In order for you to continue playing this game, youll need to click accept in the banner below.For the best results, please get the latest version of Google Chrome.Take control of one of them and stuff him full of lots of yummy food like doughnuts and candy Can you make your worm bigger and stronger than all of his fellow worms Hell need to grow up fast in order to survive while you compete against other players from all over the world.Game content and materials are trademarks and copyrights of their respective publisher and its licensors.
Email: xinwenfucs.uml.edu. Wei Zhao is with the Uni versity of Macau, Av. Most previous work assumed that a worm always propagates itself at the highest possible speed. Some newly developed worms (e.g., Atak worm) contradict this assumption by deliberately reducing the propagation speed in order to avoid detection. As such, we study a new class of worms, referred to as self-disciplinary worms. These worms adapt their propagation patterns in order to reduce the probability of detection, and eventually, to infect more computers. To develop proper countermeasures, we introduce a game-theoretic formulation to model the interaction between the worm propagator and the defender. We show that an effective integration of multiple countermeasure schemes (e.g., worm detection and forensics analysis) is critical for defending against self-disciplinary worms. We propose different integrated schemes for fighting different self-disciplinary worms, and evaluate their performance via real-world traffic data. Propagation growth rate Maximum infection rate for static self-disciplinary worms Maximum infection rate for dynamic self-disciplinary worms Relationship between maximum infection rate and maximum false positive rate Figures - uploaded by Wei Yu Author content All figure content in this area was uploaded by Wei Yu Content may be subject to copyright. Static Worm Game Pdf Content AvailableDiscover the worlds research 17 million members 135 million publications 700k research projects Join for free Public Full-texts 2 5485bf920cf2437065 ca0316.pdf Content available from Wei Yu: 5485bf920cf2437065ca0316.pdf TDSC-2008-01-0018-R1.pdf Content uploaded by Wei Yu Author content All content in this area was uploaded by Wei Yu on Dec 08, 2014 Content may be subject to copyright. ![]() These worms adapt their propa- gation patterns in order to reduce the probability of detection, and to eventually infect more computers. W e demonstrate that existing worm detection schemes based on trafc volume and variance cannot effectively defend against these self-disciplinary worms. ![]() W e show that an effective integration of multiple countermeasure schemes (e.g., worm detection and forensics analysis) is critical for defending against self-disciplinary worms. We pr opose different integrated schemes for ghting different self-disciplinary worms, and evaluate their performance via real-world trafc data. I NTR ODUCTION W orm is a malicious software program that propagates to other computers on the Internet by remotely exploiting vulnerabilities in these computers. W orm attack is considered a dangerous threat to the Internet. There have been many cases of Internet worm attacks, such as the Code-Red worm in 2001 1, the Slammer worm in 2003 2, and the WittySasser worms in 2004 3. For example, the Code-Red worm in- fected more than 350,000 computers in less than 14 hours by exploiting the buffer -overow vulnerability of Microsoft s Internet Information Services (IIS) 4.05.0, causing more than 1,200,000,000 in damage. One is to infect as many computers as possible within a given period of time. The other is to av oid being detected and punished by the defenders. After infecting a number of computers without being detected, the worm propagator can remotely control the infected computers and use them as stepping-stones to launch further attacks (e.g., distributed denial-of-service (DDoS) 4, phishing 5, and spyware 6). Recent studies showed the existence of a black market for Wei Y u is with the Department of Computer and Information Sciences, To wson University, To wson, MD 21252. E-mail: wyutowson.edu. Nan Zhang is with the Department of Computer Science, The George W ashington University, Washington, DC 20052. Email: nzhang10gwu.edu. Xinwen Fu is with the Department of Computer Science, University of Massachusetts Low- ell. Email: xinwenfucs.uml.edu. Wei Zhao is with the Uni versity of Macau, Av.
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