Challenges in Multi-Layer Data Security for Video Steganography Revisited

The importance of image security in the field of medical imaging is challenging. Several research works have been conducted to secure medical healthcare images. Encryption, not risking loss of data, is the right solution for image confidentiality. Due to data size limitations, redundancy, and capacity, traditional encryption techniques cannot be applied directly to e-health data, especially when patient data are transferred over the open channels. Therefore, patients may lose the privacy of data contents since images are different from the text because of their two particular factors of loss of data and confidentiality.Researchers have identified such security threats and have proposed several image encryption techniques to mitigate the security problem. However, the study has found that the existing proposed techniques still face application-specific several security problems. Therefore, this paper presents an efficient, lightweight encryption algorithm to develop a secure image encryption technique for the healthcare industry. The proposed lightweight encryption technique employs two permutation techniques to secure medical images. The proposed technique is analyzed, evaluated, and then compared to conventionally encrypted ones in security and execution time. Numerous test images have been used to determine the performance of the proposed algorithm. Several experiments show that the proposed algorithm for image cryptosystems provides better efficiency than conventional techniques.INDEX TERMS Internet of Medical Things, medical image encryption, lightweight encryption.

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“…(3). where MSE denotes the mean square error between the ground truth image and the encrypted image [56]. It calculated MSE using Eqn.…”

Section: Experimental Evaluation Of Proposed Techniquementioning

confidence: 99%

Lightweight Encryption Technique to Enhance Medical Image Security on Internet of Medical Things Applications

et al. 2021

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“…It is not possible to get the identical hash value for two separate messages. Secure Hash Functions (SHA-1 and SHA-256) and Message Digests (MD5) [25] are some of the popular hash encryption technologies employed in cloud computing, as shown in Figure 14.…”

Section: Hash Encryptionmentioning

confidence: 99%

Lightweight Cryptographic Algorithms for Guessing Attack Protection in Complex Internet of Things Applications

Hasan

Shafiq²,

Islam

et al. 2021

Complexity

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As the world keeps advancing, the need for automated interconnected devices has started to gain significance; to cater to the condition, a new concept Internet of Things (IoT) has been introduced that revolves around smart devicesʼ conception. These smart devices using IoT can communicate with each other through a network to attain particular objectives, i.e., automation and intelligent decision making. IoT has enabled the users to divide their household burden with machines as these complex machines look after the environment variables and control their behavior accordingly. As evident, these machines use sensors to collect vital information, which is then the complexity analyzed at a computational node that then smartly controls these devicesʼ operational behaviors. Deep learning-based guessing attack protection algorithms have been enhancing IoT security; however, it still has a critical challenge for the complex industries’ IoT networks. One of the crucial aspects of such systems is the need to have a significant training time for processing a large dataset from the networkʼs previous flow of data. Traditional deep learning approaches include decision trees, logistic regression, and support vector machines. However, it is essential to note that this convenience comes with a price that involves security vulnerabilities as IoT networks are prone to be interfered with by hackers who can access the sensor/communication data and later utilize it for malicious purposes. This paper presents the experimental study of cryptographic algorithms to classify the types of encryption algorithms into the asymmetric and asymmetric encryption algorithm. It presents a deep analysis of AES, DES, 3DES, RSA, and Blowfish based on timing complexity, size, encryption, and decryption performances. It has been assessed in terms of the guessing attack in real-time deep learning complex IoT applications. The assessment has been done using the simulation approach and it has been tested the speed of encryption and decryption of the selected encryption algorithms. For each encryption and decryption, the tests executed the same encryption using the same plaintext for five separate times, and the average time is compared. The key size used for each encryption algorithm is the maximum bytes the cipher can allow. To the comparison, the average time required to compute the algorithm by the three devices is used. For the experimental test, a set of plaintexts is used in the simulation—password-sized text and paragraph-sized text—that achieves target fair results compared to the existing algorithms in real-time deep learning networks for IoT applications.

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“…The handshake protocol allows the client and server to authenticate each other and to negotiate an encryption algorithm, MAC algorithms, and session keys for data encryption in the TLS record [17]. The TLS Record Protocol secures the connection after the TLS Handshake Protocol established using symmetric cryptography such as RC4 or AES [18] and hash functions like SHA-1 [19]. The operation is determined by the cipher suite which applied and its name represents the involved algorithms.…”

Section: B the Transport Layer Security (Tls) And Its Cipher Suitsmentioning

confidence: 99%

Lightweight Security Mechanism over MQTT Protocol for IoT Devices

Amanlou¹,

Bakar²

2020

IJACSA

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Security is one of the main concerns with regard to the Internet of Things (IoT) networks. Since most IoT devices are restricted in resource and power consumption, it is not easy to implement robust security mechanisms. There are different methods to secure network communications; however, they are not applicable to IoT devices. In addition, most authentication methods use certificates in which signing and verifying certificates need more computation and power. The main objective of this paper is to propose a lightweight authentication and encryption mechanism for IoT constrained devices. This mechanism uses ECDHE-PSK which is the Transport Layer Security (TLS) authentication algorithm over Message Queuing Telemetry Transport (MQTT) Protocol. This authentication algorithm provides a Perfect Forward Secrecy (PFS) feature that makes an improvement in security. It is the first time that this TLS authentication algorithm is implemented and evaluated over the MQTT protocol for IoT devices. To evaluate resource consumption of the proposed security mechanism, it was compared with the default security mechanism of the MQTT protocol and the ECDHE-ECDSA that is a certificate-based authentication algorithm. They were evaluated in terms of CPU utilization, execution time, bandwidth, and power consumption. The results show that the proposed security mechanism outperforms the ECDHE-ECDSA in all tests.

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Challenges in Multi-Layer Data Security for Video Steganography Revisited

Cited by 18 publications

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Lightweight Encryption Technique to Enhance Medical Image Security on Internet of Medical Things Applications

Lightweight Encryption Technique to Enhance Medical Image Security on Internet of Medical Things Applications

Lightweight Cryptographic Algorithms for Guessing Attack Protection in Complex Internet of Things Applications

Lightweight Security Mechanism over MQTT Protocol for IoT Devices

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