Screening the covert key using honey encryption to rule out the brute force attack of AES-a survey

2016 ◽  
Vol 9 (18) ◽  
pp. 6379-6385
Author(s):  
P Dharshini ◽  
J Arokia Renjith ◽  
P Mohan Kumar
Keyword(s):  
Brute Force ◽  
Brute Force Attack ◽  
Rule Out

Modelling and visualising SSH brute force attack behaviours through a hybrid learning framework

2021 ◽  
Vol 16 (1/2) ◽  
pp. 170
Author(s):  
A. Nur Zincir Heywood ◽  
Xiao Luo ◽  
Chengchao Yao
Keyword(s):  
Hybrid Learning ◽  
Brute Force ◽  
Learning Framework ◽  
Brute Force Attack

scholarly journals A New Symmetric Key Cryptographic Algorithm using Paley Graphs and ASCII Values

2021 ◽  
Vol 297 ◽  
pp. 01046
Author(s):  
Zhour Oumazouz ◽  
Driss Karim
Keyword(s):  
Brute Force ◽  
Strong Regularity ◽  
Quadratic Residues ◽  
Cryptographic Algorithm ◽  
Paley Graph ◽  
Encryption And Decryption ◽  
Symmetric Key ◽  
Brute Force Attack ◽  
The Moment ◽  
Paley Graphs

The main objective of the study conducted in this article is to introduce a new algorithm of encryption and decryption of a sensitive message after transforming it into a binary message. Our proposed encryption algorithm is based on the study of a particular graph constructed algebraically from the quadratic residues. We have exploited the Paley graph to introduce an abstract way of encryption of such message bit according to the other message bits by the intermidiate study of the neighborhood of a graph vertex. The strong regularity of the Paley graphs and the unknown behavior of the quadratic residues will play a very important role in the cryptanalysis part which allows to say that the brute force attack remains for the moment the only way to obtain the set of possible messages.

Toward Responsible AI: An Overview of Federated Learning for User-centered Privacy-preserving Computing

2021 ◽  
Vol 11 (3-4) ◽  
pp. 1-22
Author(s):  
Qiang Yang
Keyword(s):  
Private Information ◽  
High Performance ◽  
Privacy Preserving ◽  
Security And Privacy ◽  
Brute Force ◽  
New Paradigm ◽  
User Privacy ◽  
Data Governance ◽  
Incentive Mechanisms ◽  
Rule Out

With the rapid advances of Artificial Intelligence (AI) technologies and applications, an increasing concern is on the development and application of responsible AI technologies. Building AI technologies or machine-learning models often requires massive amounts of data, which may include sensitive, user private information to be collected from different sites or countries. Privacy, security, and data governance constraints rule out a brute force process in the acquisition and integration of these data. It is thus a serious challenge to protect user privacy while achieving high-performance models. This article reviews recent progress of federated learning in addressing this challenge in the context of privacy-preserving computing. Federated learning allows global AI models to be trained and used among multiple decentralized data sources with high security and privacy guarantees, as well as sound incentive mechanisms. This article presents the background, motivations, definitions, architectures, and applications of federated learning as a new paradigm for building privacy-preserving, responsible AI ecosystems.

Modelling and visualising SSH brute force attack behaviours through a hybrid learning framework

2021 ◽  
Vol 16 (1/2) ◽  
pp. 170
Author(s):  
Xiao Luo ◽  
Chengchao Yao ◽  
A. Nur Zincir Heywood
Keyword(s):  
Hybrid Learning ◽  
Brute Force ◽  
Learning Framework ◽  
Brute Force Attack

scholarly journals Investigating Brute Force Attack Patterns in IoT Network

2019 ◽  
Vol 2019 ◽  
pp. 1-13 ◽  
Author(s):  
Deris Stiawan ◽  
Mohd. Yazid Idris ◽  
Reza Firsandaya Malik ◽  
Siti Nurmaini ◽  
Nizar Alsharif ◽  
...  
Keyword(s):  
Brute Force ◽  
File Transfer ◽  
Iot Security ◽  
Insider Attack ◽  
Attack Pattern ◽  
Internal Network ◽  
Attack Patterns ◽  
Iot Devices ◽  
Set Up ◽  
Brute Force Attack

Internet of Things (IoT) devices may transfer data to the gateway/application server through File Transfer Protocol (FTP) transaction. Unfortunately, in terms of security, the FTP server at a gateway or data sink very often is improperly set up. At the same time, password matching/theft holding is among the popular attacks as the intruders attack the IoT network. Thus, this paper attempts to provide an insight of this type of attack with the main aim of coming up with attack patterns that may help the IoT system administrator to analyze any similar attacks. This paper investigates brute force attack (BFA) on the FTP server of the IoT network by using a time-sensitive statistical relationship approach and visualizing the attack patterns that identify its configurations. The investigation focuses on attacks launched from the internal network, due to the assumption that the IoT network has already installed a firewall. An insider/internal attack launched from an internal network endangers more the entire IoT security system. The experiments use the IoT network testbed that mimic the internal attack scenario with three major goals: (i) to provide a topological description on how an insider attack occurs; (ii) to achieve attack pattern extraction from raw sniffed data; and (iii) to establish attack pattern identification as a parameter to visualize real-time attacks. Experimental results validate the investigation.

scholarly journals Double image multi-encryption algorithm based on fractional chaotic time series

2015 ◽  
Vol 13 (1) ◽  
Author(s):  
Zhenghong Guo ◽  
Jie Yang ◽  
Yang Zhao
Keyword(s):  
Time Series ◽  
Chaotic Time Series ◽  
Encryption Algorithm ◽  
Brute Force ◽  
Double Image ◽  
Key Space ◽  
Plain Image ◽  
Image Pixels ◽  
Brute Force Attack ◽  
The Relationship

AbstractIn this paper, we introduce a new image encryption scheme based on fractional chaotic time series, in which shuffling the positions blocks of plain-image and changing the grey values of image pixels are combined to confuse the relationship between the plain-image and the cipher-image. Also, the experimental results demonstrate that the key space is large enough to resist the brute-force attack and the distribution of grey values of the encrypted image has a random-like behavior.

Image Encryption Algorithm Based on Chaos and S-Boxes Scrambling

2010 ◽  
Vol 171-172 ◽  
pp. 299-304 ◽  
Author(s):  
Zhuo Hui Xian ◽  
Shi Liang Sun
Keyword(s):  
Image Encryption ◽  
Chaotic Maps ◽  
Encryption Algorithm ◽  
Brute Force ◽  
Simulation Experiments ◽  
Encryption Algorithms ◽  
Brute Force Attack ◽  
Image Encryption Algorithm

Due to some features of images, traditional encryption algorithms are not suitable for practical image encryption. Considering this problem, a novel feistel network image encryption algorithm is proposed in this paper. Taking advantage of the desirable properties of mixing and sensitivity to initial parameters of chaotic maps, a sub key generator with couple chaotic maps is presented in this scheme. Meanwhile, the encryption algorithm includes a new mixing algorithm which is designed with thirty s-boxes of AES. To enhance the security of the new scheme, the encryption processes were combined in feistel network. The results of analysis and simulation experiments indicate that the scheme is secure and performed well in preventing attacks, such as brute force attack, entropy attack and statistics attack.

An analysis of Markov password against Brute force attack for effective web applications

2014 ◽  
Vol 8 ◽  
pp. 5823-5830 ◽  
Author(s):  
S. Vaithyasubramanian ◽  
A. Christy ◽  
D. Saravanan
Keyword(s):  
Web Applications ◽  
Brute Force ◽  
Brute Force Attack
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