LEADER 04278nam 22007575 450 001 996466072403316 005 20200705000026.0 010 $a3-540-39725-6 024 7 $a10.1007/11856214 035 $a(CKB)1000000000283983 035 $a(SSID)ssj0000319761 035 $a(PQKBManifestationID)11227255 035 $a(PQKBTitleCode)TC0000319761 035 $a(PQKBWorkID)10338658 035 $a(PQKB)10454454 035 $a(DE-He213)978-3-540-39725-0 035 $a(MiAaPQ)EBC3068038 035 $a(PPN)123138094 035 $a(EXLCZ)991000000000283983 100 $a20100324d2006 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt 182 $cc 183 $acr 200 10$aRecent Advances in Intrusion Detection$b[electronic resource] $e9th International Symposium, RAID 2006, Hamburg, Germany, September 20-22, 2006, Proceedings /$fedited by Diego Zamboni, Christopher Kruegel 205 $a1st ed. 2006. 210 1$aBerlin, Heidelberg :$cSpringer Berlin Heidelberg :$cImprint: Springer,$d2006. 215 $a1 online resource (XII, 331 p.) 225 1 $aInformation Systems and Applications, incl. Internet/Web, and HCI ;$v4219 300 $aBibliographic Level Mode of Issuance: Monograph 311 $a3-540-39723-X 320 $aIncludes bibliographical references and index. 327 $aRecent Advances in Intrusion Detection -- A Framework for the Application of Association Rule Mining in Large Intrusion Detection Infrastructures -- Behavioral Distance Measurement Using Hidden Markov Models -- Automated Discovery of Mimicry Attacks -- Allergy Attack Against Automatic Signature Generation -- Paragraph: Thwarting Signature Learning by Training Maliciously -- Anomaly Detector Performance Evaluation Using a Parameterized Environment -- Ranking Attack Graphs -- Using Hidden Markov Models to Evaluate the Risks of Intrusions -- The Nepenthes Platform: An Efficient Approach to Collect Malware -- Automatic Handling of Protocol Dependencies and Reaction to 0-Day Attacks with ScriptGen Based Honeypots -- Fast and Evasive Attacks: Highlighting the Challenges Ahead -- Anagram: A Content Anomaly Detector Resistant to Mimicry Attack -- DEMEM: Distributed Evidence-Driven Message Exchange Intrusion Detection Model for MANET -- Enhancing Network Intrusion Detection with Integrated Sampling and Filtering -- WIND: Workload-Aware INtrusion Detection -- SafeCard: A Gigabit IPS on the Network Card. 410 0$aInformation Systems and Applications, incl. Internet/Web, and HCI ;$v4219 606 $aManagement information systems 606 $aComputer science 606 $aComputers and civilization 606 $aData encryption (Computer science) 606 $aComputer communication systems 606 $aOperating systems (Computers) 606 $aManagement of Computing and Information Systems$3https://scigraph.springernature.com/ontologies/product-market-codes/I24067 606 $aComputers and Society$3https://scigraph.springernature.com/ontologies/product-market-codes/I24040 606 $aCryptology$3https://scigraph.springernature.com/ontologies/product-market-codes/I28020 606 $aComputer Communication Networks$3https://scigraph.springernature.com/ontologies/product-market-codes/I13022 606 $aOperating Systems$3https://scigraph.springernature.com/ontologies/product-market-codes/I14045 610 1 $aIntrusion detection 610 1 $aRAID 615 0$aManagement information systems. 615 0$aComputer science. 615 0$aComputers and civilization. 615 0$aData encryption (Computer science). 615 0$aComputer communication systems. 615 0$aOperating systems (Computers). 615 14$aManagement of Computing and Information Systems. 615 24$aComputers and Society. 615 24$aCryptology. 615 24$aComputer Communication Networks. 615 24$aOperating Systems. 676 $a005.8 702 $aZamboni$b Diego$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aKruegel$b Christopher$4edt$4http://id.loc.gov/vocabulary/relators/edt 906 $aBOOK 912 $a996466072403316 996 $aRecent Advances in Intrusion Detection$9772673 997 $aUNISA LEADER 04069nam 22007335 450 001 9910254078803321 005 20250609111446.0 010 $a3-319-51829-1 024 7 $a10.1007/978-3-319-51829-9 035 $a(CKB)3710000001100884 035 $a(MiAaPQ)EBC4822606 035 $a(DE-He213)978-3-319-51829-9 035 $a(PPN)199767467 035 $a(MiAaPQ)EBC6237365 035 $a(EXLCZ)993710000001100884 100 $a20170314d2016 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $2rdacontent 182 $2rdamedia 183 $2rdacarrier 200 10$aCombinatorics and Complexity of Partition Functions /$fby Alexander Barvinok 205 $a1st ed. 2016. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2016. 215 $a1 online resource (304 pages) $cillustrations 225 1 $aAlgorithms and Combinatorics,$x0937-5511 ;$v30 311 08$a3-319-51828-3 320 $aIncludes bibliographical references and index. 327 $aChapter I. Introduction -- Chapter II. Preliminaries -- Chapter III. Permanents -- Chapter IV. Hafnians and Multidimensional Permanents -- Chapter V. The Matching Polynomial -- Chapter VI. The Independence Polynomial -- Chapter VII. The Graph Homomorphism Partition Function -- Chapter VIII. Partition Functions of Integer Flows -- References -- Index. 330 $aPartition functions arise in combinatorics and related problems of statistical physics as they encode in a succinct way the combinatorial structure of complicated systems. The main focus of the book is on efficient ways to compute (approximate) various partition functions, such as permanents, hafnians and their higher-dimensional versions, graph and hypergraph matching polynomials, the independence polynomial of a graph and partition functions enumerating 0-1 and integer points in polyhedra, which allows one to make algorithmic advances in otherwise intractable problems. The book unifies various, often quite recent, results scattered in the literature, concentrating on the three main approaches: scaling, interpolation and correlation decay. The prerequisites include moderate amounts of real and complex analysis and linear algebra, making the book accessible to advanced math and physics undergraduates. . 410 0$aAlgorithms and Combinatorics,$x0937-5511 ;$v30 606 $aAlgorithms 606 $aCombinatorial analysis 606 $aComputer science?Mathematics 606 $aStatistical physics 606 $aDynamics 606 $aApproximation theory 606 $aMathematics of Algorithmic Complexity$3https://scigraph.springernature.com/ontologies/product-market-codes/M13130 606 $aCombinatorics$3https://scigraph.springernature.com/ontologies/product-market-codes/M29010 606 $aDiscrete Mathematics in Computer Science$3https://scigraph.springernature.com/ontologies/product-market-codes/I17028 606 $aComplex Systems$3https://scigraph.springernature.com/ontologies/product-market-codes/P33000 606 $aAlgorithms$3https://scigraph.springernature.com/ontologies/product-market-codes/M14018 606 $aApproximations and Expansions$3https://scigraph.springernature.com/ontologies/product-market-codes/M12023 615 0$aAlgorithms. 615 0$aCombinatorial analysis. 615 0$aComputer science?Mathematics. 615 0$aStatistical physics. 615 0$aDynamics. 615 0$aApproximation theory. 615 14$aMathematics of Algorithmic Complexity. 615 24$aCombinatorics. 615 24$aDiscrete Mathematics in Computer Science. 615 24$aComplex Systems. 615 24$aAlgorithms. 615 24$aApproximations and Expansions. 676 $a510 700 $aBarvinok$b Alexander$4aut$4http://id.loc.gov/vocabulary/relators/aut$0322075 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910254078803321 996 $aCombinatorics and complexity of partition functions$91523225 997 $aUNINA