The Experts below are selected from a list of 9162 Experts worldwide ranked by ideXlab platform
Chih-cheng Hung - One of the best experts on this subject based on the ideXlab platform.
-
image texture classification using Datagrams and characteristic views
ACM Symposium on Applied Computing, 2003Co-Authors: Shisong Yang, Chih-cheng HungAbstract:This paper addresses the problem of image texture classification. A novel texture feature called "characteristic view", which is directly extracted from a kernel corresponding to each texture class, was developed. The K-views template method was used to classify the texture pixels based on these features. The characteristic view concept is based on the assumption that an image taken from the nature scenes, a specific texture class in this image will frequently reveal the repetitions of some certain patterns of features. Different "views" can be obtained as features from different spatial locations. The datagram concept is developed in this paper. Experimental results using Datagrams are provided.
-
SAC - Image texture classification using Datagrams and characteristic views
Proceedings of the 2003 ACM symposium on Applied computing - SAC '03, 2003Co-Authors: Shisong Yang, Chih-cheng HungAbstract:This paper addresses the problem of image texture classification. A novel texture feature called "characteristic view", which is directly extracted from a kernel corresponding to each texture class, was developed. The K-views template method was used to classify the texture pixels based on these features. The characteristic view concept is based on the assumption that an image taken from the nature scenes, a specific texture class in this image will frequently reveal the repetitions of some certain patterns of features. Different "views" can be obtained as features from different spatial locations. The datagram concept is developed in this paper. Experimental results using Datagrams are provided.
J. J. Garcia-luna-aceves - One of the best experts on this subject based on the ideXlab platform.
-
Content-Centric Networking Using Anonymous Datagrams
arXiv: Networking and Internet Architecture, 2016Co-Authors: J. J. Garcia-luna-aceves, Maziar Mirzazad-barijoughAbstract:Using Interests (requests that elicit content) and maintaining per-Interest forwarding state in Pending Interest Tables (PIT) are integral to the design of the Named Data Networking (NDN) and Content-Centric Networking (CCNx) architectures. However, using PITs makes the network vulnerable to Interest-flooding attacks, and PITs can become very large. It is shown that in-network caching eliminates the need for Interest aggregation and obviates the use of PITs. A new approach to content-centric networking (CCN-GRAM) is introduced that provides all the benefits of NDN and CCNx, eliminates the use of PITs by means of anonymous Datagrams, and is immune to Interest-flooding attacks. Routers maintain routes to the anonymous origins of Interests using an on-demand routing approach in the data plane that can also be used to provide native support for multicasting in the dat a plane. Simulation experiments show that the number of forwarding entries required in CCN-GRAM is orders of magnitude smaller than the number of PIT entries.
-
Towards Loop-Free Forwarding of Anonymous Internet Datagrams That Enforce Provenance
2016 IEEE Global Communications Conference (GLOBECOM), 2016Co-Authors: J. J. Garcia-luna-acevesAbstract:The way in which addressing and forwarding are implemented in the Internet constitutes one of its biggest privacy and security challenges. The fact that source addresses in Internet Datagrams cannot be trusted makes the IP Internet inherently vulnerable to DoS and DDoS attacks. The Internet forwarding plane is open to attacks to the privacy of datagram sources, because source addresses in Internet Datagrams have global scope. The fact an Internet Datagrams are forwarded based solely on the destination addresses stated in datagram headers and the next hops stored in the forwarding information bases (FIB) of relaying routers allows Internet Datagrams to traverse loops, which wastes resources and leaves the Internet open to further attacks. We introduce PEAR (Provenance Enforcement through Addressing and Routing), a new approach for addressing and forwarding of Internet Datagrams that enables anonymous forwarding of Internet Datagrams, eliminates many of the existing DDoS attacks on the IP Internet, and prevents Internet Datagrams from looping, even in the presence of routing- table loops.
-
GLOBECOM - Towards Loop-Free Forwarding of Anonymous Internet Datagrams That Enforce Provenance
2016 IEEE Global Communications Conference (GLOBECOM), 2016Co-Authors: J. J. Garcia-luna-acevesAbstract:The way in which addressing and forwarding are implemented in the Internet constitutes one of its biggest privacy and security challenges. The fact that source addresses in Internet Datagrams cannot be trusted makes the IP Internet inherently vulnerable to DoS and DDoS attacks. The Internet forwarding plane is open to attacks to the privacy of datagram sources, because source addresses in Internet Datagrams have global scope. The fact an Internet Datagrams are forwarded based solely on the destination addresses stated in datagram headers and the next hops stored in the forwarding information bases (FIB) of relaying routers allows Internet Datagrams to traverse loops, which wastes resources and leaves the Internet open to further attacks. We introduce PEAR (Provenance Enforcement through Addressing and Routing), a new approach for addressing and forwarding of Internet Datagrams that enables anonymous forwarding of Internet Datagrams, eliminates many of the existing DDoS attacks on the IP Internet, and prevents Internet Datagrams from looping, even in the presence of routing- table loops.
Chen Shang - One of the best experts on this subject based on the ideXlab platform.
-
A Study of Datagram Congestion Control Protocol (DCCP)
Computer Science, 2003Co-Authors: Chen ShangAbstract:Datagram Congestion Control Protocol (DCCP) implements a congestion.controlled, unreliable flow of Datagrams suitable for use by applications such as streaming media. This paper specifies its background, main ideas, ongoing research and future implementation.
Shisong Yang - One of the best experts on this subject based on the ideXlab platform.
-
image texture classification using Datagrams and characteristic views
ACM Symposium on Applied Computing, 2003Co-Authors: Shisong Yang, Chih-cheng HungAbstract:This paper addresses the problem of image texture classification. A novel texture feature called "characteristic view", which is directly extracted from a kernel corresponding to each texture class, was developed. The K-views template method was used to classify the texture pixels based on these features. The characteristic view concept is based on the assumption that an image taken from the nature scenes, a specific texture class in this image will frequently reveal the repetitions of some certain patterns of features. Different "views" can be obtained as features from different spatial locations. The datagram concept is developed in this paper. Experimental results using Datagrams are provided.
-
SAC - Image texture classification using Datagrams and characteristic views
Proceedings of the 2003 ACM symposium on Applied computing - SAC '03, 2003Co-Authors: Shisong Yang, Chih-cheng HungAbstract:This paper addresses the problem of image texture classification. A novel texture feature called "characteristic view", which is directly extracted from a kernel corresponding to each texture class, was developed. The K-views template method was used to classify the texture pixels based on these features. The characteristic view concept is based on the assumption that an image taken from the nature scenes, a specific texture class in this image will frequently reveal the repetitions of some certain patterns of features. Different "views" can be obtained as features from different spatial locations. The datagram concept is developed in this paper. Experimental results using Datagrams are provided.
G Zorn - One of the best experts on this subject based on the ideXlab platform.
-
Microsoft Point-To-Point Encryption (MPPE) Protocol
2001Co-Authors: G. Pall, G ZornAbstract:The Point-to-Point Protocol (PPP) provides a standard method for transporting multi-protocol Datagrams over point-to-point links.
-
Deriving Keys for use with Microsoft Point-to-Point Encryption (MPPE)
2001Co-Authors: G ZornAbstract:The Point-to-Point Protocol (PPP) provides a standard method for transporting multi-protocol Datagrams over point-to-point links.
