Analisis Pengawalan Pemberat Rangkaian Neural Perambatan Balik untuk Pengecaman Aksara Jawi

One of the factors that influences the recognition ability of a neural network is the initial values given to the weight vector during the training phase. The network may be trapped into a local minima if the initial weights are not chosen carefully. This paper presents an analysis of the ability of the network to recognise Jawi characters after it was trained using different methods of weight initialization. Three most common methods are zero, random and Nguyen-Widrow random. This paper presents the effect of these three methods on the ability of the network's recognition

Cellular automata based user authentication scheme using identity-bits commitment for wireless sensor network

In Wireless Sensor Network (WSN) communication, authentication between the communicating nodes is an important aspect and has gained intensive interest from the researcher all around the world. With the advance of the technology where the communication devices are all in small form factor, high speed and low cost authentication scheme for generating Message Authentication Code (MAC) is definitely a demand. This paper introduces a new fast and lightweight authentication scheme based on Cellular Automata (CA) utilizing a so called Identity-bits Commitment embedded in a temper resistance chip inside the wireless sensors. The security analysis shows that our scheme is secure against thwart replay attack and lightweight for fast implementation

Hybrid expert system of rough set and neural network

The combination of neural network and expert system can accelerate the process of inference, and then rapidly produce associated facts and consequences. However, neural network still has some problems such as providing explanation facilities, managing the architecture of network and accelerating the training time. Thus to address these issues we develop a new method for pre-processing based on rough set and merge it with neural network and expert system. The resulting system is a hybrid expert system model called a Hybrid Rough Neural Expert System (HRNES)

A survey on digital forensics trends

Digital forensic has evolved from addressing minor computer crimes to investigation of complex international cases with massive effect on the world. This paper studies the evolution of the digital forensic; its origins, its current position and its future directions. This paper sets the scene with exploring past literature on digital forensic approaches followed by the assessment and analysis of current state of art in both industrial and academic digital forensics research. The obtained results are compared and analyzed to provide a comprehensive view of the current digital forensics landscape. Furthermore, this paper highlights critical digital forensic issues that are being overlooked and not being addressed as deserved. The paper finally concludes with offering future research directions in this area

Trends in Android Malware Detection

This paper analyzes different Android malware detection techniques from several research papers, some of these techniques are novel while others bring a new perspective to the research work done in the past. The techniques are of various kinds ranging from detection using host based frameworks and static analysis of executable to feature extraction and behavioral patterns. Each paper is reviewed extensively and the core features of each technique are highlighted and contrasted with the others. The challenges faced during the development of such techniques are also discussed along with the future prospects for Android malware detection. The findings of the review have been well documented in this paper to aid those making an effort to research in the area of Android malware detection by understanding the current scenario and developments that have happened in the field thus far

Key transformation approach for Rijndael security.

The aim of the study is to improve the security of Rijndael key scheduling by increasing the bit contusion and diffusion of the Rijndael subkey, Rijndael is a block cipher designed by Joan Daemen and Vincent Rijmen. It is a combination of security, performance, efficiency, implementability and flexibility that makes it the best selection for Advanced Encryption Standard (AES). However, the 128 bit Rijndael key schedule does not satisfy the frequency (bit confusion) test for majority of subkeys and does not satisfy the avalanche (bit diffusion) test for any subkeys. These contribute to some attacks in the key schedule. Thus, a new transformation method which is called Shiftrow is proposed into the 128-bit Rijndael Key Schedule based upon information principles (bit confusion and diffusion properties). The new method has shown positive results in terms of the bit confusion and diffusion of subkey and it has increased bit confusion and diffusion compared to the subkey of the original Rijndael key schedule

Rangkaian Neural Genetik Aplikasi dalam Pengecaman Aksara Jawi

Objektif asas bagi Algoritma Genetik (atau ringkasnya AG) ialah melihat proses evolusi asli dalam bentuk satu versi perisian. Ia sering digunakan untuk masalah pengoptimuman. Dalam proses ini suatu populasi boleh berkembang biak, ditot atau diklon, dan mati dalam beberapa saat. Perubahan ini berlaku secara berterusan. Kini, AG telah dikembangkan konsepnya ke dalam Rangkaian Neural (atau ringkasnya RN). Kertas ini membicarakan konsep atau proses evolusi yang digunakan didalam R

Towards green frameworks for digital forensics investigation

Despite the fact that digital forensics involves strict procedures and complies with fixed regulations and principles, but as this paper presents, there are plenty of opportunities that can be practically employed in digital forensics to make this science greener. Virtualization can cost effectively reduce the number of workstations running forensic tools in the lab. Cloud computing and consolidating servers and storage devices in green data centers not only facilitate managing and securing services but also decline the number of required network and cooling facilities. Forensic labs can also be optimized with regard to environmental preservation. Using remote protocols and digitalizing paperwork procedures are environmentally helpful practices to accelerate investigation progress as well. Improving electrical power needs of labs and forensic devices is another issue that should be taken into consideration. Employing storage devices with optimal energy usage in digital forensics may highly reduce energy consumption. This paper study established green technologies particularly in information technology field and suggests a framework for implementing compatible techniques in digital forensics in order to reduce greenhouse gas pollutants, limit carbon emissions, and preserve the environment

A distributed push-based XML access control model for better scalability

XML access control is a non-trivial topic as XML language becomes a standard for data representation and transmission on the Web. Existing access control approaches to the published XML documents are not likely to scale well since they specify and enforce their access control policies in centralized servers. This paper proposed a distributed model for providing a scalable access control to the published XML documents. The proposed model is cost-effectively distributed for meeting the increased workload along with avoiding the possible bottlenecks. As a result, the proposed model effectively scales with the increased system and management workloads