Abstract-Phishing has been easy and effective way for trickery and deception on the Internet. While solutions such as URL blacklisting have been effective to some degree, their reliance on exact match with the blacklisted entries makes it easy for attackers to evade. We start with the observation that attackers often employ simple modifications (e.g., changing top level domain) to URLs. Our system, PhishNet, exploits this observation using two components. In the first component, we propose five heuristics to enumerate simple combinations of known phishing sites to discover new phishing URLs. The second component consists of an approximate matching algorithm that dissects a URL into multiple components that are matched individually against entries in the blacklist. In our evaluation with real-time blacklist feeds, we discovered around 18,000 new phishing URLs from a set of 6,000 new blacklist entries. We also show that our approximate matching algorithm leads to very few false positives (3%) and negatives (5%).

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Erectile dysfunction (ED) or male impotence is defined as the inability to have or sustain an erection long enough to have a meaningful sexual intercourse. ED tends to occur gradually until the night time or early morning erections cease altogether or are so flaccid that successful intercourse does not occur. Sexual health is an important determinant of quality of life. Today, millions of men, young and old, suffer from ED due to high levels of synthetic hormones (known as Xenoestrogens) in our diet/environment; nutritionally imbalanced diet resulting from poor quality of produces; and extremely low levels of testosterone. To overcome the problem of sexual (or) ED various natural aphrodisiac potentials are preferred. The present review discusses about aphrodisiac potential of plants, its biological source, common name, part used and references, which are helpful for researchers to develop new aphrodisiac formulations.

Multi-rooted tree topologies are commonly used to construct high-bandwidth data center network fabrics. In these networks, switches typically rely on equal-cost multipath (ECMP) routing techniques to split traffic across multiple paths, where each flow is routed through one of the available paths, but packets within a flow traverse the same end-to-end path. Unfortunately, since ECMP splits traffic based on flow-granularity, it can cause load imbalance across multiple paths resulting in poor utilization of network resources. More fine-grained traffic splitting techniques are typically not preferred because they can cause packet reordering that can, according to conventional wisdom, lead to severe TCP throughput degradation. In this paper, we revisit this fact in the context of regular data center topologies such as fat-tree architectures. We argue that packet-level traffic splitting, where packets belong to a given flow are sprayed through all available paths, would lead to a better load-balanced network, which in turn leads to significantly more balanced queues and much higher throughput compared to ECMP. We conduct extensive simulations to corroborate this claim.

Multi-rooted tree topologies are commonly used to construct high-bandwidth data center network fabrics. In these networks, switches typically rely on equal-cost multipath (ECMP) routing techniques to split traffic across multiple paths, such that packets within a flow traverse the same end-to-end path. Unfortunately, since ECMP splits traffic based on flow-granularity, it can cause load imbalance across paths resulting in poor utilization of network resources. More fine-grained traffic splitting techniques are typically not preferred because they can cause packet reordering that can, according to conventional wisdom, lead to severe TCP throughput degradation. In this work, we revisit this fact in the context of regular data center topologies such as fat-tree architectures. We argue that packet-level traffic splitting, where packets of a flow are sprayed through all available paths, would lead to a better load-balanced network, which in turn leads to significantly more balanced queues and much higher throughput compared to ECMP.