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One of the challenges of digital forensics is the high volume of investigative cases. To address this problem, researchers have proposed various triage methods. Detecting the applications that have run on the compromised system under inspection can be an excellent triage method that gives the investigator an overview of the system. In this paper, we construct the signature of software usage on a system using file path artifacts. We propose a software signature detection engine (SSDE) to identify the usage of the software on the system under investigation. The SSDE consists of two subsystems: the signature construction subsystem, which builds the software signature using the TF-IDF weighting scheme, and the signature detection subsystem, which identifies the executed set of software on the target system. We consider several parameters with different values in the design of SSDEs, leading to more than 500 SSDE models. We test the SSDE models against 14 pseudo-real systems from the M57 Patents scenario and evaluate their performance. The experimental results show that about 38% of SSDE models achieve near-perfect Precision, and about 18% of them achieve near-perfect Recall. We introduce the top models and determine which parameter values lead to the superior models. Besides, we compare the SSDE models with some doc2vec-based models. The results show that SSDE models have higher average Precision, slightly lower average Recall, and much less computational time.

With the advent of fog computing, its use to provide real-time services at the network's edge has increased. However, running computationally-demanding applications in smart vehicles is constrained by the limited storage and computation capacity and energy consumption of the vehicles. A suitable solution is to offload the applications demanding massive processing to a conventional centralized cloud which wastes huge bandwidth and increases the delay. The number of smart vehicles is expected to increase in the future; there is a need for new technology such as fog computing (FC) to meet unique requirements such as QoS, resource management, and heterogeneity in vehicular ad-hoc networks (VANET). FC brings computation and storage resources to the edge of vehicles enabling them to run the highly-demanding applications in the smart vehicles while meeting strict delay requirements. This survey focuses on different applications, architectures, technical issues, and significant performance metrics using FC in vehicular network. Finally, open issues and future directions are discussed.

The development of smart cities through digital communications has improved citizens' quality of life and well-being. In these cities, IoT technology generates vast amounts of data at any given time, which is analyzed to provide services to citizens. In the proper implementation of these cities, a critical challenge is the violation of citizens' privacy and security, which leads to a lack of trust and pessimism toward the services of the smart city. To ensure citizens' participation, smart city developers should adequately protect their security and privacy from gaining their trust. If citizens don't want to participate, the main benefits of a smart city will be lost. This article presents a comprehensive review of smart city security issues and privacy. It provides a basis for categorizing current and future developments in this area and developing a thematic classification to highlight the requirements and security strategies for designing a smart and safe city. The paper identifies current security and privacy solutions and describes open research challenges and issues. An output of this study is a systematic map of literature on the subject that identifies critical concepts, evidence, challenges, solutions, and gaps. It summarizes the findings into a body of evidence that has previously been heterogeneous and complex.

Software‐defined networks are a modern architecture in computer networks where traffic transfer is separated from network control. In software‐defined networks, all decisions are made in the controller, and the necessary commands are injected into the network equipment. With the advent of software‐defined networks and the introduction of a new concept called controller in these types of networks, it becomes important to find an appropriate location for the controller and its number in the network. This problem aims to find the location and the optimal number of controllers needed in the network, and how to assign switches to the controllers declined certain constraints. In this article, a method to determine the appropriate location for controllers is proposed, so that the cost of network implementation would be reduced and thus its survivability is improved. Finally, we analyzed the proposed method in terms of evaluation criteria. With the advent of software‐defined networks and the introduction of a new concept called controller in these types of networks, it becomes important to find an appropriate location for the controller and its number in the network. This problem aims to find the location and the optimal number of controllers. In this paper, a method to determine the appropriate location for controllers is proposed, so that the cost of network implementation would be reduced and thus its survivability is improved.