Biblio

SDN represents a significant advance for the telecom world, since the decoupling of the control and data planes offers numerous advantages in terms of management dynamism and programmability, mainly due to its software-based centralized control. Unfortunately, these features can be exploited by malicious entities, who take advantage of the centralized control to extend the scope and consequences of their attacks. When this happens, both the legal and network technical fields are concerned with gathering information that will lead them to the root cause of the problem. Although forensics and incident response processes share their interest in the event information, both operate in isolation due to the conceptual and pragmatic challenges of integrating them into SDN environments, which impacts on the resources and time required for information analysis. Given these limitations, the current work focuses on proposing a framework for SDNs that combines the above approaches to optimize the resources to deliver evidence, incorporate incident response activation mechanisms, and generate assumptions about the possible origin of the security problem.

In order to analyze the trustworthiness of complex software systems, we propose a model of evidence-based software trustworthiness called trustworthiness derivation tree (TDT). The basic idea of constructing a TDT is to refine main properties into key ingredients and continue the refinement until basic facts such as evidences are reached. The skeleton of a TDT can be specified by a set of rules, which is convenient for automated reasoning in Prolog. We develop a visualization tool that can construct the skeleton of a TDT by taking the rules as input, and allow a user to edit the TDT in a graphical user interface. In a software development life cycle, TDTs can serve as a communication means for different stakeholders to agree on the properties about a system in the requirement analysis phase, and they can be used for deductive reasoning so as to verify whether the system achieves trustworthiness in the product validation phase. We have piloted the approach of using TDTs in more than a dozen real scenarios of software development. Indeed, using TDTs helped us to discover and then resolve some subtle problems.

With the widespread adoption of Internet of Things (IoT) applications around the world, security related problems become a challenge since the number of cybercrimes that must be identified and investigated increased dramatically. The volume of data generated and handled is immense due to the increased number of IoT applications around the world. As a result, when a cybercrime happens, the volume of digital data needs to be dealt with is massive. Consequently, more effort and time are needed to handle the security issues. As a result, in digital forensics, the analysis phase is an important and challenging phase. This paper proposes a generic proactive model for the cybercrime analysis process in the Internet of Things. The model is focused on the classification of evidences in advance based on its significance and relation to past crimes, as well as the severity of the evidence in terms of the probability occurrence of a cybercrime. This model is supposed to save time and effort during the automated forensic investigation process.

Software is playing a pivotal role in most enterprises, whether they realize it or not, and with the proliferation of Industrial Internet of Things (IoT) and other CyberPhysical systems across our society and critical infrastructure and our collective love affair with automation, optimization, and ``smart'' devices, the role of these types of systems is only going to increase. This talk addresses the myriad of issues that underlie unsafe, insecure, and unreliable software and provides the insights of the Industrial Internet Consortium and other government and industry efforts on how to conquer them and pave the way to a marketplace of trustworthy software-enabled connected things. As the experience of several sectors has shown, the dependence on connected software needs to be met with a strong understanding of the risks to the overall trustworthiness of our software-based capabilities that we, our enterprises, and our world utilize. In many of these new connected systems issues of safety, reliability, and resilience rival or dominate concerns for security and privacy, the long-time focus of many in the IT world. Without a scalable and efficient method for managing these risks so our enterprises can continue to benefit from these advancements that powers our military, commercial industries, cities, and homes to new levels of efficiency, versatility, and cost effectiveness we face the potential for harm, death, and destructiveness. In such a marketplace, creating, exchanging, and integrating components that are trustworthy as well as entering into value-chain relationships with trustworthy partners and service suppliers will be common if we can provide a method for explicitly defining what is meant by the word trustworthy. The approach being pursued by these groups for applying Software Assurance to these systems and their Supply Chains by leveraging Structured Assurance Cases (the focus of this paper), Software Bill of Materials, and secure development practices applied to the evolving Agile and DevSecOps methodologies, is to explicitly identify the detailed requirements ``about what we need to know about something for it to be worthy of our trust'' and to do that in a way that we can convey that basis of trust to others that: can scale; is consistent within different workflows; is flexible to differing sets of hazards and environments; and is applicable to all sectors, domains, and industries.

Cloud computing is cutting-edge platform in this information age, where organizations are shifting their business due to its elasticity, ubiquity, cost-effectiveness. Unfortunately the cyber criminals has used these characteristics for the criminal activities and victimizing multiple users at the same time, by their single exploitation which was impossible in before. Cloud forensics is a special branch of digital forensics, which aims to find the evidences of the exploitation in order to present these evidences in the court of law and bring the culprit to accountability. Collection of evidences in the cloud is not as simple as the traditional digital forensics because of its complex distributed architecture which is scattered globally. In this paper, various issues and challenges in the field of cloud forensics research and their proposed solutions have been critically reviewed, summarized and presented.

Power systems domain has generally been very conservative in terms of conducting digital forensic investigations, especially so since the advent of smart grids. This lack of research due to a multitude of challenges has resulted in absence of knowledge base and resources to facilitate such an investigation. Digitalization in the form of smart grids is upon us but in case of cyber-attacks, attribution to such attacks is challenging and difficult if not impossible. In this research, we have identified digital forensic artifacts resulting from a cyber-attack on Wide Area Monitoring, Protection and Control (WAMPAC) systems, which will help an investigator attribute an attack using the identified evidences. The research also shows the usage of sandboxing for digital forensics along with hardware-in-the-loop (HIL) setup. This is first of its kind effort to identify and acquire all the digital forensic evidences for WAMPAC systems which will ultimately help in building a body of knowledge and taxonomy for power system forensics.

Cyber crime investigation is the integration of two technologies named theoretical methodology and second practical tools. First is the theoretical digital forensic methodology that encompasses the steps to investigate the cyber crime. And second technology is the practically development of the digital forensic tool which sequentially and systematically analyze digital devices to extract the evidence to prove the crime. This paper explores the development of digital forensic framework, combine the advantages of past twenty five forensic models and generate a algorithm to create a new digital forensic model. The proposed model provides the following advantages, a standardized method for investigation, the theory of model can be directly convert into tool, a history lookup facility, cost and time minimization, applicable to any type of digital crime investigation.