A Prevention and a Traction System for Ransomware Attacks

Over the past three years, especially following WannaCry malware, ransomware has become one of the biggest concerns for private businesses, state, and local government agencies. According to Homeland Security statistics, 1.5 million ransomware attacks have occurred per year since 2016. Cybercriminals often use creative methods to inject their malware into the target machines and use sophisticated cryptographic techniques to hold hostage victims' files and programs unless a certain amount of equivalent Bitcoin is paid. The return to the cybercriminals is so high (estimated \$1 billion in 2019) without any cost because of the advanced anonymity provided by cryptocurrencies, especially Bitcoin \cite{Paquet-Clouston2019}. Given this context, this study first discusses the current state of ransomware, detection, and prevention systems. Second, we propose a global ransomware center to better manage our concerted efforts against cybercriminals. The policy implications of the proposed study are discussed in the conclusion section

Ontological support for the evolution of future services oriented architectures

Services Oriented Architectures (SOA) have emerged as a useful framework for developing interoperable, large-scale systems, typically implemented using the Web Services (WS) standards. However, the maintenance and evolution of SOA systems present many challenges. SmartLife applications are intelligent user-centered systems and a special class of SOA systems that present even greater challenges for a software maintainer. Ontologies and ontological modeling can be used to support the evolution of SOA systems. This paper describes the development of a SOA evolution ontology and its use to develop an ontological model of a SOA system. The ontology is based on a standard SOA ontology. The ontological model can be used to provide semantic and visual support for software maintainers during routine maintenance tasks. We discuss a case study to illustrate this approach, as well as the strengths and limitations

A Survey of Social Network Forensics

Social networks in any form, specifically online social networks (OSNs), are becoming a part of our everyday life in this new millennium especially with the advanced and simple communication technologies through easily accessible devices such as smartphones and tablets. The data generated through the use of these technologies need to be analyzed for forensic purposes when criminal and terrorist activities are involved. In order to deal with the forensic implications of social networks, current research on both digital forensics and social networks need to be incorporated and understood. This will help digital forensics investigators to predict, detect and even prevent any criminal activities in different forms. It will also help researchers to develop new models / techniques in the future. This paper provides literature review of the social network forensics methods, models, and techniques in order to provide an overview to the researchers for their future works as well as the law enforcement investigators for their investigations when crimes are committed in the cyber space. It also provides awareness and defense methods for OSN users in order to protect them against to social attacks

Probabilistic Trans-Algorithmic Search

Online configuration of large-scale systems such as networks requires parameter optimization within a limited amount of time. This time limit is even more pressing when configuration is needed as a recovery response to a failure in the system. To quickly configure such systems in an online manner, we propose a Probabilistic Trans-Algorithmic Search (PTAS) framework which leverages multiple optimization search algorithms in an iterative manner. PTAS applies a search algorithm to determine how to best distribute available experiment budget among multiple optimization search algorithms. It allocates an experiment budget to each available search algorithm and observes its performance on the system-at-hand. PTAS then reallocates the experiment budget for the next round proportional to each algorithm's performance relative to the rest of the algorithms. This "roulette wheel" principle favors the more successful algorithm in the next round. Following each round, the PTAS framework "transfers" the best result(s) among the individual algorithms, making our framework a "trans-algorithmic" one. PTAS thus aims to systematize how to "search for the best search". We show the performance of PTAS on well-known benchmark objective functions including scenarios where the objective function changes in the middle of the optimization process. To illustrate applicability of our framework to automated network management, we apply PTAS on the problem of optimizing link weights of an intra-domain routing protocol on three different topologies obtained from the Rocketfuel dataset. We also apply PTAS on the problem of optimizing aggregate throughput of a wireless ad hoc network by tuning data rates of traffic sources. We compared the experimental results of PTAS against other three well-known search algorithms, i.e., Random Recursive Search, Simulated Annealing, and Genetic Algorithm. We observe that PTAS outperforms other three search algorithms in the majority of experiments. Especially, when the network system at-hand is very dynamic with factors, such as link failures and link recovery, PTAS performs better, and adapts to the new system more quickly due to its hybrid nature

Maintaining SOA systems of the future : how can ontological modeling help?

Many future Services Oriented Architecture (SOA) systems may be pervasive SmartLife applications that provide real-time support for users in everyday tasks and situations. Development of such applications will be challenging, but in this position paper we argue that their ongoing maintenance may be even more so. Ontological modelling of the application may help to ease this burden, but maintainers need to understand a system at many levels, from a broad architectural perspective down to the internals of deployed components. Thus we will need consistent models that span the range of views, from business processes through system architecture to maintainable code. We provide an initial example of such a modelling approach and illustrate its application in a semantic browser to aid in software maintenance tasks