Strengthening the security of cognitive packet networks

Route selection in cognitive packet networks (CPNs) occurs continuously for active flows and is driven by the users' choice of a quality of service (QoS) goal. Because routing occurs concurrently to packet forwarding, CPN flows are able to better deal with unexpected variations in network status, while still achieving the desired QoS. Random neural networks (RNNs) play a key role in CPN routing and are responsible to the next-hop decision making of CPN packets. By using reinforcement learning, RNNs' weights are continuously updated based on expected QoS goals and information that is collected by packets as they travel on the network experiencing the current network conditions. CPN's QoS performance had been extensively investigated for a variety of operating conditions. Its dynamic and self-adaptive properties make them suitable for withstanding availability attacks, such as those caused by worm propagation and denial-of-service attacks. However, security weaknesses related to confidentiality and integrity attacks have not been previously examined. Here, we look at related network security threats and propose mechanisms that could enhance the resilience of CPN to confidentiality, integrity and availability attacks

Students' Perspective on Collaborative Research-based Learning in Embedded Systems

The Covid-19 pandemic, which has occurred for more than two years, has left various problems in learning. According to the opinion of most teachers and students, learning using an online approach in some courses was less effective. For example, the Embedded Systems course (ES) stimulates students to do product development. Online learning even tended to cause a loss of motivation, especially in applied studies that require adequate time and facilities to do the practicum. Hence there is a need for a learning method that can be a solution to the problems caused by the online approach. In the ES, students are required to understand the not only theory but also practice comprehensively. Therefore, a more sophisticated strategy is necessary. To enable students to see and assess the events that transpired during product development, collaborated research-based learning (CRL) is expected to be a proper method to tackle such problems. With the RL approach, especially for applied subjects such as Embedded Systems, students must be able to innovate so that the learning process encourages them to find real solutions to the faced problems. CRL encourages students to be able to formulate research designs, data collection, practical research, and interpretation of results. CRL engages students in the process and active participation in acquiring reflective knowledge and critical thinking to build their vision. This report presents a preliminary examination of the implementation of CRL in ES to improve students' engagement. The study measure participants’ overview of using project management application in CRL. The study involved 30 students taking the ES. The study finding discovers that the students’ perspective of the CRL approach in ES is suitable during pandemi

FinTech, blockchain and Islamic finance : an extensive literature review

Purpose: The paper aims to review the academic research work done in the area of Islamic financial technology. The Islamic FinTech area has been classified into three broad categories of the Islamic FinTech, Islamic Financial technology opportunities and challenges, Cryptocurrency/Blockchain sharia compliance and law/regulation. Finally, the study identifies and highlights the opportunities and challenges that Islamic Financial institutions can learn from the conventional FinTech organization across the world. Approach/Methodology/Design: The study collected 133 research studies (50 from Social Science Research Network (SSRN), 30 from Research gate, 33 from Google Scholar and 20 from other sources) in the area of Islamic Financial Technology. The study presents the systematic review of the above studies. Findings: The study classifies the Islamic FinTech into three broad categories namely, Islamic FinTech opportunities and challenges, Cryptocurrency/Blockchain sharia compliance and law/regulation. The study identifies that the sharia compliance related to the cryptocurrency/Blockchain is the biggest challenge which Islamic FinTech organizations are facing. During our review we also find that Islamic FinTech organizations are to be considered as partners by the Islamic Financial Institutions (IFI’s) than the competitors. If Islamic Financial institutions want to increase efficiency, transparency and customer satisfaction they have to adopt FinTech and become partners with the FinTech companies. Practical Implications: The study will contribute positively to the understanding of Islamic Fintech for the academia, industry, regulators, investors and other FinTech users. Originality/Value: The study believes to contribute positively to understanding of Fintech based technology like cryptocurrency/Blockchain from sharia perspective.peer-reviewe

Iris recognition based on 2D Gabor filter

Iris recognition is a type of biometrics technology that is based on physiological features of the human body. The objective of this research is to recognize and identify iris among many irises that are stored in a visual database. This study employed a left and right iris biometric framework for inclusion decision processing by combining image processing and artificial bee colony. The proposed approach was evaluated on a visual database of 280 colored iris pictures. The database was then divided into 28 clusters. Images were preprocessed and texture features were extracted based Gabor filters to capture both local and global details within an iris. The technique begins by comparing the attributes of the online-obtained iris picture with those of the visual database. This technique either generates a reject or approve message. The consequences of the intended work reflect the output’s accuracy and integrity. This is due to the careful selection of attributes, as well as the deployment of an artificial bee colony and data clustering, which decreased complexity and eventually increased identification rate to 100%. We demonstrate that the proposed method achieves state-of-the-art performance and that our recommended procedures outperform existing iris recognition systems

Hand geometry recognition: an approach for closed and separated fingers

Hand geometry has been a biometric trait that has attracted attention from several researchers. This stems from the fact that it is less intrusive and could be captured without contact with the acquisition device. Its application ranges from forensic examination to basic authentication use. However, restrictions in hand placement have proven to be one of its challenges. Users are either instructed to keep their fingers separate or closed during capture. Hence, this paper presents an approach to hand geometry using finger measurements that considers both closed and separate fingers. The system starts by cropping out the finger section of the hand and then resizing the cropped fingers. 20 distances were extracted from each finger in both separate and closed finger images. A comparison was made between Manhattan distance and Euclidean distance for features extraction. The support vector machine (SVM) was used for classification. The result showed a better result for Euclidean distance with a false acceptance ratio (FAR) of 0.6 and a false rejection ratio (FRR) of 1.2

New approach on global optimization problems based on meta-heuristic algorithm and quasi-Newton method

This paper presents an innovative approach in finding an optimal solution of multimodal and multivariable function for global optimization problems that involve complex and inefficient second derivatives. Artificial bees colony (ABC) algorithm possessed good exploration search, but the major weakness at its exploitation stage. The proposed algorithms improved the weakness of ABC algorithm by hybridized with the most effective gradient based method which are Davidon-Flecher-Powell (DFP) and Broyden-Flecher-Goldfarb-Shanno (BFGS) algorithms. Its distinguished features include maximizing the employment of possible information related to the objective function obtained at previous iterations. The proposed algorithms have been tested on a large set of benchmark global optimization problems and it has shown a satisfactory computational behaviour and it has succeeded in enhancing the algorithm to obtain the solution for global optimization problems

Android Based Diet Consultant using Rule Pattern-based algorithm

The proposed project is based on a Dietitian app. The proposed app lets us discover what should we eat based on our weight, height, age, sex, and physical activity. It calculates BMI and BMR and tells us how many calories should we ideally need to intake per day. The calories we should intake will be feed in and based on the RETE algorithm the amount of food intake for the day will be decided. The proposed application is for any type of body person, it is also suited for any range of weight people. It will ideally inform how should we cut down the weight using target programs such as 1LB per week gain/loss. The given system will suggest a food list according to the meal that is if it’s breakfast lunch or dinner. It will accordingly organize heavy calorie food & light calorie food. The system will give more accurate results as it accepts the data entered by the user and processes it depending on some metrics already known to the application on the basis of which a diet plan is generated and ask the user if the user accepts the diet plan. If not accepted the system may also give an alternative diet pla

IoT Based Intruder Prevention using Fogger

Anamoly detection in videos plays an important role in various real-life applications. Most of traditional approaches depend on utilizing handcrafted features which are problem-dependent and optimal for specific tasks. Nowadays, there has been a rise in the amount of disruptive and offensive activities that have been happening. Due to this, security has been given principal significance. Public places like shopping centers, avenues, banks, etc. are increasingly being equipped with CCTVs to guarantee the security of individuals. Subsequently, this inconvenience is making a need to computerize this system with high accuracy. Since constant observation of these surveillance cameras by humans is a near-impossible task. It requires workforces and their constant attention to judge if the captured activities are anomalous or suspicious. Hence, this drawback is creating a need to automate this process with high accuracy. Moreover, there is a need to display which frame and which parts of the recording contain the uncommon activity which helps the quicker judgment of that unordinary action being unusual or suspicious. Therefore, to reduce the wastage of time and labour, we are utilizing deep learning algorithms for Automating Threat Recognition System. Its goal is to automatically identify signs of aggression and violence in real-time, which filters out irregularities from normal patterns. We intend to utilize different Deep Learning models (CNN and RNN) to identify and classify levels of high movement in the frame. From there, we can raise a detection alert for the situation of a threat, indicating the suspicious activities at an instance of time and spray the smoke spray

Prognostic System for Heart Disease using Machine Learning: A Review

In today’s world it became difficult for daily routine check-up. The Heart disease system is an end user support and online consultation project. Here the motto behind it is to make a person to know about their heart related problem and according to it formulate them how much vital the disease is. It will be easy to access and keep track of their respective health. Thus, it’s important to predict the disease as earliest. Attributes such as Bp, Cholesterol, Diabetes are fed into Classification methods of Machine Learning are been used to predict risk of heart disease

Chat Robot for Medical Applications

The Medical bot project is built using artificial algorithms that analyses user’s queries and understand user’s message. This System is a web application which provides answer to the query of the patients. Patients just have to query through the bot which is used for chatting. Patients can chat using any format there is no specific format the user has to follow. The System uses built in artificial intelligence to answer the query. The answers are appropriate what the user queries. The User can query any Medical related activities through the system. The user does not have to personally go to the Medical for enquiry. The System analyses the question and then answers to the user. The system answers to the query as if it is answered by the person. With the help of artificial intelligence, the system answers the query asked by the patients. The system replies using an effective Graphical user interface which implies that as if a real person is talking to the user. The user just has to register himself to the system and has to login to the system. After login user can access to the various helping pages. Various helping pages has the bot through which the user can chat by asking queries related to Medical activities. The system replies to the user with the help of effective graphical user interface. The user can query about the Medical related activities through online with the help of this web application. The user can query Medical related activities such as date and timing of annual day, sports day, and other cultural activities. This system helps the patients to be updated about the Medical activities