Security issues, threats, and attacks in relation with the IoT have been identified as promising and challenging area of research. Eventually, the need for a forensics methodology for investigating IoT -related crime is therefore essential. However, the IoT poses many challenges for forensics investigators. These include the wide range and variety of information, the unclear lines of differentiation between networks, for example private networks increasingly fading into public networks. Further, integration of a large number of objects in IoT forensic interest, along with the relevance of identified and collected devices makes forensic of IoT devices more complicated. The scope of this paper is to present a framework for IoT forensic. We aimed at the study and development of the link to support digital investigations of IoT devices and tackle emerging challenges in digital forensics. We emphasize on various steps for digital forensic with respect to IoT devices.
Fuzzy logic has wide adoption in every field of study due to its immense advantages and techniques. In cloud computing, there are many challenges that can be resolved with the help of fuzzy logic. The core objective of this paper is to analyze the application of fuzzy logic in most demanding research areas of cloud computing. We also analyzed the fuzzy methods that were used in the solving of problems relates to cloud computing. A systematic literature review was conducted to enlist the all the challenging areas of research relates to cloud computing, categorized the most critical and challenging areas of cloud research, studied existing problem-solving techniques of each challenging cloud area, and finally studied the application of fuzzy logic in each aforementioned areas to redress different problems. The authors concluded that fuzzy logic can be used in every area of research including cloud computing to solve the problems and optimized the performance, as well as fuzzy logic techniques, were opted by many cloud computing researchers to conduct their study to optimize the performance of the system.
Cybersecurity of industrial control system is a very complex and challenging research topic, due to the integration of these systems in national critical infrastructures. The control systems are now interconnected in industrial networks and frequently to the Internet. In this context they are becoming targets of various cyber attacks conducted by malicious people such as hackers, script kiddies, industrial spies and even foreign armies and intelligence agencies. In this paper the authors propose a way to model the most frequent attacker profiles and to estimate the success rate of an attack conducted in given conditions. The authors use a fuzzy approach for generating attacker profiles based on attacker attributes such as knowledge, technical resources and motivation. The attack success rate is obtained by using another fuzzy inference system that analyzes the attacker profile and system intrinsic characteristics.
Today, Android accounts for more than 80% of the global market share. Such a high rate makes Android applications an important topic that raises serious questions about its security, privacy, misbehavior and correctness. Application code analysis is obviously the most appropriate and natural means to address these issues. However, no analysis could be led with confidence in the absence of a solid formal foundation. In this paper, we propose a full-fledged formal approach to build the operational semantics of a given Android application by reverse-engineering its assembler-type code, called Smali. We call the new formal language Smali . Its semantics consist of two parts. The first one models a single-threaded program, in which a set of main instructions is presented. The second one presents the semantics of a multi-threaded program which is an important feature in Android that has been glossed over in the-state-of-the-art works. All multi-threading essentials such as scheduling, threads communication and synchronization are considered in these semantics. The resulting semantics, forming Smali , are intended to provide a formal basis for developing security enforcement, analysis and misbehaving detection techniques for Android applications.