Provable Secure and Efficient Digital Rights Management Authentication Scheme Using Smart Card Based on Elliptic Curve Cryptography

Since the concept of ubiquitous computing is firstly proposed by Mark Weiser, its connotation has been extending and expanding by many scholars. In pervasive computing application environment, many kinds of small devices containing smart cart are used to communicate with others. In 2013, Yang et al. proposed an enhanced authentication scheme using smart card for digital rights management. They demonstrated that their scheme is secure enough. However, Mishra et al. pointed out that Yang et al.’s scheme suffers from the password guessing attack and the denial of service attack. Moreover, they also demonstrated that Yang et al.’s scheme is not efficient enough when the user inputs an incorrect password. In this paper, we analyze Yang et al.’s scheme again, and find that their scheme is vulnerable to the session key attack. And, there are some mistakes in their scheme. To surmount the weakness of Yang et al.’s scheme, we propose a more efficient and provable secure digital rights management authentication scheme using smart card based on elliptic curve cryptography

Secure Chaotic Map Based Block Cryptosystem with Application to Camera Sensor Networks

Recently, Wang et al. presented an efficient logistic map based block encryption system. The encryption system employs feedback ciphertext to achieve plaintext dependence of sub-keys. Unfortunately, we discovered that their scheme is unable to withstand key stream attack. To improve its security, this paper proposes a novel chaotic map based block cryptosystem. At the same time, a secure architecture for camera sensor network is constructed. The network comprises a set of inexpensive camera sensors to capture the images, a sink node equipped with sufficient computation and storage capabilities and a data processing server. The transmission security between the sink node and the server is gained by utilizing the improved cipher. Both theoretical analysis and simulation results indicate that the improved algorithm can overcome the flaws and maintain all the merits of the original cryptosystem. In addition, computational costs and efficiency of the proposed scheme are encouraging for the practical implementation in the real environment as well as camera sensor network

To study the procurement process and develop a conceptual framework model in the Pakistani construction industry

Procurement of equipment and materials in any construction project holds a tremendous significance for the project to be completed on time and within the budget. In this research, procurement in the Pakistan’s construction industry has been studied and a conceptual framework in terms of e-procurement portal has been suggested to smoothly execute the process of e-procurement by mitigating the barriers involved in the concerned process. A questionnaire survey form has been developed and 100 responses have been recorded to take the input from industry experts on the proposed procurement framework. A total of 84 respondents out of 100 thought that the proposed framework will be a better way to solve the problems that come up during the procurement process. Furthermore, it was also found that the main reason for procurement delays in construction projects is lack of communication and coordination among different departments within an organization, to which the suggested framework can be used as a potential tool to deal with

Melanotic Neuroectodermal Tumour of Infancy: A Rare Brain Tumour of Childhood

Melanotic neuroectodermal tumour of infancy is a rare, mostly benign but locally aggressive tumour of neural crest cellorigin occurring in infants. The most commonly affected anatomic site is the maxilla. Such tumours of the brain and skull are very rare. We present the case of an 8 months old baby girl whose presenting complaint was a swelling in the scalp for 6 months. She was otherwise asymptomatic. CT imaging confirmed the presence of an osteolytic tumour in the anterior parasagittal skull with dural involvement. The tumour was surgically excised enbloc. The patient has been well at 2 years follow-up without any evidence of recurrence

PRIMARY GASTROINTESTINAL STROMAL TUMOUR OF THE PROSTATE: A CASE REPORT OF A RARE TUMOUR

A 70-year-old gentleman underwent prostatectomy for bladder outlet obstruction due to enlarged prostate and was found to have primary extragastrointestinal stromal tumour (EGIST). He has been started on imatinib therapy and is presently on follow-up. Prostatic EGIST should be one of the differential diagnoses in patients with enlarged prostate with normal prostate-specific antigen levels.Key words: Prostate, gastrointestinal stromal tumour, PSA 

Prediction of Soil Macronutrients Using Machine Learning Algorithm

In this research work, machine learning algorithms were applied to find the relationship between independent variables and dependent variables for soil data analysis. The independent variables include moisture, temperature, soil pH, Cation Exchange Capacity(CEC) whereas, the dependent variables include Nitrogen, Phosphorus and Potassium (NPK). This research concludes relationships between Phosphorus, Potassium,  soil pH and CEC; Nitrogen and soil moisture and temperature using machine learning(ML) algorithms so as to deduce NPK content of soil. A comparative analysis with obtained results from each ML method is also presented. Machine learning algorithms are best performed on data with multiple independent variables. The values computed for nitrogen relationship were more accurate than PK relationship values. The accuracy of data set I was less than data set II. A large data set would produce more accurate results for both data sets