Key Issues and Challenges of Intrusion Detection and Prevention System: Developing Proactive Protection in Wireless Network Environment

Nowadays wireless technology plays an important role in public and personal communication. However, the growth of wireless networking has confused the traditional boundaries between trusted and untrusted networks. Wireless networks are subject to a variety of threats and attacks at present. An attacker has the ability to listen to all network traffic which becoming a potential intrusion. Intrusion of any kind may lead to a chaotic condition. In addition, improperly configured access points also contribute the risk to wireless network. To overcome this issue, a security solution that includes an intrusion detection and prevention system need to be implemented. In this paper, first the security drawbacks of wireless network will be analyzed then investigate the characteristics and also the limitations on current wireless intrusion detection and prevention system. Finally, the requirement of next wireless intrusion prevention system will be identified including some key issues which should be focused on in the future to overcomes those limitations.

An Enhanced Cryptanalytic Attack on Knapsack Cipher using Genetic Algorithm

With the exponential growth of networked system and application such as eCommerce, the demand for effective internet security is increasing. Cryptology is the science and study of systems for secret communication. It consists of two complementary fields of study: cryptography and cryptanalysis. The application of genetic algorithms in the cryptanalysis of knapsack ciphers is suggested by Spillman [7]. In order to improve the efficiency of genetic algorithm attack on knapsack cipher, the previously published attack was enhanced and re-implemented with variation of initial assumptions and results are compared with Spillman results. The experimental result of research indicates that the efficiency of genetic algorithm attack on knapsack cipher can be improved with variation of initial assumption.

The Implicit Methods for the Study of Tolerance

Tolerance is a tool for achieving a social cohesion, particularly, among individuals and groups with different values. The aim is to study the characteristics of the ethnic tolerance, the inhabitants of Latvia. The ethnic tolerance is taught as a set of conscious and unconscious orientations of the individual in social interaction and inter-ethnic communication. It uses the tools of empirical studies of the ethnic tolerance which allows to identify the explicitly and implicitly levels of the emotional component of Latvia's residents. Explicit measurements were made using the techniques of self-report which revealed the index of the ethnic tolerance and the ethnic identity of the participants. The implicit component was studied using methods based on the effect of the emotional priming. During the processing of the results, there were calculated indicators of the positive and negative implicit attitudes towards members of their own and other ethnicity as well as the explicit parameters of the ethnic tolerance and the ethnic identity of Latvia-s residents. The implicit measurements of the ratio of neighboring ethnic groups against each other showed a mutual negative attitude whereas the explicit measurements indicate a neutral attitude. The data obtained contribute to a further study of the ethnic tolerance of Latvia's residents.

Using Teager Energy Cepstrum and HMM distancesin Automatic Speech Recognition and Analysis of Unvoiced Speech

In this study, the use of silicon NAM (Non-Audible Murmur) microphone in automatic speech recognition is presented. NAM microphones are special acoustic sensors, which are attached behind the talker-s ear and can capture not only normal (audible) speech, but also very quietly uttered speech (non-audible murmur). As a result, NAM microphones can be applied in automatic speech recognition systems when privacy is desired in human-machine communication. Moreover, NAM microphones show robustness against noise and they might be used in special systems (speech recognition, speech conversion etc.) for sound-impaired people. Using a small amount of training data and adaptation approaches, 93.9% word accuracy was achieved for a 20k Japanese vocabulary dictation task. Non-audible murmur recognition in noisy environments is also investigated. In this study, further analysis of the NAM speech has been made using distance measures between hidden Markov model (HMM) pairs. It has been shown the reduced spectral space of NAM speech using a metric distance, however the location of the different phonemes of NAM are similar to the location of the phonemes of normal speech, and the NAM sounds are well discriminated. Promising results in using nonlinear features are also introduced, especially under noisy conditions.

Using Different Aspects of the Signings for Appearance-based Sign Language Recognition

Sign language is used by the deaf and hard of hearing people for communication. Automatic sign language recognition is a challenging research area since sign language often is the only way of communication for the deaf people. Sign language includes different components of visual actions made by the signer using the hands, the face, and the torso, to convey his/her meaning. To use different aspects of signs, we combine the different groups of features which have been extracted from the image frames recorded directly by a stationary camera. We combine the features in two levels by employing three techniques. At the feature level, an early feature combination can be performed by concatenating and weighting different feature groups, or by concatenating feature groups over time and using LDA to choose the most discriminant elements. At the model level, a late fusion of differently trained models can be carried out by a log-linear model combination. In this paper, we investigate these three combination techniques in an automatic sign language recognition system and show that the recognition rate can be significantly improved.

An Experimental Multi-Agent Robot System for Operating in Hazardous Environments

In this paper, a multi-agent robot system is presented. The system consists of four robots. The developed robots are able to automatically enter and patrol a harmful environment, such as the building infected with virus or the factory with leaking hazardous gas. Further, every robot is able to perform obstacle avoidance and search for the victims. Several operation modes are designed: remote control, obstacle avoidance, automatic searching, and so on.

Investigating Cultural, Artistic and Architectural Consequences of Mongolian Invasion of Iran and Establishment of Ilkhanate Dynasty

Social, culture and artistic status of a society in various historical eras is affected by numerous, and sometimes imposed, factors that better understanding requires analysis of such conditions. Throughout history Iran has been involved with determining and significant events that examining each of these events can improve the understanding of social conditions of this country in the intended time. Mongolian conquest of Iran is one of most significant events in the history of Iran with consequences that never left Iranian societies. During this tragic invasion and subsequent devastating wars, which led to establishment of Ilkhanate dynasty, numerous cultural and artistic changes occurred both in Mongolian conquerors and Iranian society. This study examines these changes with a glimpse towards art and architecture as important part of cultural aspects and social communication.

Tabu Search Approach to Solve Routing Issues in Communication Networks

Optimal routing in communication networks is a major issue to be solved. In this paper, the application of Tabu Search (TS) in the optimum routing problem where the aim is to minimize the computational time and improvement of quality of the solution in the communication have been addressed. The goal is to minimize the average delays in the communication. The effectiveness of Tabu Search method is shown by the results of simulation to solve the shortest path problem. Through this approach computational cost can be reduced.

Specification of Agent Explicit Knowledge in Cryptographic Protocols

Cryptographic protocols are widely used in various applications to provide secure communications. They are usually represented as communicating agents that send and receive messages. These agents use their knowledge to exchange information and communicate with other agents involved in the protocol. An agent knowledge can be partitioned into explicit knowledge and procedural knowledge. The explicit knowledge refers to the set of information which is either proper to the agent or directly obtained from other agents through communication. The procedural knowledge relates to the set of mechanisms used to get new information from what is already available to the agent. In this paper, we propose a mathematical framework which specifies the explicit knowledge of an agent involved in a cryptographic protocol. Modelling this knowledge is crucial for the specification, analysis, and implementation of cryptographic protocols. We also, report on a prototype tool that allows the representation and the manipulation of the explicit knowledge.

Towards Model-Driven Communications

In modern distributed software systems, the issue of communication among composing parts represents a critical point, but the idea of extending conventional programming languages with general purpose communication constructs seems difficult to realize. As a consequence, there is a (growing) gap between the abstraction level required by distributed applications and the concepts provided by platforms that enable communication. This work intends to discuss how the Model Driven Software Development approach can be considered as a mature technology to generate in automatic way the schematic part of applications related to communication, by providing at the same time high level specialized languages useful in all the phases of software production. To achieve the goal, a stack of languages (meta-meta¬models) has been introduced in order to describe – at different levels of abstraction – the collaborative behavior of generic entities in terms of communication actions related to a taxonomy of messages. Finally, the generation of platforms for communication is viewed as a form of specification of language semantics, that provides executable models of applications together with model-checking supports and effective runtime environments.

Hiding Data in Images Using PCP

In recent years, everything is trending toward digitalization and with the rapid development of the Internet technologies, digital media needs to be transmitted conveniently over the network. Attacks, misuse or unauthorized access of information is of great concern today which makes the protection of documents through digital media a priority problem. This urges us to devise new data hiding techniques to protect and secure the data of vital significance. In this respect, steganography often comes to the fore as a tool for hiding information. Steganography is a process that involves hiding a message in an appropriate carrier like image or audio. It is of Greek origin and means "covered or hidden writing". The goal of steganography is covert communication. Here the carrier can be sent to a receiver without any one except the authenticated receiver only knows existence of the information. Considerable amount of work has been carried out by different researchers on steganography. In this work the authors propose a novel Steganographic method for hiding information within the spatial domain of the gray scale image. The proposed approach works by selecting the embedding pixels using some mathematical function and then finds the 8 neighborhood of the each selected pixel and map each bit of the secret message in each of the neighbor pixel coordinate position in a specified manner. Before embedding a checking has been done to find out whether the selected pixel or its neighbor lies at the boundary of the image or not. This solution is independent of the nature of the data to be hidden and produces a stego image with minimum degradation.

Algebraic Approach for the Reconstruction of Linear and Convolutional Error Correcting Codes

In this paper we present a generic approach for the problem of the blind estimation of the parameters of linear and convolutional error correcting codes. In a non-cooperative context, an adversary has only access to the noised transmission he has intercepted. The intercepter has no knowledge about the parameters used by the legal users. So, before having acess to the information he has first to blindly estimate the parameters of the error correcting code of the communication. The presented approach has the main advantage that the problem of reconstruction of such codes can be expressed in a very simple way. This allows us to evaluate theorical bounds on the complexity of the reconstruction process but also bounds on the estimation rate. We show that some classical reconstruction techniques are optimal and also explain why some of them have theorical complexities greater than these experimentally observed.