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2022-06-30
Wu, Kaijun, Li, Wenqin.  2021.  Multi image cross hybrid encryption method based on combined chaotic system. 2021 International Conference on Intelligent Transportation, Big Data & Smart City (ICITBS). :681—685.
In order to improve the security and encryption efficiency of multi image cross hybrid encryption, a multi image cross hybrid encryption method based on combined chaotic system is proposed. On the basis of chaos theory, the characteristics of Logistic chaotic system and Lorenz chaotic system are analyzed, and Logistic chaotic system and Lorenz chaotic system are combined to form a combined chaotic system. In order to improve the security of multi image encryption, the plaintext image is preprocessed before encryption. The preprocessing process is embedding random number sequence in the plaintext image. Based on the random number embedded image, the combined chaotic system is applied to the multi image cross chaotic encryption method. Experimental results show that the proposed method has high encryption security and high encryption efficiency.
2021-03-29
Feng, G., Zhang, C., Si, Y., Lang, L..  2020.  An Encryption and Decryption Algorithm Based on Random Dynamic Hash and Bits Scrambling. 2020 International Conference on Communications, Information System and Computer Engineering (CISCE). :317–320.
This paper proposes a stream cipher algorithm. Its main principle is conducting the binary random dynamic hash with the help of key. At the same time of calculating the hash mapping address of plaintext, change the value of plaintext through bits scrambling, and then map it to the ciphertext space. This encryption method has strong randomness, and the design of hash functions and bits scrambling is flexible and diverse, which can constitute a set of encryption and decryption methods. After testing, the code evenness of the ciphertext obtained using this method is higher than that of the traditional method under some extreme conditions..
2020-09-28
Chen, Lvhao, Liao, Xiaofeng, Mu, Nankun, Wu, Jiahui, Junqing, Junqing.  2019.  Privacy-Preserving Fuzzy Multi-Keyword Search for Multiple Data Owners in Cloud Computing. 2019 IEEE Symposium Series on Computational Intelligence (SSCI). :2166–2171.
With cloud computing's development, more users are decide to store information on the cloud server. Owing to the cloud server's insecurity, many documents should be encrypted to avoid information leakage before being sent to the cloud. Nevertheless, it leads to the problem that plaintext search techniques can not be directly applied to the ciphertext search. In this case, many searchable encryption schemes based on single data owner model have been proposed. But, the actual situation is that users want to do research with encrypted documents originating from various data owners. This paper puts forward a privacy-preserving scheme that is based on fuzzy multi-keyword search (PPFMKS) for multiple data owners. For the sake of espousing fuzzy multi-keyword and accurate search, secure indexes on the basis of Locality-Sensitive Hashing (LSH) and Bloom Filter (BF)are established. To guarantee the search privacy under multiple data owners model, a new encryption method allowing that different data owners have diverse keys to encrypt files is proposed. This method also solves the high cost caused by inconvenience of key management.
2020-01-07
Sakr, Ahmed S., El–kafrawy, P M., Abdullkader, Hatem M., Ibrahem, Hani M..  2018.  An Efficient Framework for Big Data Security Based on Selection Encryption on Amazonec2. 2018 1st International Conference on Computer Applications Information Security (ICCAIS). :1-5.

With the wide use of smart device made huge amount of information arise. This information needed new methods to deal with it from that perspective big data concept arise. Most of the concerns on big data are given to handle data without concentrating on its security. Encryption is the best use to keep data safe from malicious users. However, ordinary encryption methods are not suitable for big data. Selective encryption is an encryption method that encrypts only the important part of the message. However, we deal with uncertainty to evaluate the important part of the message. The problem arises when the important part is not encrypted. This is the motivation of the paper. In this paper we propose security framework to secure important and unimportant portion of the message to overcome the uncertainty. However, each will take a different encryption technique for better performance without losing security. The framework selects the important parts of the message to be encrypted with a strong algorithm and the weak part with a medium algorithm. The important of the word is defined according to how its origin frequently appears. This framework is applied on amazon EC2 (elastic compute cloud). A comparison between the proposed framework, the full encryption method and Toss-A-Coin method are performed according to encryption time and throughput. The results showed that the proposed method gives better performance according to encryption time, throughput than full encryption.

2019-08-12
Nevriyanto, A., Sutarno, S., Siswanti, S. D., Erwin, E..  2018.  Image Steganography Using Combine of Discrete Wavelet Transform and Singular Value Decomposition for More Robustness and Higher Peak Signal Noise Ratio. 2018 International Conference on Electrical Engineering and Computer Science (ICECOS). :147-152.

This paper presents an image technique Discrete Wavelet Transform and Singular Value Decomposition for image steganography. We are using a text file and convert into an image as watermark and embed watermarks into the cover image. We evaluate performance and compare this method with other methods like Least Significant Bit, Discrete Cosine Transform, and Discrete Wavelet Transform using Peak Signal Noise Ratio and Mean Squared Error. The result of this experiment showed that combine of Discrete Wavelet Transform and Singular Value Decomposition performance is better than the Least Significant Bit, Discrete Cosine Transform, and Discrete Wavelet Transform. The result of Peak Signal Noise Ratio obtained from Discrete Wavelet Transform and Singular Value Decomposition method is 57.0519 and 56.9520 while the result of Mean Squared Error is 0.1282 and 0.1311. Future work for this research is to add the encryption method on the data to be entered so that if there is an attack then the encryption method can secure the data becomes more secure.

2019-05-20
Dey, H., Islam, R., Arif, H..  2019.  An Integrated Model To Make Cloud Authentication And Multi-Tenancy More Secure. 2019 International Conference on Robotics,Electrical and Signal Processing Techniques (ICREST). :502–506.

Cloud Computing is an important term of modern technology. The usefulness of Cloud is increasing day by day and simultaneously more and more security problems are arising as well. Two of the major threats of Cloud are improper authentication and multi-tenancy. According to the specialists both pros and cons belong to multi-tenancy. There are security protocols available but it is difficult to claim these protocols are perfect and ensure complete protection. The purpose of this paper is to propose an integrated model to ensure better Cloud security for Authentication and multi-tenancy. Multi-tenancy means sharing of resources and virtualization among clients. Since multi-tenancy allows multiple users to access same resources simultaneously, there is high probability of accessing confidential data without proper privileges. Our model includes Kerberos authentication protocol to enhance authentication security. During our research on Kerberos we have found some flaws in terms of encryption method which have been mentioned in couple of IEEE conference papers. Pondering about this complication we have elected Elliptic Curve Cryptography. On the other hand, to attenuate arose risks due to multi-tenancy we are proposing a Resource Allocation Manager Unit, a Control Database and Resource Allocation Map. This part of the model will perpetuate resource allocation for the users.