteins by the M. hapla J2 decreased with increasing of protein molecular mass, based on enzyme-linked immunosorbent assay analysis. Our discovery revealed 140 kDa nematicidal crystal proteins entered M. hapla J2 via the stylet, and it has important implications in designing a transgenic resistance approach to control RKN