On some artificial intelligence methods and technologies for cloud-computing protection

An overview of data-mining technologies used in applied information security systems is presented. The focus is made on a new and actively developing trend, cloud-computing media (including the socalled fog computing). The status and promising opportunities of using artificial intelligence models and methods to solve information security problems are also discussed.

[1]  Laura Schweitzer,et al.  Database Systems A Practical Approach To Design Implementation And Management , 2016 .

[2]  Danny Williams,et al.  Cloud Application Architectures: Building Applications and Infrastructure in the Cloud , 2009 .

[3]  Timothy Grance,et al.  Guidelines on Security and Privacy in Public Cloud Computing | NIST , 2012 .

[4]  Dave Aitel,et al.  The Shellcoder's Handbook: Discovering and Exploiting Security Holes , 2004 .

[5]  Patrick E. O'Neil,et al.  Precisely Serializable Snapshot Isolation (PSSI) , 2011, 2011 IEEE 27th International Conference on Data Engineering.

[6]  Elizabeth O'Neil,et al.  Database--Principles, Programming, and Performance , 1994 .

[7]  P. Mell,et al.  The NIST Definition of Cloud Computing , 2011 .

[8]  David Walker,et al.  Consistent updates for software-defined networks: change you can believe in! , 2011, HotNets-X.

[9]  Rick McGeer.  A correct, zero-overhead protocol for network updates , 2013, HotSDN '13.

[10]  David Walker,et al.  Abstractions for network update , 2012, SIGCOMM '12.

[11]  Andrei V. Gurtov,et al.  Detecting the Origin of DDoS Attacks in OpenStack Cloud Platform Using Data Mining Techniques , 2016, NEW2AN.

[12]  Irving L. Traiger,et al.  The notions of consistency and predicate locks in a database system , 1976, CACM.

[13]  Patrick E. O'Neil,et al.  Database Principles, Programming, Performance , 1994 .

[14]  J. Hadamard.  Sur les problemes aux derive espartielles et leur signification physique , 1902 .

[15]  Philip A. Bernstein,et al.  Concurrency Control and Recovery in Database Systems , 1987 .

[16]  Patrick O'Neil,et al.  Precisely serializable snapshot isolation , 2011 .

[17]  Carolyn E. Begg,et al.  Database Systems: A Practical Approach to Design, Implementation and Management , 1998 .

[18]  Ali Ghaffari,et al.  Software defined networks: A survey , 2016, J. Netw. Comput. Appl..

[19]  Jim Gray,et al.  A critique of ANSI SQL isolation levels , 1995, SIGMOD '95.

[20]  A. M. Turing,et al.  Computing Machinery and Intelligence , 1950, The Philosophy of Artificial Intelligence.

[21]  Karen A. Scarfone,et al.  Guide to Intrusion Detection and Prevention Systems (IDPS) , 2007 .

[22]  Jugal K. Kalita,et al.  Network attacks: Taxonomy, tools and systems , 2014, J. Netw. Comput. Appl..

[23]  Ivan Kholod,et al.  Creation of Data Mining Cloud Service on the Actor Model , 2015, NEW2AN.

[24]  Shane Legg,et al.  Universal Intelligence: A Definition of Machine Intelligence , 2007, Minds and Machines.

[25]  A. Tikhonov.  On the stability of inverse problems , 1943 .

[26]  Dennis Gamayunov,et al.  Hide and seek: worms digging at the Internet backbones and edges , 2013 .

[27]  Rick McGeer,et al.  Declarative Verifiable SDI Specifications , 2016, 2016 IEEE Security and Privacy Workshops (SPW).

[28]  K. Manton.  The White Papers , 2018, Population Registers and Privacy in Britain, 1936—1984.

[29]  Shane Legg,et al.  A Collection of Definitions of Intelligence , 2007, AGI.

[30]  Viktor Mikhaĭlovich Glushkov,et al.  An Introduction to Cybernetics , 1957, The Mathematical Gazette.

[31]  Sandra L. Murphy,et al.  BGP Security Vulnerabilities Analysis , 2006, RFC.

[32]  M. I. Zabezhailo,et al.  On the potential applications of data mining for information security provision of cloud-based environments , 2015, Automatic Documentation and Mathematical Linguistics.