Low-power group key agreement for heterogeneous wireless networks
Heterogeneous wireless networks are gaining popularity as users can be connected to these networks without any cables and even when they are mobile. The high power nodes in heterogeneous wireless networks do not have energy constraints but the user nodes, which can be large in numbers, are usually low power energy constrained devices. Therefore, the GKA protocol used to secure group communications in these networks has to take into consideration both the low power nature of the user nodes and the network size. In this paper, we present an energy efficient and scalable GKA protocol, which uses our proposed Contributory Ring-Centralized (ContRi-Central) group model. Besides providing complexity analysis, we also show the computational and communication energy consumption costs analysis of all nodes running our proposed scheme and four other efficient GKA protocols. Both the complexity analysis and energy consumption costs analysis indicate that our proposed scheme is more efficient and suitable for heterogeneous wireless networks.

title: Public-Key Encryption from ID-Based Encryption Without One-Time Signature
abstract: Design a secure public key encryption scheme and its security proof are one of the main interests in cryptography In 2004, Canetti, Halevi and Katz  constructed a public key encryption (PKE) from a selective identity-based encryption scheme with a strong one-time signature scheme In 2005, Boneh and Katz  improved Canetti-Halevi-Katz construction by replacing a strong one-time signature with a message authentication code, but it is not publicly verifiable Later, Boyen, Mei and Waters  constructed PKE scheme directly from Waters' IBE scheme  , which is only secure against direct chosen-ciphertext attack and is not secure against adaptive chosen-ciphertext attack In 2006,  further improved the efficiency of Canetti-Halevi-Katz (CHK) construction by directly from Boneh-Boyen identity based encryption (IBE) scheme  with a weak one-time signature In this paper, we construct an efficient public key encryption scheme without one-time signature, which preserves a publicly verifiable property and secure against adaptive chosen-ciphertext attack The construction of the proposed scheme is based on Boneh-Boyen identity-based encryption (IBE) scheme  and a trapdoor function We also show that the proposed scheme is more efficient than CHK construction.

title: Image-based document vectors for text retrieval
abstract: We propose a method for constructing a vector for a document image to represent its content to facilitate text retrieval. The method is based on an N-Gram algorithm for text similarity measure based on the frequency of occurrence of n-character strings appearing in the electronic text. Instead of using ASCII values, the present study investigates the use of character images to obtain the document vector and has found promising results for use in our news article retrieval project.

title: A Distributed Throttling Approach for Handling High Bandwidth Aggregates
abstract: Public-access networks need to handle persistent congestion and overload caused by high bandwidth aggregates that may occur during times of flooding-based DDoS attacks or flash crowds. The often unpredictable nature of these two activities can severely degrade server performance. Legitimate user requests also suffer considerably when traffic from many different sources aggregates inside the network and causes congestion. This paper studies a family of algorithms that "proactively" protect a server from overload by installing rate throttles in a set of upstream routers. Based on an optimal control setting, we propose algorithms that achieve throttling in a distributed and fair manner by taking important performance metrics into consideration, such as minimizing overall load variations. Using ns-2 simulations, we show that our proposed algorithms 1) are highly adaptive by avoiding unnecessary parameter configuration, 2) provide max-min fairness for any number of throttling routers, 3) respond very quickly to network changes, 4) are extremely robust against extrinsic factors beyond the system control, and 5) are stable under given delay bounds.

title: Text/graphics separation using agent-based pyramid operations
abstract: This paper describes a document image analysis system using multiple agents working on a pyramid structure to separate text from graphics in the image. Text strings appear as different groupings of connected components at different image resolutions. As such, the pyramid structure, which is a multi-resolution image representation, provides a natural means of identifying and grouping of character strings in the document at different levels of resolution. The pyramid structure is also amenable to parallel processing, where multiple agents in the system can individually and concurrently look for groups of connected components at appropriate levels. The agent-based pyramid operations do not require expensive feature analysis among different connected components to detect text strings as found in other existing works.

title: Chart analysis and recognition in document images
abstract: Hidden Markov models are a probabilistic modeling tool for time series data. It has been successfully applied to many areas, such as speech recognition, hand-written character recognition, etc. In this paper, we present a novel statistical approach using ergodic hidden Markov models to recognize scientific charts. We also present a newly developed feature extraction method for chart images. Unlike traditional primitive-based diagram recognition method, our approach need not recognize the graphic primitives in charts thus bypassing the recognition error problem caused by the inaccurate primitive extraction that is also a major obstacle to the construction of a general chart recognition system.

title: Document retrieval from compressed images
abstract: With the emergence of digital libraries, more and more documents are stored and transmitted through the Internet in the format of compressed images. It is of significant meaning to develop a system which is capable of retrieving documents from these compressed document images. Aiming at the popular compression standard-CCITT Group 4 which is widely used for compressing document images, we present an approach to retrieve the documents from CCITT Group 4 compressed document images in this paper. The black and white changing elements are extracted directly from the compressed document images to act as the feature pixels, and the connected components are detected simultaneously. Then the word boxes are bounded based on the merging of the connected components. Weighted Hausdorff distance is proposed to assign all of the word objects from both the query document and the document from database to corresponding classes by an unsupervised classifier, whereas the possible stop words are excluded. Document vectors are built by the occurrence frequency of the word object classes, and the pair-wise similarity of two document images is represented by the scalar product of the document vectors. Nine groups of articles pertaining to different domains are used to test the validity of the presented approach. Preliminary experimental results with the document images captured from students’ theses show that the proposed approach has achieved a promising performance.