A Study on the Applications of the Biomedical Image Encryption Methods for Secured Computer Aided Diagnostics
01 Feb 2019-
TL;DR: In this work, some application of cryptographic methods have been discussed which are used to protect biomedical images from unwanted modifications and access and can be highly beneficial in future research in the field of biomedical image protection as well as multimedia data security.
Abstract: Computer aided diagnostic is one of the most active research area and has huge impact on the health care industry. With the advent of intelligent methods, biomedical data processing becomes easier and less error prone. Moreover, remote health care is also possible using the IoT infrastructure. However, data security over the network is always considered as a challenge. Biomedical data are generally sensitive to external disturbances and small manipulation in the data may cause huge difference in the ultimate result. Wrong diagnosis can be life threatening in some scenarios or can be severe in almost every instance. Therefore, biomedical data security is one of the major challenge and necessary for remote health care. In this work, some application of cryptographic methods have been discussed which are used to protect biomedical images from unwanted modifications and access. This work can be highly beneficial in future research in the field of biomedical image protection as well as multimedia data security.
Citations
More filters
01 Jan 2020
TL;DR: In this chapter, a comprehensive overview of the deep learning-assisted biomedical image analysis methods is presented and can be helpful for the researchers to understand the recent developments and drawbacks of the present systems.
Abstract: Biomedical image analysis methods are gradually shifting towards computer-aided solutions from manual investigations to save time and improve the quality of the diagnosis. Deep learning-assisted biomedical image analysis is one of the major and active research areas. Several researchers are working in this domain because deep learning-assisted computer-aided diagnostic solutions are well known for their efficiency. In this chapter, a comprehensive overview of the deep learning-assisted biomedical image analysis methods is presented. This chapter can be helpful for the researchers to understand the recent developments and drawbacks of the present systems. The discussion is made from the perspective of the computer vision, pattern recognition, and artificial intelligence. This chapter can help to get future research directions to exploit the blessings of deep learning techniques for biomedical image analysis.
28 citations
01 Jan 2020
TL;DR: This chapter proposes a new filter (kernel), and the compass operator is applied on it to detect edges more efficiently, and the results are compared with some of the previously proposed filters both qualitatively and quantitatively.
Abstract: Image segmentation has been an active topic of research for many years. Edges characterize boundaries, and therefore, detection of edges is a problem of fundamental importance in image processing. Edge detection in images significantly reduces the amount of data and filters out useless information while preserving the important structural properties in an image. Edges carry significant information about the image structure and shape, which is useful in various applications related with computer vision. In many applications, the edge detection is used as a pre-processing step. Edge detection is highly beneficial in automated cell counting, structural analysis of the image, automated object detection, shape analysis, optical character recognition, etc. Different filters are developed to find the gradients and detect edges. In this chapter, a new filter (kernel) is proposed, and the compass operator is applied on it to detect edges more efficiently. The results are compared with some of the previously proposed filters both qualitatively and quantitatively.
24 citations
17 Aug 2019
TL;DR: In this work, DNA encryption and its different approaches are discussed to give a brief overview on the data security methods based on DNA encryption.
Abstract: Security of the digital data is one of the major concerns of the today’s world. There are several methods for digital data security that can be found in the literature. Biological sequences have some features that make it worthy for the digital data security processes. In this work, DNA encryption and its different approaches are discussed to give a brief overview on the data security methods based on DNA encryption. This work can be highly beneficial for future research on DNA encryption and can be applied on different domains.
20 citations
17 Aug 2019
TL;DR: A secure and lossless encryption method is developed in this work and various numerical parameters are used to evaluate the performance of the proposed method which proves the effectiveness of the algorithm.
Abstract: Biomedical image analysis is an integral part of the modern healthcare industry and has a huge impact on the modern world. Automated computer-aided systems are highly beneficial for fast, accurate and efficient diagnosis of the biomedical images. Remote healthcare systems allow doctors and patients to perform their jobs from separate geographic locations. Moreover, expert opinion about a patient can be obtained from a doctor who is in a different country or in some distant location within stipulated amount of time. Remote healthcare systems require digital biomedical images to be transferred over the network. But several security threats are associated with the transmission of the biomedical images. Privacy of the patients must be preserved by keeping the images safe from any unauthorized access. Moreover, the contents of the biomedical images must be preserved efficiently so that no one can tamper it. Data tampering can produce drastic results in many cases. In this work, a method for biomedical image security has been proposed. DNA encryption method is one of the emerging methods in the field of cryptography. A secure and lossless encryption method is developed in this work. Various numerical parameters are used to evaluate the performance of the proposed method which proves the effectiveness of the algorithm.
15 citations
TL;DR: The proposed encryption framework provides a potential way to realize DNA-strand-displacement-based encryption via biological experiments and promotes the research on DNA- Strand-Displacement -based encryption.
Abstract: DeoxyriboNucleic Acid (DNA) encryption is a new encryption method that appeared along with the research of DNA nanotechnology in recent years. Due to the complexity of biology in DNA nanotechnology, DNA encryption brings in an additional difficulty in deciphering and, thus, can enhance information security. As a new approach in DNA nanotechnology, DNA strand displacement has particular advantages such as being enzyme free and self-assembly. However, the existing research on DNA-strand-displacement-based encryption has mostly stayed at a theoretical or simulation stage. To this end, this paper proposes a new DNA-strand-displacement-based encryption framework. This encryption framework involves three main strategies. The first strategy was a tri-phase conversion from plaintext to DNA sequences according to a Huffman-coding-based transformation rule, which enhances the concealment of the information. The second strategy was the development of DNA strand displacement molecular modules, which produce the initial key for information encryption. The third strategy was a cyclic-shift-based operation to extend the initial key long enough, and thus increase the deciphering difficulty. The results of simulation and biological experiments demonstrated the feasibility of our scheme for encryption. The approach was further validated in terms of the key sensitivity, key space, and statistic characteristic. Our encryption framework provides a potential way to realize DNA-strand-displacement-based encryption via biological experiments and promotes the research on DNA-strand-displacement-based encryption.
11 citations
References
More filters
TL;DR: A novel method for cell segmentation and identification has been proposed that incorporated marking cells in cuckoo search (CS) algorithm and experimental results established that the Kapur's entropy segmentation method based on the modified CS required the least computational time.
Abstract: Microscopic image analysis is one of the challenging tasks due to the presence of weak correlation and different segments of interest that may lead to ambiguity It is also valuable in foremost meadows of technology and medicine Identification and counting of cells play a vital role in features extraction to diagnose particular diseases precisely Different segments should be identified accurately in order to identify and to count cells in a microscope image Consequently, in the current work, a novel method for cell segmentation and identification has been proposed that incorporated marking cells Thus, a novel method based on cuckoo search after pre-processing step is employed The method is developed and evaluated on light microscope images of rats' hippocampus which used as a sample for the brain cells The proposed method can be applied on the color images directly The proposed approach incorporates the McCulloch's method for levy flight production in cuckoo search (CS) algorithm Several objective functions, namely Otsu's method, Kapur entropy and Tsallis entropy are used for segmentation In the cuckoo search process, the Otsu's between class variance, Kapur's entropy and Tsallis entropy are employed as the objective functions to be optimized Experimental results are validated by different metrics, namely the peak signal to noise ratio (PSNR), mean square error, feature similarity index and CPU running time for all the test cases The experimental results established that the Kapur's entropy segmentation method based on the modified CS required the least computational time compared to Otsu's between-class variance segmentation method and the Tsallis entropy segmentation method Nevertheless, Tsallis entropy method with optimized multi-threshold levels achieved superior performance compared to the other two segmentation methods in terms of the PSNR
94 citations
16 Apr 2007
TL;DR: This work discusses the information security technology in DNA computing, a new field of cryptography arising with DNA computing research in recent years that can realize several security technologies such as encryption, steganography, signature and authentication by using DNA molecular as information medium.
Abstract: DNA computing is a new method of simulating biomolecular structure of DNA and computing by means of molecular biology technological computation. It introduces a fire-new data structure and calculating method, providing a new way for solving the NP-complete problem. It is a new computational method by harnessing the enormous parallel computing ability and high memory density of bio-molecules, which brings potential challenges and opportunities to traditional cryptography. DNA cryptography is a new field of cryptography arising with DNA computing research in recent years. It can realize several security technologies such as encryption, steganography, signature and authentication by using DNA molecular as information medium. We firstly introduce the basic idea of DNA computing, and then discuss the information security technology in DNA computing.
51 citations
"A Study on the Applications of the ..." refers background in this paper
...DNA encryption is one of recent branch of cryptography that uses parallel computing environment [47], [48]....
[...]
TL;DR: Experiments and analyses demonstrate that high embedding capacity and low distortion have been achieved in the process of data hiding, and, at the same time, high security has been acquired in the encryption phase.
Abstract: An encryption frame of medical image with watermark based on hyperchaotic system is proposed in this paper. Medical information, such as the patients’ private information, data needed for diagnosis, and information for authentication or protection of medical files, is embedded into the regions of interest (ROI) in medical images with a high capacity difference-histogram-based reversible data-hiding scheme. After that, the watermarked medical images are encrypted with hyperchaotic systems. In the receiving end, the receiver with encryption key can decrypt the image to get similar images for diagnosis. If the receiver has the key for data hiding at the same time, he/she can extract the embedded private information and reversibly recover the original medical image. Experiments and analyses demonstrate that high embedding capacity and low distortion have been achieved in the process of data hiding, and, at the same time, high security has been acquired in the encryption phase.
42 citations
Additional excerpts
...A hyper chaotic system based hybrid system is proposed in [34]....
[...]
TL;DR: DNA algorithm based substitution is used for spatial domain bit permutation for generating a pseudorandom bit sequence and a final layer of security is imposed to make this process more fault tolerant.
Abstract: Presently, there is a growth in the transmission of image and video data. Security becomes a main issue. Very strong image cryptographic techniques are a solution to this problem. There is a use of a randomly generated public key and based on that there is an application of DNA algorithm. In the proposed method DNA algorithm based substitution is used for spatial domain bit permutation. Here the chaotic logistic map is used for generating a pseudorandom bit sequence. We have generated 48bit length sequences for every pixel. After the substitution operation, a final layer of security is imposed to make this process more fault tolerant. The For checking the strength of the work a series of tests are performed and various parameters are checked like Correlation Coefficient Analysis, analysis of NPCR and UACI values etc.
40 citations
"A Study on the Applications of the ..." refers background in this paper
...Chaos is one of the latest concept inherited from mathematics which are extensively used in cryptography [32]....
[...]
01 Jan 2015
TL;DR: In this article, the authors presented an algorithm based on simulated annealing method to solve the job shop scheduling problem, which is an approximation algorithm for finding the minimum makespan in a job shop.
Abstract: The Job Shop Scheduling Problem (known as JSSP) is a wellknown and one of the difficult combinatorial optimization problems and treated as a member of NP-complete problem class. This paper presents an algorithm based on Simulated Annealing method to solve the Job Shop Scheduling problem. It is an approximation algorithm for finding the minimum makespan in a job shop. The proposed algorithm is based on Roulette wheel selection and simulated annealing, a generalization of the well known and effective iterative improvement approach for combinatorial optimization problems. The generalization involves the acceptance of cost-increasing transitions with a nonzero probability to avoid getting stuck in local minima. The problem studied in this research focuses on the sequencing of operations and allocation of operation to the machine under some sequence constraint.
39 citations