Increasing Accuracy and Reliability of IP Traceback for DDoS Attack Using Completion Condition

Abstract Probabilistic Packet Marking (PPM ) is one of the most promising schemes for performing IP Traceback. PPM reconstructs the attack graph in order to trace back to the attackers. Finding the Completion Condition Number (i.e. precise number of packets required to complete the traceback) is very important. Without a proper completion-condition, we might reconstruct a wrong attack-graph and attackers can evade detection. One presently being used works only for a single attacker based DoS attack and has an accuracy of just around 70%. We propose a new Completion Condition Number which has an accuracy of 95% and it works even for the multiple attacker based DDoS attacks. We confirm the results using detailed theoretical analysis and extensive simulation work. To the best of our knowledge, we are the first to apply the concept of Completion Condition Number to increase the reliability of IP Traceback for the DDoS attacks

An Analytical Model for Information Gathering and Propagation in Social Networks using Random Graphs

In this paper, we propose an analytical model for information gathering and propagation in social networks using random sampling. We represent the social network using the Erdos–Renyi model of the random graph. When a given node is selected in the social network, information about itself and all of its neighbors are obtained and these nodes are considered to be discovered. We provide an analytical solution for the expected number of nodes that are discovered as a function of the number of nodes randomly sampled in the graph. We use the concepts of combinatorics, probability, and inclusion–exclusion principle for computing the number of discovered nodes. This is a computationally-intensive problem with combinatorial complexity. This model is useful when crawling and mining of the social network graph is prohibited. Our work finds application in several important real-world decision support scenarios such as survey sample selection, construction of public directory, and crowdsourced databases using social networks, targeted advertising, and recommendation systems. It can also be used for finding a randomized dominating set of a graph that finds applications in computer networks, document summarization, and biological networks. We have evaluated the performance both analytically as well as by means of simulation, and the results are comparable. The results have an accuracy of around 96% for random graphs and above 87% for the power-law graphs

Effect of sulfonamide derivatives of phenylglycine on scopolamine‐induced amnesia in rats

Abstract Alzheimer's disease is a neurodegenerative disease responsible for dementia and other neuropsychiatric symptoms. In the present study, compounds 30 and 33, developed earlier in our laboratory as selective butyrylcholinesterase inhibitors, were tested against scopolamine‐induced amnesia to evaluate their pharmacodynamic effect. The efficacy of the compounds was determined by behavioral experiments using the Y‐maze and the Barnes maze and neurochemical testing. Both compounds reduced the effect of scopolamine treatment in the behavioral tasks at a dose of 20 mg/kg. The results of the neurochemical experiment indicated a reduction in cholinesterase activity in the prefrontal cortex and the hippocampus. The levels of antioxidant enzymes superoxide dismutase and catalase were restored compared to the scopolamine‐treated groups. The docking study on rat butyrylcholinesterase (BChE) indicated tight binding, with free energies of −9.66 and −10.23 kcal/mol for compounds 30 and 33, respectively. The two aromatic amide derivatives of 2‐phenyl‐2‐(phenylsulfonamido) acetic acid produced stable complexes with rat BChE in the molecular dynamics investigation

Tunable Synchronization in Duty-cycled Wireless Sensor Networks

In this work, we consider a duty-cycled wireless sensor network with the assumption that the on/off schedules are uncoordinated. In such networks, as all nodes may not be awake during the transmission of time synchronization messages, nodes will require to re-transmit the synchronization messages. Ideally a node should re-transmit for the maximum sleep duration to ensure that all nodes are synchronized. However, such a proposition will immensely increase the energy consumption of the nodes. Such a situation demands that there is an upper bound of the number of retransmissions. We refer to the time a node spends in re-transmission of the control message as broadcast duration. We ask the question, what should be the broadcast duration to ensure that a certain percentage of the available nodes are synchronized. The problem to estimate the broadcast duration is formulated so as to capture the probability threshold of the nodes being synchronized. Results show the proposed analytical model can predict the broadcast duration with a given lower error margin under real world conditions, thus demonstrating the efficiency of our solution

Vasicinone, a pyrroloquinazoline alkaloid from Adhatoda vasica Nees enhances memory and cognition by inhibiting cholinesterases in Alzheimer's disease

Background: Alzheimer's disease (AD) is a neurodegenerative disease with cognitive and memory decline. Due to the lack of effective treatment for AD, there is an interest in finding novel compounds to treat AD. The leaves of Adhatoda vasica Nees (AV) exhibited anti-AD effects and known to be rich in pyrroloquinazoline alkaloids. However, the role of pyrroloquinazoline alkaloids as an anti-AD was not explored. Therefore, the present study aimed to isolate active pyrroloquinazoline alkaloids through bioactivity guided fractionation from AV to explore their anti-AD effect. Method: Column chromatography of dichloromethane (DCM) fraction of methanolic extract was used to isolate the alkaloids from AV. The isolated compounds were characterized by TLC, HPLC, ATR, HRMS, and NMR techniques. In-silico, studies were performed to investigate the interaction of the isolated compounds with cholinesterase enzymes (AChE and BuChE). Further, in-vitro assays were carried out to evaluate the AChE, BuChE, and Aβ inhibition properties. Propidium iodide displacement assay was performed to know the selectivity of isolated compounds at AChE PAS site. Furthermore, in-vivo studies were performed to evaluate memory and cognitive improvement against scopolamine-induced amnesia and Aβ induced neurotoxicity in rats. Results: A couple of leads were identified through bioactivity guided fractionation, such as vasicinone (VAS) and vasicine (VA) were responsible for the cholinesterase inhibition in DCM fraction. In-silico studies identified that both compounds exhibited stable interactions at AChE and BuChE active sites. VAS and VA inhibited the AChE, BuChE, and Aβ aggregation in-vitro studies and effectively displaced the propidium iodide at AChE PAS site. Further, in-vivo studies showed that administration of VAS and VA significantly improved the memory and cognitive dysfunction in scopolamine and Aβ induced cognitive and memory impairments in rats. Besides, both VAS and VA recovered the hippocampal cell density in AD rats. Moreover, VAS and VA did not show any sign of toxicity. Conclusions: The present study revealed that VAS acts as potent anti-AD agent from Adhatoda vasica Nees and it showed similar potency profile to VA against memory and cognitive impairment in AD. Both compounds VAS and VA possess strong potential in the preclinical development as natural drugs for anti-AD

Wireless Precision Time Protocol

The IEEE 1588 precision time protocol (PTP) is a time synchronization protocol with sub-microsecond precision primarily designed for wired networks. In this letter, we propose wireless precision time protocol (WPTP) as an extension to PTP for multi-hop wireless networks. WPTP significantly reduces the convergence time and the number of packets required for synchronization without compromising on the synchronization accuracy