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Muddassar Farooq: [Publications] [Author Rank by year] [Co-authors] [Prefers] [Cites] [Cited by]

Publications of Author

  1. Horst Wedde, Muddassar Farooq, Yue Zhang
    BeeHive: An Efficient Fault-Tolerant Routing Algorithm Inspired by Honey Bee Behavior. [Citation Graph (0, 0)][DBLP]
    ANTS Workshop, 2004, pp:83-94 [Conf]
  2. Horst Wedde, Muddassar Farooq
    A Performance Evaluation Framework for Nature Inspired Routing Algorithms. [Citation Graph (0, 0)][DBLP]
    EvoWorkshops, 2005, pp:136-146 [Conf]
  3. Horst Wedde, Constantin Timm, Muddassar Farooq
    BeeHiveGuard: A Step Towards Secure Nature Inspired Routing Algorithms. [Citation Graph (0, 0)][DBLP]
    EvoWorkshops, 2006, pp:243-254 [Conf]
  4. Horst Wedde, Muddassar Farooq, Mario Lischka
    An Evolutionary Meta Hierarchical Scheduler for the Linux Operating System. [Citation Graph (0, 0)][DBLP]
    GECCO (2), 2004, pp:1334-1335 [Conf]
  5. Horst Wedde, Muddassar Farooq, Thorsten Pannenbaecker, Bjoern Vogel, Christian Mueller, Johannes Meth, Rene Jeruschkat
    BeeAdHoc: an energy efficient routing algorithm for mobile ad hoc networks inspired by bee behavior. [Citation Graph (0, 0)][DBLP]
    GECCO, 2005, pp:153-160 [Conf]
  6. Horst Wedde, Muddassar Farooq
    Nature Centered Information Systems: How Philosophy and Poetry Helps in Designing Technical Systems. [Citation Graph (0, 0)][DBLP]
    IC-AI, 2005, pp:938-943 [Conf]
  7. Horst Wedde, Muddassar Farooq, Mario Lischka
    A User Centered Evolutionary Scheduling Framework. [Citation Graph (0, 0)][DBLP]
    IC-AI, 2004, pp:1126-1132 [Conf]
  8. Horst Wedde, Frank Thorsten Breuer, Muddassar Farooq
    A Role-Based Adaptive CSCL Environment for Intensive Hands-on Teaching and Learning under Rigid Time Constraints. [Citation Graph (0, 0)][DBLP]
    SECIII, 2002, pp:241-250 [Conf]
  9. Horst Wedde, Constantin Timm, Muddassar Farooq
    BeeHiveAIS: A Simple, Efficient, Scalable and Secure Routing Framework Inspired by Artificial Immune Systems. [Citation Graph (0, 0)][DBLP]
    PPSN, 2006, pp:623-632 [Conf]
  10. Muddassar Farooq, Ronaldo Menezes
    Special issue on nature-inspired applications and systems. [Citation Graph (0, 0)][DBLP]
    Journal of Systems Architecture, 2006, v:52, n:8-9, pp:441-442 [Journal]
  11. Horst F. Wedde, Muddassar Farooq
    A comprehensive review of nature inspired routing algorithms for fixed telecommunication networks. [Citation Graph (0, 0)][DBLP]
    Journal of Systems Architecture, 2006, v:52, n:8-9, pp:461-484 [Journal]
  12. Horst Wedde, Muddassar Farooq
    BeeHive: Routing Algorithms Inspired by Honey Bee Behavior. [Citation Graph (0, 0)][DBLP]
    KI, 2005, v:19, n:4, pp:18-24 [Journal]
  13. Muhammad Saleem, Muddassar Farooq
    BeeSensor: A Bee-Inspired Power Aware Routing Protocol for Wireless Sensor Networks. [Citation Graph (0, 0)][DBLP]
    EvoWorkshops, 2007, pp:81-90 [Conf]
  14. Nauman Mazhar, Muddassar Farooq
    Vulnerability analysis and security framework (BeeSec) for nature inspired MANET routing protocols. [Citation Graph (0, 0)][DBLP]
    GECCO, 2007, pp:102-109 [Conf]
  15. M. Zubair Shafiq, Mehrin Kiani, Bisma Hashmi, Muddassar Farooq
    Extended thymus action for reducing false positives in ais based network intrusion detection systems. [Citation Graph (0, 0)][DBLP]
    GECCO, 2007, pp:182- [Conf]
  16. Nauman Mazhar, Muddassar Farooq
    BeeAIS: Artificial Immune System Security for Nature Inspired, MANET Routing Protocol, BeeAdHoc. [Citation Graph (0, 0)][DBLP]
    ICARIS, 2007, pp:370-381 [Conf]
  17. M. Zubair Shafiq, Muddassar Farooq
    Defence Against 802.11 DoS Attacks Using Artificial Immune System. [Citation Graph (0, 0)][DBLP]
    ICARIS, 2007, pp:95-106 [Conf]

  18. The Role of Biomedical Dataset in Classification. [Citation Graph (, )][DBLP]

  19. Formal Modeling of BeeAdHoc: A Bio-inspired Mobile Ad Hoc Network Routing Protocol. [Citation Graph (, )][DBLP]

  20. Using spatio-temporal information in API calls with machine learning algorithms for malware detection. [Citation Graph (, )][DBLP]

  21. Embedded Malware Detection Using Markov n-Grams. [Citation Graph (, )][DBLP]

  22. A Comparative Study of Fuzzy Inference Systems, Neural Networks and Adaptive Neuro Fuzzy Inference Systems for Portscan Detection. [Citation Graph (, )][DBLP]

  23. Particle Swarm Optimisation as a Hardware-Oriented Meta-heuristic for Image Analysis. [Citation Graph (, )][DBLP]

  24. Guidelines to Select Machine Learning Scheme for Classification of Biomedical Datasets. [Citation Graph (, )][DBLP]

  25. A sense of danger: dendritic cells inspired artificial immune system for manet security. [Citation Graph (, )][DBLP]

  26. A formal performance modeling framework for bio-inspired ad hoc routing protocols. [Citation Graph (, )][DBLP]

  27. Attack analysis & bio-inspired security framework for IP multimedia subsystem. [Citation Graph (, )][DBLP]

  28. Improving accuracy of immune-inspired malware detectors by using intelligent features. [Citation Graph (, )][DBLP]

  29. Attack analysis & bio-inspired security framework for IPMultimedia subsystem. [Citation Graph (, )][DBLP]

  30. Application of evolutionary algorithms in detection of SIP based flooding attacks. [Citation Graph (, )][DBLP]

  31. IMAD: in-execution malware analysis and detection. [Citation Graph (, )][DBLP]

  32. Evolvable malware. [Citation Graph (, )][DBLP]

  33. Are evolutionary rule learning algorithms appropriate for malware detection? [Citation Graph (, )][DBLP]

  34. A hybrid GA-PSO fuzzy system for user identification on smart phones. [Citation Graph (, )][DBLP]

  35. Performance evaluation of evolutionary algorithms in classification of biomedical datasets. [Citation Graph (, )][DBLP]

  36. Bio-inspired telecommunications. [Citation Graph (, )][DBLP]

  37. On the appropriateness of evolutionary rule learning algorithms for malware detection. [Citation Graph (, )][DBLP]

  38. A Sense of 'Danger' for Windows Processes. [Citation Graph (, )][DBLP]

  39. Malware detection using statistical analysis of byte-level file content. [Citation Graph (, )][DBLP]

  40. RTP-miner: a real-time security framework for RTP fuzzing attacks. [Citation Graph (, )][DBLP]

  41. A Scalable Formal Framework for Analyzing the Behavior of Nature-Inspired Routing Protocols. [Citation Graph (, )][DBLP]

  42. Using Computational Intelligence to Identify Performance Bottlenecks in a Computer System. [Citation Graph (, )][DBLP]

  43. Using Formal Grammar and Genetic Operators to Evolve Malware. [Citation Graph (, )][DBLP]

  44. PE-Miner: Mining Structural Information to Detect Malicious Executables in Realtime. [Citation Graph (, )][DBLP]

  45. Keystroke-Based User Identification on Smart Phones. [Citation Graph (, )][DBLP]

  46. A framework for empirical evaluation of nature inspired routing protocols for wireless sensor networks. [Citation Graph (, )][DBLP]

  47. Extended thymus action for improving response of AIS based NID system against malicious traffic. [Citation Graph (, )][DBLP]

  48. A comprehensive formal framework for analyzing the behavior of nature-inspired routing protocols. [Citation Graph (, )][DBLP]

  49. Evaluating DoS Attacks against Sip-Based VoIP Systems. [Citation Graph (, )][DBLP]

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