scholarly journals JLVEA: Lightweight Real-Time Video Stream Encryption Algorithm for Internet of Things

Sensors ◽  
2020 ◽  
Vol 20 (13) ◽  
pp. 3627 ◽  
Author(s):  
Junhyeok Yun ◽  
Mihui Kim

Along with the recent growth of Internet of Things (IoT) security camera market, there have been a number of personal information leakage incidents from security attacks targeting such cameras. Therefore, a permutation-based video encryption algorithm was proposed to secure video streams in low-performance processors such as IoT security cameras. However, existing permutation-based video encryption algorithms are vulnerable to known-plaintext attacks since they use the same permutation list for every frame. Moreover, situation deduction based on the color composition is possible. In this paper, we propose a new permutation-based video encryption algorithm that updates the permutation list for every frame using a crypto secure pseudo-random number generator without significantly increasing memory usage. By doing so, the algorithm becomes robust to known-plaintext attacks, which has been a common problem with existing permutation-based video encryption algorithms. In addition, color channel separation can prevent attackers from deducing situations through color composition. Pre-compression encryption is applied to make the algorithm robust to data loss because of packet loss. We implement the proposed algorithm and conduct an experiment to show its performance in terms of probability of data loss because of packet loss, encryption speed, and memory usage.

Author(s):  
Mourad Talbi ◽  
Med Salim Bouhalel

The IoT Internet of Things being a promising technology of the future. It is expected to connect billions of devices. The increased communication number is expected to generate data mountain and the data security can be a threat. The devices in the architecture are fundamentally smaller in size and low powered. In general, classical encryption algorithms are computationally expensive and this due to their complexity and needs numerous rounds for encrypting, basically wasting the constrained energy of the gadgets. Less complex algorithm, though, may compromise the desired integrity. In this paper we apply a lightweight encryption algorithm named as Secure IoT (SIT) to a quantized speech image for Secure IoT. It is a 64-bit block cipher and requires 64-bit key to encrypt the data. This quantized speech image is constructed by first quantizing a speech signal and then splitting the quantized signal into frames. Then each of these frames is transposed for obtaining the different columns of this quantized speech image. Simulations result shows the algorithm provides substantial security in just five encryption rounds.


Author(s):  
Norliza Katuk ◽  
Ikenna Rene Chiadighikaobi

Many previous studies had proven that The PRESENT algorithm is ultra-lightweight encryption. Therefore, it is suitable for use in an IoT environment. However, the main problem with block encryption algorithms like PRESENT is that it causes attackers to break the encryption key. In the context of a fingerprint template, it contains a header and many zero blocks that lead to a pattern and make it easier for attackers to obtain an encryption key. Thus, this research proposed header and zero blocks bypass method during the block pre-processing to overcome this problem. First, the original PRESENT algorithm was enhanced by incorporating the block pre-processing phase. Then, the algorithm’s performance was tested using three measures: time, memory usage, and CPU usage for encrypting and decrypting fingerprint templates. This study demonstrated that the proposed method encrypted and decrypted the fingerprint templates faster with the same CPU usage of the original algorithm but consumed higher memory. Thus, it has the potential to be used in IoT environments for security.


Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Mohammad Kamrul Hasan ◽  
Muhammad Shafiq ◽  
Shayla Islam ◽  
Bishwajeet Pandey ◽  
Yousef A. Baker El-Ebiary ◽  
...  

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.


2021 ◽  
Vol 39 (1B) ◽  
pp. 184-196
Author(s):  
Attaa R. Alawi ◽  
Nidaa F. Hassan

Video encrypting is one technique to protect digital videos, it used to avoid unwanted interference and viewing of the transmitted videos. In this paper, a new selective video cryptography algorithm is suggested using light stream algorithm. As it known video size is large in size and it consume time in the encryption process, ChaCha a light encryption algorithm has been used to reduce the encryption time, encryption is done by Xoring frames of video with the key generated from ChaCha algorithm, it produced an acceptable results from robustness point view, but still encryption process consumed time, thus to speed up this process, feature detection operator (FAST) is used to encrypt key points result from FAST operator, in addition key points from this is increased to optimized between speed and robustness of proposed algorithm. In evaluation process, some of measuring quality factors MSE, PSNR, Correlation, NPCR, UACI and entropy are specified for evaluating and comparing between two suggested encryption algorithms which gave good result in encryption process (ChaCha and ChaCha with FAST Enhancement). Experimental results have discovered that the current projected has less encrypting time and better encrypting influence.


Author(s):  
Er. Shikha Atwal ◽  
Dr. Umesh Kumar

With the emerging technology connected with the internet, there is one constant issue related to that is data security. The only solution with which this issue can be resolved at a limit and can be used to protect the data is various algorithms for encryption. Though different approaches were used for the same, Cryptography seems to be efficiently protecting the data while transmitting in network from sender to receiver. Firstly the data is encrypted before sending to receiver using the most secure and reliable encryption algorithm. Secondly, at the receiver end it can be decrypted using the same decryption algorithm. Only receiver will have the key with which the data can be decrypted. In this paper, AES, DSS and RSA algorithms were implemented. These algorithms are encryption algorithms which perform encoding and decoding of data, to be sent from sender to receiver, using the keys. Each have different criteria for encryption and are then compared based on different parameters viz. delay, throughput, PDR is an acronym for packet delivery ratio, PLR represents packet loss ratio and RPC denotes Received Packet Count. The results in the form of graphs are given to analyze the security provided by each algorithm.


Author(s):  
Mourad Talbi ◽  
Med Salim Bouhalel

The IoT Internet of Things being a promising technology of the future. It is expected to connect billions of devices. The increased communication number is expected to generate data mountain and the data security can be a threat. The devices in the architecture are fundamentally smaller in size and low powered. In general, classical encryption algorithms are computationally expensive and this due to their complexity and needs numerous rounds for encrypting, basically wasting the constrained energy of the gadgets. Less complex algorithm, though, may compromise the desired integrity. In this paper we apply a lightweight encryption algorithm named as Secure IoT (SIT) to a quantized speech image for Secure IoT. It is a 64-bit block cipher and requires 64-bit key to encrypt the data. This quantized speech image is constructed by first quantizing a speech signal and then splitting the quantized signal into frames. Then each of these frames is transposed for obtaining the different columns of this quantized speech image. Simulations result shows the algorithm provides substantial security in just five encryption rounds.


With the advent of digital world today, securing images across internet has become an important issue. There exist many image security techniques viz. steganography, encryption, watermarking etc. Image Encryption is one of such fruitful technique which encrypts an image using random secret key and stores the encrypted image on the server. There are many challenges of implementing image encryption algorithms such as higher computational complexity, loss of information during encryption, universality and applicability of algorithm, less scalability etc. Many image encryption algorithms are selective image encryption algorithm which works for specific part of image. It consists of encrypting only a subset of the data. The aim of selective encryption is to reduce the amount of data to encrypt while preserving a sufficient level of security. The selective encryption algorithms have a problem of scalability and data loss. The paper proposes a new algorithm Jumbling-Salting for images. The algorithm was earlier used in encryption passwords, text files, DNS, payment gateway data etc. An application is developed which incorporates the Jumbling salting encryption stategy for images.


Author(s):  
Qingtao Wu ◽  
Zaihui Cao

: Cloud monitoring technology is an important maintenance and management tool for cloud platforms.Cloud monitoring system is a kind of network monitoring service, monitoring technology and monitoring platform based on Internet. At present, the monitoring system is changed from the local monitoring to cloud monitoring, with the flexibility and convenience improved, but also exposed more security issues. Cloud video may be intercepted or changed in the transmission process. Most of the existing encryption algorithms have defects in real-time and security. Aiming at the current security problems of cloud video surveillance, this paper proposes a new video encryption algorithm based on H.264 standard. By using the advanced FMO mechanism, the related macro blocks can be driven into different Slice. The encryption algorithm proposed in this paper can encrypt the whole video content by encrypting the FMO sub images. The method has high real-time performance, and the encryption process can be executed in parallel with the coding process. The algorithm can also be combined with traditional scrambling algorithm, further improve the video encryption effect. The algorithm selects the encrypted part of the video data, which reducing the amount of data to be encrypted. Thus reducing the computational complexity of the encryption system, with faster encryption speed, improve real-time and security, suitable for transfer through mobile multimedia and wireless multimedia network.


2020 ◽  
Vol 8 (6) ◽  
pp. 5759-5764

Given the current use of the Internet, The most important thing is to provide security to the user's information. Many encryption algorithms already exist for this purpose. Here we discussed a new process called Mahaviracharya Encryption Standard. MES is a symmetric encryption algorithm. Here, this algorithm is cryptanalyzed, and compared with blowfish algorithm. MES algorithm can be used instead off algorithms like AES, Blowfish etc.


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