Bonchi, F., Ferrari, E., Jiang, W., Malin, B. (Eds.)
2009, IX, 127 p.
Springer eBooks may be purchased by end-customers only and are sold without copy protection (DRM free). Instead, all eBooks include personalized watermarks. This means you can read the Springer eBooks across numerous devices such as Laptops, eReaders, and tablets.
You can pay for Springer eBooks with Visa, Mastercard, American Express or Paypal.
After the purchase you can directly download the eBook file or read it online in our Springer eBook Reader. Furthermore your eBook will be stored in your MySpringer account. So you can always re-download your eBooks.
This book constitutes the thoroughly refereed post-workshop proceedings of the Second International Workshop on Privacy, Security, and Trust in KDD, PinKDD 2008, held in Las Vegas, NV, USA, in March 2008 in conjunction with the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2008.
The 5 revised full papers presented together with 1 invited keynote lecture and 2 invited panel sessions were carefully reviewed and selected from numerous submissions. The papers are extended versions of the workshop presentations and incorporate reviewers' comments and discussions at the workshop and represent the diversity of data mining research issues in privacy, security, and trust as well as current work on privacy issues in geographic data mining.
Content Level »Research
Keywords »access control - anonymization - classification - data analysis - data mining - fraud detection - geocoding - graph data - identification - intelligence informatics - knowledge discovery - modeling - national security - network security - privacy
Invited Paper.- Data Mining for Security Applications and Its Privacy Implications.- Geocode Matching and Privacy Preservation.- Mobility, Data Mining and Privacy the Experience of the GeoPKDD Project.- Contributed Papers.- Data and Structural k-Anonymity in Social Networks.- Composing Miners to Develop an Intrusion Detection Solution.- Malicious Code Detection Using Active Learning.- Maximizing Privacy under Data Distortion Constraints in Noise Perturbation Methods.- Strategies for Effective Shilling Attacks against Recommender Systems.