Gunasekaran Manogaran

A survey of big data architectures and machine learning algorithms in healthcare

Big Data has gained much attention from researchers in healthcare, bioinformatics, and information sciences. As a result, data production at this stage will be 44 times greater than that in 2009. Hence, the volume, velocity, and variety of data rapidly increase. Hence, it is difficult to store, process and visualise this huge data using traditional technologies. Many organisations such as Twitter, LinkedIn, and Facebook are used big data for different use cases in the social networking domain. Also, implementations of such architectures of the use cases have been published worldwide. However, a conceptual architecture for specific big data application has been limited. The intention of this paper is application-oriented architecture for big data systems, which is based on a study of published big data architectures for specific use cases. This paper also provides an overview of the state-of-the-art machine learning algorithms for processing big data in healthcare and other applications.

HIoTPOT: Surveillance on IoT Devices against Recent Threats

Honeypot Internet of Things (IoT) (HIoTPOT) keep a secret eye on IoT devices and analyzes the various recent threats which are dangerous to IoT devices. In this paper, implementation of a research honeypot is presented which is used to learn the recent tactics and ethics used by black hat community to attack on IoT devices. As IoT is open and easy for accessing, all the intruders are highly attracted towards IoT. Recently Telnet based attacks are very famous on IoT devices to get easy access and attack on other devices. To reduce these kinds of threats, it is necessary to know in details about intruder, therefore the aim of this research work is to implement novel based secret eye server known as HIoTPOT which will make the IoT environment more safe and secure.

Secure Disintegration Protocol for Privacy Preserving Cloud Storage

Cloud service providers offer infrastructure, network services, and software applications in the cloud. The cloud services are hosted in a data center that can be used by users with the help of network connectivity. Hence, there is a need for providing security and integrity in cloud resources. Most security instruments have a finite rate of failure, and the intrusion comes with more complex and sophisticated techniques; the security failure rates are skyrocketing. In this paper, we have proposed a secure disintegration protocol (SDP) for the protection of privacy on-site and in the cloud. The architecture presented in this paper is used for cloud storage, and it is used in conjunction with our unique data compression and encoding technique. Probabilistic analysis is used for calculating the intrusion tolerance abilities for the SDP.

A hybrid whale optimization algorithm based on local search strategy for the permutation flow shop scheduling problem

Abstract The flow shop scheduling problem is one of the most important types of scheduling with a large number of real-world applications. In this paper, we propose a new algorithm that integrates the Whale Optimization Algorithm (WOA) with a local search strategy for tackling the permutation flow shop scheduling problem. The Largest Rank Value (LRV) requires the algorithm to deal with the discrete search space of the problem. The diversity of candidate schedules is improved using a swap mutation operation as well. In addition to the insert-reversed block operation is adopted to escape from the local optima. The proposed hybrid whale algorithm (HWA) is incorporated with Nawaz–Enscore–Ham (NEH) to improve the performance of the algorithm. It is observed that HWA gives competitive results compared to the existing algorithms.

Score level based latent fingerprint enhancement and matching using SIFT feature

Latent fingerprint identification is such a difficult task to law enforcement agencies and border security in identifying suspects. It is a too complicate due to poor quality images with non-linear distortion and complex background noise. Hence, the image quality is required for matching those latent fingerprints. The current researchers have been working based on minutiae points for fingerprint matching because of their accuracy are acceptable. In an effort to extend technology for fingerprint matching, our model is to propose the enhancementand matching for latent fingerprints using Scale Invariant Feature Transformation (SIFT). It has involved in two phases (i) Latent fingerprint contrast enhancement using intuitionistic type-2 fuzzy set (ii) Extract the SIFTfeature points from the latent fingerprints. Then thematching algorithm is performedwith n- number of images and scoresare calculated by Euclidean distance. We tested our algorithm for matching, usinga public domain fingerprint database such as FVC-2004 and IIIT-latent fingerprint. The experimental consequences indicatethe matching result is obtained satisfactory compare than minutiae points.

An improved nature inspired meta-heuristic algorithm for 1-D bin packing problems

Bin packing problem (BPP) is a classical combinatorial optimization problem widely used in a wide range of fields. The main aim of this paper is to propose a new variant of whale optimization algorithm named improved Lévy-based whale optimization algorithm (ILWOA). The proposed ILWOA adapts it to search the combinatorial search space of BPP problems. The performance of ILWOA is evaluated through two experiments on benchmarks with varying difficulty and BPP case studies. The experimental results confirm the prosperity of the proposed algorithm in proficiency to find the optimal solution and convergence speed. Further, the obtained results are discussed and analyzed according to the problem size.

A hybrid approach of neutrosophic sets and DEMATEL method for developing supplier selection criteria

For any organization, the selection of suppliers is a very important step to increase productivity and profitability. Any organization or company seeks to use the best methodology and the appropriate technology to achieve its strategies and objectives. The present study employs the neutrosophic set for decision making and evaluation method (DEMATEL) to analyze and determine the factors influencing the selection of SCM suppliers. DEMATEL is considered a proactive approach to improve performance and achieve competitive advantages. This study applies the neutrosophic set Theory to adjust general judgment, using a new scale to present each value. A case study implementing the proposed methodology is presented (i.e. selecting the best supplier for a distribution company). This research was designed by neutrosophic DEMATEL data collection survey of experts, interviewing professionals in management, procurement and production. The results analyzed in our research prove that quality is the most influential criterion in the selection of suppliers.

Internet of Things (IoT) and its impact on supply chain: A framework for building smart, secure and efficient systems

Abstract The traditional supply chains faces several challenges such as uncertainty, cost, complexity and vulnerable problems. To overcome these problems the supply chains must be more smarter. For establishing a large-scale of smart infrastructure to merge data, information, products, physical objects and all processes of supply chain, we applies the internet of things (IOT) in supply chain management (SCM) through building a smart and secure system of SCM. We have prepared a website for suppliers and managers. We tracked the flow of products at each stage in supply chain management through the Radio Frequency Identification (RFID) technology. Each product attached with RFID tag and scanned through RFID reader and ESP8266 at each phase of supply chain management. After scanning the tag we stores tag id in the database. All information about products will be entered by suppliers and then uploaded to managers. In our system the supplier and manager gets perfect information of the entire life cycle of goods, and this will achieve transparency of supply chain management. For assessing security criteria of proposed system of supply chain management, we also proposed a framework which integrates neutrosophic Decision Making Trial and Evaluation Laboratory (N-DEMATEL) technique with analytic hierarchy process (AHP). The neutrosophic Decision Making Trial and Evaluation Laboratory (N-DEMATEL) technique is utilized to infer cause and effect interrelationships among criteria of smart supply chain security requirements. Depending on obtained information from (N-DEMATEL) the neutrosophic AHP is utilized to calculate weight of criteria and sub-criteria. Then the integrated framework will help researchers and practitioners to design secure system of supply chains. We presented DEMATEL and AHP in neutrosophic environment to deal effectively with vague, uncertain and incomplete information. So the proposed system of supply chain management will be able to overcome all challenges of traditional SCM and provide secure environment of SCM processes.

Paillier homomorphic cryptosystem with poker shuffling transformation based water marking method for the secured transmission of digital medical images

Digital watermarking is a technique that provides security and authentication for digital image transmission. In general, patient reports are stored in the form of a medical image. A medical image shared through the Internet can be easily modified by an unauthorized user. In order to overcome this risk, we have proposed a method, namely, Paillier homomorphic cryptosystem with poker shuffling transformation-based watermarking method for ensuring security for the digital medical images. In this paper, the watermarking process initially is done at an encrypted DWT-DCT domain. Paillier homomorphic cryptosystem is used for encrypting the original image. The watermark image is scrambled using poker shuffling transformation to generate the scrambled image. This is followed by the encryption of the scrambled image. The embedding process is used for generating an encrypted watermark image. The extraction process involves the decryption of encrypted watermark image for getting the original and the watermark image. The medical data is collected from the private hospitals. The experimental results have established the improvement in the robustness of our proposed watermarking system in an encrypted DWT-DCT domain apart from providing security for the digital image transmission.

Three-way decisions based on neutrosophic sets and AHP-QFD framework for supplier selection problem

Abstract The neutrosophic set is an excellent tool for dealing with vague and inconsistent information effectively. Consequently, by studying the concept of three-way decisions based on neutrosophic set, we can find a suitable manner to take a reasonable decision. In this article, we suggest two rules of three-way decisions based on three membership degrees of neutrosophic set. A new evaluation function is presented to calculate weights of alternatives, for choosing the best one. We also study a supplier selection problem (selecting suppliers to obtain the indispensable materials for assisting the outputs of companies). The best suppliers need to be selected to enhance quality, service, to reduce cost, and to control time. The most widely used technique for determining the requirements of a company is the Quality Function Deployment (QFD). Since traditional QFD technique does not prioritize stakeholders’ requirements and fails to deal with vague and inconsistent information, this research also integrates it with Analytic Hierarchy Process (AHP) depending on neutrosophic environment. A case study is presented to illustrate the effectiveness of the proposed model.