THE USE OF AMPPD AS AN ALTERNATIVE SUBSTRATE FOR AP-MEDIATED DETECTION OF NONRADIOLABELED DNA PROBES IN EUCALYPTUS-SALIGNA

We present a non-radioactive alternative to Southern's (J. Mol. Biol. 98: 503-517, 1975) DNA-DNA hybridization technique. The use of AMPPD - Disodium 3-(4-Methoxyspiro {1,2-dioxetane-3,2'tricyclo[3.3.1.1(3,7)]decan}-4-yl)phyenyl phosphate as an alternative substrate for AP-mediated detection of digoxigenin-11 dUTP-labeled probes made possible the simple and nonhazardous reuse of blots. We used 0.8 % agarose gels containing 30 mug per lane of Eucalyptus saligna DNA, digested with Eco RI, electrophoresed and blotted on to nylon membranes (Hybond-N, Amersham, UK), using the Southern blotting procedure, and UV irradiated for one minute for DNA fixation. The hybridizations were carried out overnight with digoxigenin labeled random inserts of E. saligna DNA by using the Genius Kit (Boehringer Mannheim). Detection of the DNA-DNA hybrids was performed in the presence of 0.5% blocking agent and the substrates NBT/BCIP were replaced by 0.26 mM AMPPD in the final alkaline assay buffer (50 mul/cm2). After membrane incubation for five minutes at room temperature in a sealed plastic bag, the AMPPD solution was retrieved and stored at 4-degrees-C for reuse. A Kodak X-BRAF QA-S film was pressed firmly onto the bag containing the wet membrane, exposed for two to six hours and then developed. After use, the probes were stripped off and the blots reutilized, three times so far, with the same results.

On data-centric misbehavior detection in VANETs

Detecting misbehavior (such as transmissions of false information) in vehicular ad hoc networks (VANETs) is a very important problem with wide range of implications, including safety related and congestion avoidance applications. We discuss several limitations of existing misbehavior detection schemes (MDS) designed for VANETs. Most MDS are concerned with detection of malicious nodes. In most situations, vehicles would send wrong information because of selfish reasons of their owners, e.g. for gaining access to a particular lane. It is therefore more important to detect false information than to identify misbehaving nodes. We introduce the concept of data-centric misbehavior detection and propose algorithms which detect false alert messages and misbehaving nodes by observing their actions after sending out the alert messages. With the data-centric MDS, each node can decide whether an information received is correct or false. The decision is based on the consistency of recent messages and new alerts with reported and estimated vehicle positions. No voting or majority decisions is needed, making our MDS resilient to Sybil attacks. After misbehavior is detected, we do not revoke all the secret credentials of misbehaving nodes, as done in most schemes. Instead, we impose fines on misbehaving nodes (administered by the certification authority), discouraging them to act selfishly. This reduces the computation and communication costs involved in revoking all the secret credentials of misbehaving nodes. © 2011 IEEE.