The development of smart network infrastructure of the Internet of Things (IoT) faces the immense threat of sophisticated Distributed Denial-of-Services (DDoS) security attacks. The existing network security solutions of enterprise networks are significantly expensive and unscalable for IoT. The integration of recently developed Software Defined Networking (SDN) reduces a significant amount of computational overhead for IoT network devices and enables additional security measurements. At the prelude stage of SDN-enabled IoT network infrastructure, the sampling based security approach currently results in low accuracy and low DDoS attack detection. In this paper, we propose an Adaptive Machine Learning based SDN-enabled Distributed Denial-of-Services attacks Detection and Mitigation (AMLSDM) framework. The proposed AMLSDM framework develops an SDN-enabled security mechanism for IoT devices with the support of an adaptive machine learning classification model to achieve the successful detection and mitigation of DDoS attacks. The proposed framework utilizes machine learning algorithms in an adaptive multilayered feed-forwarding scheme to successfully detect the DDoS attacks by examining the static features of the inspected network traffic. In the proposed adaptive multilayered feed-forwarding framework, the first layer utilizes Support Vector Machine (SVM), Naive Bayes (NB), Random Forest (RF), k-Nearest Neighbor (kNN), and Logistic Regression (LR) classifiers to build a model for detecting DDoS attacks from the training and testing environment-specific datasets. The output of the first layer passes to an Ensemble Voting (EV) algorithm, which accumulates the performance of the first layer classifiers. In the third layer, the adaptive frameworks measures the real-time live network traffic to detect the DDoS attacks in the network traffic. The proposed framework utilizes a remote SDN controller to mitigate the detected DDoS attacks over Open Flow (OF) switches and reconfigures the network resources for legitimate network hosts. The experimental results show the better performance of the proposed framework as compared to existing state-of-the art solutions in terms of higher accuracy of DDoS detection and low false alarm rate.

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A BSTRACT Background: This study aimed to evaluate the phytochemicals screening of Erythrina suberosa (Roxb) bark and to analyze the enzymatic activities of its various organic fractions. Materials and Methods: Crude methanolic fraction of E. suberosa (Roxb) bark and its respective fractions were screened for the presence of different phytochemicals with different reagents. On the basis of increasing order of polarity, different organic solvents were used to obtain different fractions. Enzymatic studies were performed on crude methanolic extract of the plant. All the assays were performed under standard in vitro conditions. Results: The phytochemical analysis shows the presence of alkaloids, phenols, triterpenoids, phytosterols, and flavonoids. Phenolic compounds and flavonoids are the major constituents of the plant. In anticholinesterase assay, the percent inhibition of standard drug (eserine) was 91.27 ± 1.17 and the half maximal inhibitory concentration (IC 50 ) was 0.04 ± 0.0001. For α-glucosidase inhibition, the IC 50 value for Dichloromethane fraction was 8.45 ± 0.13, for Methanol fraction it was 64.24 ± 0.15, and for aqueous fraction it was 42.62 ± 0.17 as compared with standard IC 50 that is 37.42 (acarbose). Furthermore, results show that all fractions have potential against anti-urease enzyme, but DCM fraction of crude aqueous extract has significant IC 50 value (45.26 ± 0.13) than other fractions. Conclusion: Keeping in view all the results, it is evident that the plant can be used in future for formulating effective drugs against many ailments. Secondary metabolites and their derivatives possess different biological activities, for example, .g. flavonoids in cancer, asthma, and Alzheimer. Furthermore, the extracts of this plant can be used in their crude form, which is an addition to the complementary and alternative treatment strategies.

Purpose of the study: The main purpose of this study is to analyze the novel The Golden Legend by Nadeem Aslam in the light of the concept of Nationalism given by Benedict Anderson in Imagined communities. Methodology: The entire data is evaluated by the entire text related to nationalism. This research is based on qualitative research skills. The basic resource of this research is the novel of Nadeem Aslam, named The Golden Legend. Further, the other resources used in this research are the journals or the articles regarding or reflecting the explanation of this novel (The Golden Legend). Main Findings: The findings depict a wonderful series of characters who have humanity in their hearts; they have love and respect for others, either the other person is from their religion or a different one. It is a story of sorrow and the game of religions in the world which is being played under the acts of the political authorities. Applications of this study: This study can be applied to the nationalism literature. Novelty/Originality of this study: The study is one of its kind because, after a careful analysis of the literature available, it is safe to say that no study is done up till now on analyzing the concept of nationalism in the Golden Legend.

Background: The study presents the critical discourse analysis of Muniba Mazari speech (confined to one speech about her life struggles in her own words in TEDx) to unveil the concept of empowering women by sharing life struggles in Pakistani socio-cultural context. Muniba Mazari is UN representative of women of Pakistan and considered as the 'iron lady of Pakistan' that is why in this research her one speech at TEDx Malaysia in 2017,which went viral on social media. Her life story and struggle in the form of speech is analyzed by using Textual dimension of Three dimensional model of Fairclough (1989) approach to critical discourse analysis which is integrated with M.A.K. Halliday's (1985) Systematic Functional Grammar (SFG). Methodology: This qualitative study analyzed linguistic elements used by Muniba Mazari in her speech while sharing her life struggles in order to unveil the concept of women empowerment. Results: The finding include the excessive use of Pronoun 'I' which shows the explicit power as a woman. By using words with negative connotation like 'disable' she gave new direction to look at these words which have negative connation. Moreover, the key findings include how she was trapped in her societal customs and at last after her tragedy she took step for herself. Conclusion: This study will play an important role in the emerging trend of women empowerment in Pakistan by analyzing the language of an iron lady of Pakistan.