Mobile Application Security Platforms Survey

Nowadays Smartphone and other mobile devices have become incredibly important in every aspect of our life. Because they have practically offered same capabilities as desktop workstations as well as come to be powerful in terms of CPU (Central processing Unit), Storage and installing numerous applications. Therefore, Security is considered as an important factor in wireless communication technologies, particularly in a wireless ad-hoc network and mobile operating systems. Moreover, based on increasing the range of mobile application within variety of platforms, security is regarded as on the most valuable and considerable debate in terms of issues, trustees, reliabilities and accuracy. This paper aims to introduce a consolidated report of thriving security on mobile application platforms and providing knowledge of vital threats to the users and enterprises. Furthermore, in this paper, various techniques as well as methods for security measurements, analysis and prioritization within the peak of mobile platforms will be presented. Additionally, increases understanding and awareness of security on mobile application platforms to avoid detection, forensics and countermeasures used by the operating systems. Finally, this study also discusses security extensions for popular mobile platforms and analysis for a survey within a recent research in the area of mobile platform security

Security and Privacy Issues of Big Data

This chapter revises the most important aspects in how computing infrastructures should be configured and intelligently managed to fulfill the most notably security aspects required by Big Data applications. One of them is privacy. It is a pertinent aspect to be addressed because users share more and more personal data and content through their devices and computers to social networks and public clouds. So, a secure framework to social networks is a very hot topic research. This last topic is addressed in one of the two sections of the current chapter with case studies. In addition, the traditional mechanisms to support security such as firewalls and demilitarized zones are not suitable to be applied in computing systems to support Big Data. SDN is an emergent management solution that could become a convenient mechanism to implement security in Big Data systems, as we show through a second case study at the end of the chapter. This also discusses current relevant work and identifies open issues.Comment: In book Handbook of Research on Trends and Future Directions in Big Data and Web Intelligence, IGI Global, 201

Security Issues in Distributed Database Management Systems: Challenges and Opportunities

Database management systems (DBMS) are essential systems of software technologies for multi-level and multi-angled operations with the utmost security. Currently, its form of distributed database, i.e. DDB, is very popular in communication networks. The current write-up is aimed at investigating important security aspects and issues, exploring some major challenges pertinent to the security of DDB, finding solutions to the same, and eventually talking about some future opportunities through promoting research towards curbing these security-related points. To accomplish these tasks, the author has reviewed some of the latest and most pertinent research articles of the last ten years. It comprises the application of DDBMS, major pertinent issues within its range of investigation, and a conclusion

Enhancing User Authentication with Facial Recognition and Feature-Based Credentials

This research proposes a novel and trustworthy user authentication method that creates individualized and trusted credentials based on distinctive facial traits using facial recognition technology. The ability to easily validate user identification across various login methods is provided by this feature. The fundamental elements of this system are face recognition, feature extraction, and the hashing of characteristics to produce usernames and passwords. This method makes use of the OpenCV library, which is free software for computer vision. Additionally, it employs Hashlib for secure hashing and Image-based Deep Learning for Identification (IDLI) technology to extract facial tags. For increased security and dependability, the system mandates a maximum of ten characters for users and passwords. By imposing this restriction, the system increases its resilience by reducing any possible weaknesses in its defense. The policy also generates certificates that are neatly arranged in an Excel file for easy access and management. To improve user data and provide reliable biometric authentication, this study intends to create and implement a recognition system that incorporates cutting-edge approaches such as face feature extraction, feature hashing, and password creation. Additionally, the system has robust security features using face recognition

A Systematic Review on Image Data Protection Methods

Securing data is the main goal of any data security system (DSS). Valuable data must be protected all the time and stored in a very highly secure data storage device. This need has become more critical due to the continuous growth of data size.  Furthermore, non-text data in the form of images, audio, and videos can now be transferred and processed easily and thus become part of sensitive data that needs to be protected. Since there is a need to secure and protect data in any form in order to keep them private and valid, it is expected that there would be many attempts already that have been proposed in the literature for this purpose. This paper reviews a group of these proposed strategies and methods that have been applied to different kinds of DSSs. Challenges and future trends of DSSs are also discussed. A number of main findings are grouped and organized as follows: (1) there are many different kinds of security techniques, each of which offers varying degrees of performance in terms of the amount of data and information that can be managed securely, (2) depending on the architecture of the proposed method, the tactics or strategies of the security system, the kinds of DSSs, as well as a few other factors, some methods are more appropriate for the storage of certain categories of data than others

Survey and Systematization of Secure Device Pairing

Secure Device Pairing (SDP) schemes have been developed to facilitate secure communications among smart devices, both personal mobile devices and Internet of Things (IoT) devices. Comparison and assessment of SDP schemes is troublesome, because each scheme makes different assumptions about out-of-band channels and adversary models, and are driven by their particular use-cases. A conceptual model that facilitates meaningful comparison among SDP schemes is missing. We provide such a model. In this article, we survey and analyze a wide range of SDP schemes that are described in the literature, including a number that have been adopted as standards. A system model and consistent terminology for SDP schemes are built on the foundation of this survey, which are then used to classify existing SDP schemes into a taxonomy that, for the first time, enables their meaningful comparison and analysis.The existing SDP schemes are analyzed using this model, revealing common systemic security weaknesses among the surveyed SDP schemes that should become priority areas for future SDP research, such as improving the integration of privacy requirements into the design of SDP schemes. Our results allow SDP scheme designers to create schemes that are more easily comparable with one another, and to assist the prevention of persisting the weaknesses common to the current generation of SDP schemes.Comment: 34 pages, 5 figures, 3 tables, accepted at IEEE Communications Surveys & Tutorials 2017 (Volume: PP, Issue: 99