Sharif Digital Repository

This paper proposes a behavior detection system, HB2DS, to address the behavior-detection challenges in high-bandwidth networks. In HB2DS, a summarization of network traffic is represented through some meta-events. The relationships amongst meta-events are used to mine end-user behaviors. HB2DS satisfies the main constraints exist in analyzing of high-bandwidth networks, namely online learning and outlier handling, as well as one-pass processing, delay, and memory limitations. Our evaluation indicates significant improvement in big data stream analyzing in terms of accuracy and efficiency. © 2016 Elsevier Inc  

High-bandwidth network analysis is challenging, resource consuming, and inaccurate due to the high volume, velocity, and variety characteristics of the network traffic. The infinite stream of incoming traffic forms a dynamic environment with unexpected changes, which requires analysing approaches to satisfy the high-bandwidth network processing challenges such as incremental learning, inline processing, and outlier handling. This study proposes an inline high-bandwidth network stream clustering algorithm designed to incrementally mine large amounts of continuously transmitting network traffic when some outliers can be dropped before determining the network traffic behaviour. Maintaining... 

Today's high-bandwidth networks require adaptive analyzing approaches to recognize the network variable behaviors. The analyzing approaches should be robust against the lack of prior knowledge and provide data to impose more complex policies. In this paper, ACoPE is proposed as an adaptive semi-supervised learning approach for complex-policy enforcement in high-bandwidth networks. ACoPE detects and maintains inter-flows relationships to impose complex-policies. It employs a statistical process control technique to monitor accuracy. Whenever the accuracy decreased, ACoPE considers it as a changed behavior and uses data from a deep packet inspection module to adapt itself with the change. The... 

Correctness assurance of query results in data outsourcing scenarios includes authenticity, completeness, and freshness of the results. Utilizing signature chaining and aggregation, this paper proposes a method to verify the correctness of results returned from an untrusted server. An MHT constructed over attribute values of a tuple is used to provide the authenticity, and timestamp is used to provide the freshness verifiability of results. While our approach supports a wide range of queries, simulation results indicate its efficiency in comparison with some existing methods in terms of communication and computation overhead imposed to execute a query  

Nanocomposites of polypropylene (PP)/ethylene-propylene-diene rubber (EPDM) blend with montmorillonite-based organoclay were prepared in a solvent blending method. Solvent blending of PP and EPDM in a composition of 50:50 formed a two phase morphology in which EPDM appeared as dispersed phase with irregular shape. The size of dispersed phase reduced significantly to almost spherical domains by addition of the nanoclay. For better dispersion of nanoclay in the PP/EPDM blend, an antioxidant was used as compatibilizer. State of nanoclay dispersion was evaluated by X-ray diffraction (XRD), and also, by a novel method using permeability measurements data in a permeability model. The measured... 

Bivium is a simplified version of Trivium, a hardware profile finalist of eSTREAM project. Bivium has an internal state of size 177 bits and a key length of 80 bits. In this paper we introduce a distinguishing attack on this cipher. In this method we first find the best linear approximation for the updating function. Then by using this approximation, and optimizing the time delay, we find the distinguisher. The complexity of the attack is O(230.79), which is an improvement to the previous distinguishing attack with a complexity of order O(232)