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Purpose: This study explores the perspectives of data experts (DXs) and refugees on the algorithms used by law enforcement officers and focuses on emerging insecurities. The authors take police risk-scoring algorithms (PRSA) as a proxy to examine perceptions on algorithms that make/assist sensitive decisions affecting people’s lives.

Methodology/approach: In-depth interviews were conducted with DXs (24) in Estonia and refugees (19) in Estonia and Turkey. Using projective techniques, the interviewees were provided a simple definition of PRSA and a photo to encourage them to share their perspectives. The authors applied thematic analysis to the data combining manual and computer-aided techniques using the Maxqda software.

Findings: The study revealed that the perspectives on PRSA may change depending on the individual’s position relative to the double security paradox surrounding refugees. The use of algorithms for a sensitive matter such as security raises concerns about potential social outcomes, intentions of authorities and fairness of the algorithms. The algorithms are perceived to construct further social borders in society and justify extant ideas about marginalized groups.

Research limitations: The study made use of a small population sample and aimed at exploring perspectives of refugees and DXs by taking PRSA as the case without targeting representativeness.

Originality/value: The study is based on a double security paradox where refugees who escape their homelands due to security concerns are also considered to be national security threats. DXs, on the other hand, represent a group that takes an active role in decisions about who is at risk and who is risky. The study provides insights on two groups of people who are engaged with algorithms in different ways.

In this study, we analyze the power of the individual return-to-volatility security performance heuristic (ri/stdi) to simplify the identification of securities to buy and, consequently, to form the optimal no short sales mean–variance portfolios. The heuristic ri/stdi is powerful enough to identify the long and shorts sets. This is due to the positive definiteness of the variance–covariance matrix – the key is to use the heuristic sequentially. At the investor level, the heuristic helps investors to decide what securities to consider first. At the portfolio level, the heuristic may help us find out whether it is a good idea to invest in equity to begin with. Our research may also help to integrate individual security analysis into portfolio optimization through improved security rankings.

In the cloud-computing environment, privacy preservation and enabling security to the cloud data is a crucial and demanding task. In both the commercial and academic world, the privacy of important and sensitive data needs to be safeguarded from unauthorized users to improve its security. Therefore, several key generations, encryption and decryption algorithms are developed for data privacy preservation in the cloud environment. Still, the outsourced data remains with the problems like minimum data security, time consumption and increased computational complexity. The purpose of this research study is to develop an effective cryptosystem algorithm to secure the outsourced data with minimum computational complexity.

A new cryptosystem algorithm is proposed in this paper to address the above-mentioned concerns. The introduced cryptosystem algorithm has combined the ElGamal algorithm and hyperchaotic sequence, which effectively encrypts the outsourced data and diminishes the computational complexity of the system.

In the resulting section, the proposed improved ElGamal cryptosystem (IEC) algorithm performance is validated using the performance metrics like encryption time, execution time, decryption time and key generation comparison time. The IEC algorithm approximately reduced 0.08–1.786 ms of encryption and decryption time compared to the existing model: secure data deletion and verification.

The IEC algorithm significantly enhances the data security in cloud environments by increasing the power of key pairs. In this manuscript, the conventional ElGamal algorithm is integrated with the pseudorandom sequences for a pseudorandom key generation for improving the outsourced cloud data security.

Cloud eases information processing, but it holds numerous risks, including hacking and confidentiality problems. It puts businesses at risk in terms of data security and compliance. This paper aims to maximize the covered human resource (HR) vulnerabilities and minimize the security costs in the enterprise cloud using a fuzzy-based method and firefly optimization algorithm.

Cloud computing provides a platform to improve the quality and availability of IT resources. It changes the way people communicate and conduct their businesses. However, some security concerns continue to derail the expansion of cloud-based systems into all parts of human life. Enterprise cloud security is a vital component in ensuring the long-term stability of cloud technology by instilling trust. In this paper, a fuzzy-based method and firefly optimization algorithm are suggested for optimizing HR vulnerabilities while mitigating security expenses in organizational cloud environments. MATLAB is employed as a simulation tool to assess the efficiency of the suggested recommendation algorithm. The suggested approach is based on the firefly algorithm (FA) since it is swift and reduces randomization throughout the lookup for an optimal solution, resulting in improved performance.

The fuzzy-based method and FA unveil better performance than existing met heuristic algorithms. Using a simulation, all the results are verified. The study findings showed that this method could simulate complex and dynamic security problems in cloud services.

The findings may be utilized to assist the cloud provider or tenant of the cloud infrastructure system in taking appropriate risk mitigation steps.

Using a fuzzy-based method and FA to maximize the covered HR vulnerabilities and minimize the security costs in the enterprise cloud is the main novelty of this paper.

In the past recent years, wireless sensor network (WSN) has progressively grown as an emerging technology. Various research efforts have been made in the literature to address the problem associated with WSN security. Based on the review analysis, it is found that the existing methods are mostly associated with complex security operations that are not suitable for resource constraint sensor nodes. The proposed paper has presented cost-effective modeling of the security framework that addresses the problem of security and energy in WSN.

The proposed security framework implements two different protocols to attain maximum security services and optimizes the security operation of the proposed security models to achieve higher energy efficiency and privacy preservation against a majority of the lethal attacks. The first security model introduces a novel cost-efficient pairwise key-based authentication mechanism to identify the availability of optimal routes under the presence of adversary in the network. The second security model introduces an integrated part of the first security model that optimizes security operation to perform secure communication using a lightweight encryption mechanism.

Based on the experimental outcome and analysis, the proposed system attains a 60% performance improvement in terms of security and computational efficiency compared to the existing Sec-LEACH. The second security model has achieved a 50% improvement in terms of overall aspects like reduction in transmission delay, packet delivery ratio, remaining energy and communication performance.

The proposed study has presented a computationally efficient model that provides lightweight security operations based on secure hash function. It also focuses on the security associations between WSN nodes and the selection of reliable routes for secure data transmission. The design of the proposed security model is best suited for homogeneous and heterogeneous sensor networks, which will be robust to any attacking scenario.

The purpose of this paper is to apply security policies over the mobile ad hoc networks. A mobile ad hoc network refers to infrastructure-less, persistently self-designing systems; likewise, there is a noteworthy innovation that supplies virtual equipment and programming assets according to the requirement of mobile ad hoc network.

It faces different execution and effectiveness-based difficulties. The major challenge is the compromise of performance because of unavailable resources with respect to the MANET. In order to increase the MANET environment’s performance, various techniques are employed for routing and security purpose. An efficient security module requires a quality-of-service (QoS)-based security policy. It performs the task of routing and of the mobile nodes, and it also reduces the routing cost by finding the most trusted node.

The experimental results specify that QoS-based security policy effectively minimizes the cost, response time as well as the mobile makespan (routing cost and response time) of an application with respect to other existing approaches.

In this paper, the authors proposed an enhancement of Cross Centric Intrusion Detection System named as PIHNSPRA Routing Algorithm (PIHNSPRA).

It maps the security with the secure IDS communication and distributes the packets among different destinations, based on priority. This calculation is proposed for the purpose of routing and security by considering greatest throughput with least routing cost and reaction time.

When the concept is applied to practical applications. Quality of Service introduced in the proposed research reduces the cost of routing and improves the throughput.

The proposed calculation is tested by NS2 simulator and the outcomes showed that the execution of the calculation is superior to other conventional algorithms.

Privacy and security of personal data is the prime concern in any communication. Security algorithms play a crucial role in privacy preserving and are used extensively. Therefore, these algorithms need to be effective as well as energy-efficient. Advanced Encryption Standards (AES) is one of the efficient security algorithms. The principal purpose of this research is to design Energy efficient implementation of AES, as it is one of the important aspects for a step toward green computing.

This paper presents a low voltage complementary metal oxide semiconductor (LVCMOS) based energy efficient architecture for AES encryption algorithm on Field Programmable Gate Array (FPGA) platform. The experiments are performed for five different FPGAs at different input/output standards of LVCMOS. Experiments are performed separately at two frequencies (default and 1.6 GHz).

The comparative study of total on-chip power consumption for different frequency suggested that LVCMOS12 performed best for all the FPGAs. Also, Kintex-7 Low Voltage was found to be the best performing FPGA. At 1.6 GHz frequency, the authors observed 55% less on-chip power consumption when switched from Artix-7 with LVCMOS33 (maximum power consuming combination) to Kintex-7 Low Voltage with LVCMOS12. Mathematical models are developed for the proposed design.

The green implementation of AES algorithm based on LVCMOS standards has not been explored yet by researchers. The energy efficient implementation of AES will certainly be beneficial for society as it will consume less power and dissipate lesser heat to environment.

As the number of devices that connect to the Internet of Things (IoT) has grown, privacy and security issues have come up. Because IoT devices collect so much sensitive information, like user names, locations, phone numbers and even how they usually use energy, it is very important to protect users' privacy and security. IoT technology will be hard to use on the client side because IoT-enabled devices do not have clear privacy and security controls.

IoT technology would be harder to use on the client side if the IoT did not offer enough well-defined ways to protect users’ privacy and security. The goal of this research is to protect people's privacy in the IoT by using the oppositional artificial flora optimization (EGPKC-OAFA) algorithm to generate the best keys for the ElGamal public key cryptosystem (EGPKC). The EGPKC-OAFA approach puts the most weight on the IEEE 802.15.4 standard for MAC, which is the most important part of the standard. The security field is part of the MAC header of this standard. In addition, the MAC header includes EGPKC, which makes it possible to make authentication keys as quickly as possible.

With the proliferation of IoT devices, privacy and security have become major concerns in the academic world. Security and privacy are of the utmost importance due to the large amount of personally identifiable information acquired by IoT devices, such as name, location, phone numbers and energy use. Client-side deployment of IoT technologies will be hampered by the absence of well-defined privacy and security solutions afforded by the IoT. The purpose of this research is to present the EGPKC with optimum key generation using the EGPKC-OAFA algorithm for the purpose of protecting individual privacy within the context of the IoT. The EGPKC-OAFA approach is concerned with the MAC standard defined by the IEEE 802.15.4 standard, which includes the security field in its MAC header. Also, the MAC header incorporates EGPKC, which enables the fastest possible authentication key generation. In addition, the best methodology award goes to the OAFA strategy, which successfully implements the optimum EGPKC selection strategy by combining opposition-based (OBL) and standard AFA ideas. The EGPKC-OAFA method has been proved to effectively analyze performance in a number of simulations, with the results of various functions being identified.

In light of the growing prevalence of the IoT, an increasing number of people are becoming anxious about the protection and confidentiality of the personal data that they save online. This is especially true in light of the fact that more and more things are becoming connected to the internet. The IoT is capable of gathering personally identifiable information such as names, addresses and phone numbers, as well as the quantity of energy that is used. It will be challenging for customers to adopt IoT technology because of worries about the security and privacy of the data generated by users. In this work, the EGPKC is paired with adversarial artificial flora, which leads in an increase to the privacy security provided by EGPKC for the IoT (EGPKC-OAFA). The MAC security field that is part of the IEEE 802.15.4 standard is one of the areas that the EGPKC-OAFA protocol places a high focus on. The Authentication Key Generation Protocol Key Agreement, also known as EGPKCA, is used in MAC headers. The abbreviation for this protocol is EGPKCA. The OAFA technique, also known as the combination of OBL and AFA, is the most successful method for selecting EGPKCs. This method is recognized by its acronym, OAFA. It has been shown via a variety of simulations that the EGPKC-OAFA technique is a very useful instrument for carrying out performance analysis.

The purpose of this study is to test the Internet of things (IoT) devices with respect to reliability and quality.

In this paper, the authors have presented the analysis on design metrics such as perception, communication and computation layers for a constrained environment. In this paper, based on their literature survey, the authors have also presented a study that shows multipath routing is more efficient than single-path, and the retransmission mechanism is not preferable in an IoT environment.

This paper discusses the reliability of various layers of IoT subject methodologies used in those layers. The authors ran performance tests on Arduino nano and raspberry pi using the AES-128 algorithm. It was empirically determined that the time required to process a message increases exponentially and is more than what benchmark time estimates as the message size is increased. From these results, the authors can accurately determine the optimal size of the message that can be processed by an IoT system employing controllers, which are running 8-bit or 64-bit architectures.

The authors have tested the performance of standard security algorithms on different computational architectures and discuss the implications of the results. Empirical results demonstrate that encryption and decryption times increase nonlinearly rather than linearly as message size increases.

The purpose of this paper is to increase the degree of automation within information security compliance projects by introducing a formal representation of the ISO 27002 standard. As information is becoming more valuable and the current businesses face frequent attacks on their infrastructure, enterprises need support at protecting their information-based assets.

Information security standards and guidelines provide baseline knowledge for protecting corporate assets. However, the efforts to check whether the implemented measures of an organization adhere to the proposed standards and guidelines are still significantly high.

This paper shows how the process of compliance checking can be supported by using machine-readable ISO 27002 control descriptions in combination with a formal representation of the organization’s assets.

The authors created a formal representation of the ISO 27002 standard and showed how a security ontology can be used to increase the efficiency of the compliance checking process.