In this work, a class of polyol solid-solid phase change material where Neopentyl glycol is mixed in 6 and 2 wt.% of Pentaerythritol and was synthesized by physical blending method to obtain homogeneous mixture and thermally cycled for 500 times. The surface morphology, chemical composition, crystal phase identification, thermal degradation, and phase change phenomena were characterized. The phase transition temperatures and enthalpies upon heating and cooling of 6 and 2 wt.% of Pentaerythritol are found to be 43.1 °C, 133 J g-1, and 28.2 °C, 119 J g-1, and 41.2 °C, 121 J g-1, and 28.5 °C, 106 J g-1, respectively which suits for electronic system to keep under operating zone. Laser Flash Apparatus was used to find the thermal diffusivity and thermal conductivity value was calculated. Further, the effect of heat transfer in binary polyol mixtures were experimentally analysed through conventional heat sink for electronic cooling application.

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HTTP flooding attack has a unique feature of interrupting application level services rather than depleting the network resources as in any other flooding attacks. Bombarding of HTTP GET requests to a target results in Denial of Service (DoS) of the web server. Usage of shortened Uniform Resource Locator (URL) is one of the best ways to unknowingly trap users for their participation in HTTP GET flooding attack. The existing solutions for HTTP attacks are based on browser level cache maintenance, CAPTCHA technique, and usage of Access Control Lists (ACL). Such techniques fail to prevent dynamic URL based HTTP attacks. To come up with a solution for the prevention of such kind of HTTP flooding attack, a real time HTTP GET flooding attack was generated using d0z-me, a malicious URL shortener tool. When user clicked the shortened URL, it was found that the user intended web page was displayed in the web browser. But simultaneously, an avalanche of HTTP GET requests were generated at the backdrop to the web server based on the scripts downloaded from the attacker. Since HTTP GET request traffic are part of any genuine internet traffic, it becomes difficult for the firewall to detect such kind of attacks. This motivated us to propose a Threshold Based Kernel Level HTTP Filter (TBHF), which would prevent internet users from taking part in such kind of Distributed Denial of Service (DDoS) attacks unknowingly. Windows Filtering Platform (WFP), which is an Application Programming Interface (API), was used to develop TBHF. The proposed solution was tested by installing TBHF on a victim machine and generating the DDoS attack. It was observed that the TBHF completely prevented the user from participating in DDoS attack by filtering out the malicious HTTP GET requests while allowing other genuine HTTP GET requests generated from that system

Abstract-Bots usually vary from their other malicious counter parts by periodically reporting to the botmaster through regular exchange of messages. Our experiments on bot attack generation showed a continuous exchange of packets with similar content between the botmaster and the zombie machine at various time intervals. Though there were also genuine packets with similar content being sent out of the victim machine challenge was to differentiate between the two and pass only the genuine ones.

Bot is a malicious piece of software derived from the word 'robot', which when installed in a host makes it a Zombie machine. Botnets are a group of distributed bots controlled by a master computer often referred to as botmaster (remote attacker). A zombie machine may respond to genuine requests as well as the requests from its botmaster simultaneously. The responses for the genuine requests do not exhibit similarity. But the responses for the botmaster exhibit a high degree of similarity. This similarity can be used to distinguish the presence of malware. Many modern botnets rely on dynamic/fast-flux DNS services. In a fast-flux DNS technique, hundreds or thousands of compromised hosts are used as proxies to hide the identities of the true command and control (C&C) servers. These hosts constantly alternate in a round-robin fashion to resolve one hostname to many different IP addresses 1. Bots can basically be classified into two types. 1.1 Network-based Bots These bots generate attacks on the victim machine in an attempt to overload the computing resources. These bots perform various attacks such as spamming, phishing, clickjacking, and different flooding attacks, viz., UDP flood attacks, SYN flood attacks, Socket flood attacks, and HTTP flood attacks. 1.2 Host-based Bots These are bots which get installed in the victim machine automatically when the user downloads any kind of freeware from the internet. These are Trojans which are bound along with the software downloaded from the internet using binder software which the victim is totally unaware of. These bots are developed with features such as keylogging for closely monitoring user behavior, interception of sensitive data including passwords and monitoring of mouse clicks. Bots usually communicate with their botmaster in order to receive commands from them. Based on this behavior, bots can be categorised into many types as discussed in the following IRC bots make use of internet relay chat protocol for communication. The detection of such kinds of bots is done by using number of features such as average packet size, ratio of visible to invisible users in the channel, unusual or common nicknames used during the chat, average word length, string distance, etc. [2] Alternatively the command and control of botmaster can be implemented by message exchanges using HTTP. Such bots are known as HTTP bots. These HTTP bots are detected by observing the degree of periodic repeatability in bot communication using packet information such as source and destination IP addresses and the inter arrival time between the packets 3. In a Peer2Peer(P2P) network, attackers make use of the decentralized structure of