Priority-based joint EDF–RM scheduling algorithm for individual real-time task on distributed systems

The Journal of Supercomputing - Multiple tasks arrive in the distributed systems that can be executed in either parallel or sequential manner. Before the execution, tasks are scheduled prioritywise...     

Identity Governance Framework for Privileged Users

Information technology companies have grown in size and recognized the need to protect their valuable assets. As a result, each IT application has its authentication mechanism, and an employee needs a username and password. As the number of applications increased, as a result, it became increasingly complex to manage all identities like the number of usernames and passwords of an employee. All identities had to be retrieved by users. Both the identities and the access rights associated with those identities had to be protected by an administrator. Management couldn’t even capture such access rights because they couldn’t verify things like privacy and security. Identity management can help solve this problem. The concept behind identity management is to centralize identity management and manage access identity centrally rather than multiple applications with their authentication and authorization mechanisms. In this research work, we develop governance and an identity management framework for information and technology infrastructures with privileged access management, consisting of cybersecurity policies and strategies. The results show the efficiency of the framework compared to the existing information security components. The integrated identity and access management and privileged access management enable organizations to respond to incidents and facilitate compliance. It can automate use cases that manage privileged accounts in the real world.     

DETERMINATION OF CINACALCET HYDROCHLORIDE BY CAPILLARY ELECTROPHORESIS WITH PHOTODIODE ARRAY DETECTION

This article reports a validated stability-indicating capillary electrophoresis method using a photodiode array detector at 220 nm for the determination of cinacalcet hydrochloride. The best electrophoretic separation between the analyte and internal standard (lamotrigine) was achieved within 5 min in a deactivated fused silica capillary (55 cm effective length × 75 µm internal diameter) maintained at 24°C using a background electrolyte solution consisted of phosphate buffer (50 mM, pH 6.4):methanol (95:5, v/v) at a separation voltage of 30 kV. The linear range of the method was 0.5–30 µg/mL (r = 0.9999) with limits of detection and quantitation of 0.1 and 0.5 µg/mL, respectively. The assay precision and accuracy were favorable as the relative standard deviations did not exceed 1.09%, and the recovery values were 98.99–100.33 ± 0.19–1.09%. The induced degradation products, when any, did not interfere with the detection of analyte. The proposed method was successfully applied for the determination of cinacalcet hydrochloride in bulk and pharmaceutical formulations; the percentage recovery values were 98.16–102.00 ± 0.24–1.08%. The results demonstrated the value of the method.     

Impact of Human Vulnerabilities on Cybersecurity

Today, security is a major challenge linked with computer network companies that cannot defend against cyber-attacks. Numerous vulnerable factors increase security risks and cyber-attacks, including viruses, the internet, communications, and hackers. Internets of Things (IoT) devices are more effective, and the number of devices connected to the internet is constantly increasing, and governments and businesses are also using these technologies to perform business activities effectively. However, the increasing uses of technologies also increase risks, such as password attacks, social engineering, and phishing attacks. Humans play a major role in the field of cybersecurity. It is observed that more than 39% of security risks are related to the human factor, and 95% of successful cyber-attacks are caused by human error, with most of them being insider threats. The major human factor issue in cybersecurity is a lack of user awareness of cyber threats. This study focuses on the human factor by surveying the vulnerabilities and reducing the risk by focusing on human nature and reacting to different situations. This study highlighted that most of the participants are not experienced with cybersecurity threats and how to protect their personal information. Moreover, the lack of awareness of the top three vulnerabilities related to the human factor in cybersecurity, such as phishing attacks, passwords, attacks, and social engineering, are major problems that need to be addressed and reduced through proper awareness and training.     

Blockchain-Based SQKD and IDS in Edge Enabled Smart Grid Network

Smart Grid is a power grid that improves flexibility, reliability, and efficiency through smart meters. Due to extensive data exchange over the Internet, the smart grid faces many security challenges that have led to data loss, data compromise, and high power consumption. Moreover, the lack of hardware protection and physical attacks reduce the overall performance of the smart grid network. We proposed the BLIDSE model (Blockchain-based secure quantum key distribution and Intrusion Detection System in Edge Enables Smart Grid Network) to address these issues. The proposed model includes five phases: The first phase is blockchain-based secure user authentication, where all smart meters are first registered in the blockchain, and then the blockchain generates a secret key. The blockchain verifies the user ID and the secret key during authentication matches the one authorized to access the network. The secret key is shared during transmission through secure quantum key distribution (SQKD). The second phase is the lightweight data encryption, for which we use a lightweight symmetric encryption algorithm, named Camellia. The third phase is the multi-constraint-based edge selection; the data are transmitted to the control center through the edge server, which is also authenticated by blockchain to enhance the security during the data transmission. We proposed a perfect matching algorithm for selecting the optimal edge. The fourth phase is a dual intrusion detection system which acts as a firewall used to drop irrelevant packets, and data packets are classified into normal, physical errors and attacks, which is done by Double Deep Q Network (DDQN). The last phase is optimal user privacy management. In this phase, smart meter updates and revocations are done, for which we proposed Forensic based Investigation Optimization (FBI), which improves the security of the smart grid network. The simulation is performed using network simulator NS3.26, which evaluates the performance in terms of computational complexity, accuracy, false detection, and false alarm rate. The proposed BLIDSE model effectively mitigates cyber-attacks, thereby contributing to improved security in the network.