From Security Protocols to Systems Security

2005 ◽  
pp. 323-323
Author(s):  
Brian Monahan
Keyword(s):  
Security Protocols ◽  
Systems Security

Towards a Standard for a Reliable Execution Environment for Security Protocols

2016 ◽  
Vol 2 (1) ◽  
pp. 78
Author(s):  
Mahalingam Ramkumar
Keyword(s):  
Information Systems ◽  
Full Advantage ◽  
Real World ◽  
Security Protocols ◽  
Low Complexity ◽  
High Integrity ◽  
Execution Environment ◽  
World Information ◽  
Digital Assets ◽  
Attack Models

Approaches for securing digital assets of information systems can be classified as active approaches based on attack models, and passive approaches based on system-models. Passive approaches are inherently superior to active ones. However, taking full advantage of passive approaches calls for a rigorous standard for a low-complexity-high-integrity execution environment for security protocols. We sketch broad outlines of mirror network (MN) modules, as a candidate for such a standard. Their utility in assuring real-world information systems is illustrated with examples.

The effectiveness of web advertising, its legal regulation and the problem of information systems security

2020 ◽  
Vol 4 (3(12)) ◽  
pp. 1-15
Author(s):  
Samira Ilgarovna Proshkina ◽  
Keyword(s):  
Information Systems ◽  
Computational Models ◽  
Evolutionary Dynamics ◽  
Legal Regulation ◽  
Information Systems Security ◽  
Systematic Analysis ◽  
Web Advertising ◽  
Systems Security ◽  
Business Structures ◽  
Display Location

The work is devoted to an urgent problem — the study of the evolutionary dynamics of web advertising, its assessment and effectiveness, as well as the problem of legal support and security of information systems. The goal is a systematic analysis of web advertising in an unsafe information field, its relevance and criteria for assessing marketing efforts, minimizing risks, maximizing additional profits and image. Research hypothesis — the effectiveness of web advertising is determined by the form of advertising, place of display, location of the block, model of calculation of the advertising campaign. An approach based on the establishment of preferences, partnership between the state and business structures is emphasized. It takes into account the COVID-19 pandemic, a slowdown in the pace and features of the evolution of business companies in self-isolation. The subtasks of influence on the advertising efficiency of the site’s features and web advertising are highlighted. A comprehensive analysis of information and logical security and computational models of web advertising companies was also carried out.

scholarly journals A Survey on Ethereum Systems Security

2020 ◽  
Vol 53 (3) ◽  
pp. 1-43 ◽  
Author(s):  
Huashan Chen ◽  
Marcus Pendleton ◽  
Laurent Njilla ◽  
Shouhuai Xu
Keyword(s):  
Systems Security

Evaluation of Algorithms and Security Protocols to Mitigate the Risks in Commercial Transactions carried out by Public Companies

2020 ◽  
Author(s):  
Segundo Moises Toapanta Toapanta ◽  
Luis Enrique Mafla Gallegos ◽  
Alex Enrique Aranda Alvarado ◽  
Maximo Prado Solis
Keyword(s):  
Security Protocols ◽  
Public Companies

ExypnoSteganos - A smarter approach to steganography

2021 ◽  
pp. 1-12
Author(s):  
Gaurav Sarraf ◽  
Anirudh Ramesh Srivatsa ◽  
MS Swetha
Keyword(s):  
Neural Network ◽  
Deep Learning ◽  
Data Compression ◽  
Building Block ◽  
Communication Techniques ◽  
Systems Security ◽  
Learning Technique ◽  
Critical Problems ◽  
Sporadic Cases ◽  
Compressed Data

With the ever-rising threat to security, multiple industries are always in search of safer communication techniques both in rest and transit. Multiple security institutions agree that any systems security can be modeled around three major concepts: Confidentiality, Availability, and Integrity. We try to reduce the holes in these concepts by developing a Deep Learning based Steganography technique. In our study, we have seen, data compression has to be at the heart of any sound steganography system. In this paper, we have shown that it is possible to compress and encode data efficiently to solve critical problems of steganography. The deep learning technique, which comprises an auto-encoder with Convolutional Neural Network as its building block, not only compresses the secret file but also learns how to hide the compressed data in the cover file efficiently. The proposed techniques can encode secret files of the same size as of cover, or in some sporadic cases, even larger files can be encoded. We have also shown that the same model architecture can theoretically be applied to any file type. Finally, we show that our proposed technique surreptitiously evades all popular steganalysis techniques.

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