Develop Secure Information Systems Research Articles

An effective method to improve nonlinearity value of substitution boxes based on random selection

In today's digital society, new design alternatives are needed for substitution box structures, which has critical importance in developing secure information systems that are resistant to algebraic and application attacks, as new attacks negatively affect designs based on mathematical transformations. Although random selection-based substitution box structures are a good alternative against algebraic and application attacks, the low value of nonlinearity criterion is an important problem. Solution suggestions using optimization algorithms have been proposed to address this problem. “Information Sciences 523 (2020) 152–166” is the study that reached the highest nonlinearity value based on optimization algorithms to date. However, the high computational costs of optimization algorithms are another challenge that must be overcome. In this study, it has been shown that the nonlinearity values ​​of random (chaotic) selection substitution box structures can be improved as much as mathematically based designs by using a method that is too simple to compare with optimization algorithms. It has been shown that the nonlinearity value can be improved up to 110 for random selection-based substitution box designs. Although this nonlinearity value is the highest achievable value in the literature based on the random selection principle, the fact that it requires only 2×255×255 processes in the worst case has been evaluated as an important success of the proposed method compared to other design approaches. Other advantages of the proposed method are that the improved substitution box structures are resistant to side-channel attacks, simple structure, easy hardware implementation, and successful results in practical applications such as image encryption. It is believed that all these results will be a motivation for new post-processing techniques to be designed in the future for random selection-based substitution box designs.

A Review on Various Methods of Intrusion Detection System

Detection of Intrusion is an essential expertise business segment as well as a dynamic area of study and expansion caused by its requirement. Modern day intrusion detection systems still have these limitations of time sensitivity. The main requirement is to develop a system which is able of handling large volume of network data to detect attacks more accurately and proactively. Research conducted by on the KDDCUP99 dataset resulted in a various set of attributes for each of the four major attack types. Without reducing the number of features, detecting attack patterns within the data is more difficult for rule generation, forecasting, or classification. The goal of this research is to present a new method that Compare results of appropriately categorized and inaccurately categorized as proportions and the features chosen. Data mining is used to clean, classify and examine large amount of network data. Since a large volume of network traffic that requires processing, we use data mining techniques. Different Data Mining techniques such as clustering, classification and association rules are proving to be useful for analyzing network traffic. This paper presents the survey on data mining techniques applied on intrusion detection systems for the effective identification of both known and unknown patterns of attacks, thereby helping the users to develop secure information systems. Keywords: IDS, Data Mining, Machine Learning, Clustering, Classification DOI : 10.7176/CEIS/11-1-02 Publication date: January 31 st 2020

Ensemble Classification for Intrusion Detection

Security of network systems is becoming an important
 issue, as more and sensitive information is being stored and manipulated online. Therefore, it is essential to find an effective way to protect it. Mining approach can play very important role in developing an intrusion detection system. This paper presents various data mining Classification techniques applied on intrusion detection systems for the effective identification of both known and unknown patterns of attacks, to develop secure information systems.

Survey paper on intrusion detection techniques

Network security has been one of the most important problems in Computer Network Management and Intrusion is the most publicized threats to security. In recent years, intrusion detection has emerged as an important field for network security. IDSs obtain better results when each class ofattacks is treated as a separate problem and handled by specialized algorithms. Now in days various model and method are available for intrusion detection. In this paper, we present a study of intrusion detection. Detection method to improve the detection rate & helping the users to develop secure information systems.

Towards maturity of information security maturity criteria: six lessons learned from software maturity criteria

Traditionally, information security management standards listing generic means of protection have received a lot of attention in the field of information security management. In the background a few information security management‐oriented maturity criteria have been laid down. These criteria can be regarded as the latest promising innovations on the information security checklist‐standard family tree. Whereas information security maturity criteria have so far received inadequate attention in information security circles, software maturity endeavours have been the focus of constructive debate in software engineering circles. Aims to analyze what the alternative maturity criteria for developing secure information systems (IS) and software can learn from these debates on software engineering maturity criteria. First, advances a framework synthesized from the information systems (IS) and software engineering literatures, including six lessons that information security maturity criteria can learn from. Second, pores over the existing information security maturity criteria in the light of this framework. Third, presents, on the basis of results of this analysis, implications for practice and research.

Risk Expectation Management for Building Secure Information Systems

AbstractThis paper describes the process of building Information Systems that integrate security mechanisms to protect from unauthorized access and mistreatment Risk expectation management for information systems is associated with security requirements‐policy‐architecture‐risk analysis and synthesis. Cognizance of threat is the most important part of developing secure information systems. The paper organizes the complexity of information security principles into a structured approach intended to minimize the expected security risk. An example is presented in the appendix.