Biblio

Protecting sensitive information from illegal access and misuse is crucial to all organizations. An inappropriate Information Security (IS) policy and procedures are not only a suitable environment for an outsider attack but also a good chance for the insiders' misuse. In this paper, we will discuss the roles of an organization in information security and how human behavior affects the Information Security System (ISS). How an organization can create and instill an effective information security culture in an organization to improve their information safeguards. The findings in this review can be used to further researches and will be useful for organizations to improve their information security structure (ISC).

In the era of Industry 4.0 (IR 4.0), information leakage has become a critical issue for information security. The basic approach to addressing information leakage threats is to implement an information security policy (ISP) that defines the standards, boundaries, and responsibilities of users of information and technology of an organization. ISPs are one of the most commonly used methods for controlling internal user security behaviours, which include, but not limited to, computer usage ethics; organizational system usage policies; Internet and email usage policies; and the use of social media. Human error is the main security threat to information security, resulting from negligence, ignorance, and failure to adhere to organizational information security policies. Information security incidents are a problem related to human behaviour because technology is designed and operated by humans, presenting the opportunities and spaces for human error. In addition to the factor of human error as the main source of information leakage, this study aims to systematically analyse the fundamental issues of information security policy compliance. An analysis of these papers identifies and categories critical factor that effect an employee's attitude toward compliance with ISP. The human, process, technology element and information governance should be thought as a significant scope for more efficiency of information security policy compliance and in any further extensive studies to improve on information security policy compliance. Therefore, to ensure these are properly understood, further study is needed to identity the information governance that needs to be included in organizations and current best practices for developing an information security policy compliance within organizations.

With the development of cloud computing technology, developed countries including the U.S. are performing the efficiency of national defense and public sector, national innovation, and construction of the infrastructure for cloud computing environment through the policies that apply cloud computing. Korea Military is also considering that apply the cloud computing technology into its national defense command control system. However, only existing security requirements for national defense information system cannot solve the problem related security vulnerabilities of cloud computing. In order to solve this problem, it is necessary to design the secure security architecture of national defense command control system considering security requirements related to cloud computing. This study analyze the security requirements needed when the U.S. military apply the cloud computing system. It also analyze existing security requirements for Korea national defense information system and security requirements for cloud computing system and draw the security requirements needed to Korea national defense information system based on cloud computing.

We present research on the security of the most popular websites, ranked according to Alexa's top one million list, based on an HTTP response headers analysis. For each of the domains included in the list, we made four different requests: an HTTP/1.1 request to the domain itself and to its "www" subdomain and two more equivalent HTTPS requests. Redirections were always followed. A detailed discussion of the request process and main outcomes is presented, including X.509 certificate issues and comparison of results with equivalent HTTP/2 requests. The body of the responses was discarded, and the HTTP response header fields were stored in a database. We analysed the prevalence of the most important response headers related to web security aspects. In particular, we took into account Strict- Transport-Security, Content-Security-Policy, X-XSS-Protection, X-Frame-Options, Set-Cookie (for session cookies) and X-Content-Type. We also reviewed the contents of response HTTP headers that potentially could reveal unwanted information, like Server (and related headers), Date and Referrer-Policy. This research offers an up-to-date survey of current prevalence of web security policies implemented through HTTP response headers and concludes that most popular sites tend to implement it noticeably more often than less popular ones. Equally, HTTPS sites seem to be far more eager to implement those policies than HTTP only websites. A comparison with previous works show that web security policies based on HTTP response headers are continuously growing, but still far from satisfactory widespread adoption.

Recent behavioral research in information security has focused on increasing employees' motivation to enhance the security performance in an organization. This empirical study investigated employees' information security policy (ISP) compliance intentions using self-determination theory (SDT). Relevant hypotheses were developed to test the proposed research model. Data obtained via a survey (N=3D407) from a Fortune 600 organization in Saudi Arabia provides empirical support for the model. The results confirmed that autonomy, competence and the concept of relatedness all positively affect employees' intentions to comply. The variable 'perceived value congruence' had a negative effect on ISP compliance intentions, and the perceived legitimacy construct did not affect employees' intentions. In general, the findings of this study suggest that SDT has value in research into employees' ISP compliance intentions.

Security and Privacy challenges are the most obstacles for the advancement of cloud computing and the erosion of trust boundaries already happening in organizations is amplified and accelerated by this emerging technology. Policy Management Frameworks are the most proper solutions to create dedicated security levels based on the sensitivity of resources and according to the mapping process between requirements cloud customers and capabilities of service providers. The most concerning issue in these frameworks is the rate of perfect matches between capabilities and requirements. In this paper, a reliable ring analysis engine has been introduced to efficiently map the security requirements of cloud customers to the capabilities of service provider and to enhance the rate of perfect matches between them for establishment of different security levels in clouds. In the suggested model a structural index has been introduced to receive the requirement and efficiently map them to the most proper security mechanism of the service provider. Our results show that this index-based engine enhances the rate of perfect matches considerably and decreases the detected conflicts in syntactic and semantic analysis.

Large enterprises and organizations from both private and public sectors typically outsource a platform solution, as part of the Managed Security Services (MSSs), from 3rd party providers (MSSPs) to monitor and analyze their data containing cyber security information. Sharing such data among these large entities is believed to improve their effectiveness and efficiency at tackling cybercrimes, via improved analytics and insights. However, MSS platform customers currently are not able or not willing to share data among themselves because of multiple reasons, including privacy and confidentiality concerns, even when they are using the same MSS platform. Therefore any proposed mechanism or technique to address such a challenge need to ensure that sharing is achieved in a secure and controlled way. In this paper, we propose a new architecture and use case driven designs to enable confidential, flexible and collaborative data sharing among such organizations using the same MSS platform. MSS platform is a complex environment where different stakeholders, including authorized MSSP personnel and customers' own users, have access to the same platform but with different types of rights and tasks. Hence we make every effort to improve the usability of the platform supporting sharing while keeping the existing rights and tasks intact. As an innovative and pioneering attempt to address the challenge of data sharing in the MSS platform, we hope to encourage further work to follow so that confidential and collaborative sharing eventually happens among MSS platform customers.

With the rapid progression of Information and Communication Technology (ICT) and especially of Internet of Things (IoT), the conventional electrical grid is transformed into a new intelligent paradigm, known as Smart Grid (SG). SG provides significant benefits both for utility companies and energy consumers such as the two-way communication (both electricity and information), distributed generation, remote monitoring, self-healing and pervasive control. However, at the same time, this dependence introduces new security challenges, since SG inherits the vulnerabilities of multiple heterogeneous, co-existing legacy and smart technologies, such as IoT and Industrial Control Systems (ICS). An effective countermeasure against the various cyberthreats in SG is the Intrusion Detection System (IDS), informing the operator timely about the possible cyberattacks and anomalies. In this paper, we provide an anomaly-based IDS especially designed for SG utilising operational data from a real power plant. In particular, many machine learning and deep learning models were deployed, introducing novel parameters and feature representations in a comparative study. The evaluation analysis demonstrated the efficacy of the proposed IDS and the improvement due to the suggested complex data representation.

Security and privacy of smart grid communication data is crucial given the nature of the continuous bidirectional information exchange between the consumer and the utilities. Data security has conventionally been ensured using cryptographic techniques implemented at the upper layers of the network stack. However, it has been shown that security can be further enhanced using physical layer (PHY) methods. To aid and/or complement such PHY and upper layer techniques, in this paper, we propose a PHY design that can detect and locate not only an active intruder but also a passive eavesdropper in the network. Our method can either be used as a stand-alone solution or together with existing techniques to achieve improved smart grid data security. Our machine learning based solution intelligently and automatically detects and locates a possible intruder in the network by reusing power line transmission modems installed in the grid for communication purposes. Simulation results show that our cost-efficient design provides near ideal intruder detection rates and also estimates its location with a high degree of accuracy.

Smart grid has evolved as the next generation power grid paradigm which enables the transfer of real time information between the utility company and the consumer via smart meter and advanced metering infrastructure (AMI). These information facilitate many services for both, such as automatic meter reading, demand side management, and time-of-use (TOU) pricing. However, there have been growing security and privacy concerns over smart grid systems, which are built with both smart and legacy information and operational technologies. Intrusion detection is a critical security service for smart grid systems, alerting the system operator for the presence of ongoing attacks. Hence, there has been lots of research conducted on intrusion detection in the past, especially anomaly-based intrusion detection. Problems emerge when common approaches of pattern recognition are used for imbalanced data which represent much more data instances belonging to normal behaviors than to attack ones, and these approaches cause low detection rates for minority classes. In this paper, we study various machine learning models to overcome this drawback by using CIC-IDS2018 dataset [1].

Security refers to precautions designed to shield the availability and integrity of information exchanged among the digital global community. Information safety measure typically protects the virtual facts from unauthorized sources to get a right of entry to, disclosure, manipulation, alteration or destruction on both hardware and software technologies. According to an evaluation through experts operating in the place of information safety, some of the new cyber-attacks are keep on emerging in all the business processes. As a stop result of the analyses done, it's been determined that although the level of risk is not excessive in maximum of the attacks, it's far a severe risk for important data and the severity of those attacks is prolonged. Prior safety structures has been established to monitor various cyber-threats, predominantly using a gadget processed data or alerts for showing each deterministic and stochastic styles. The principal finding for deterministic patterns in cyber- attacks is that they're neither unbiased nor random over the years. Consequently, the quantity of assaults in the past helps to monitor the range of destiny attacks. The deterministic styles can often be leveraged to generate moderately correct monitoring.

The security of Cyber-physical systems has been a hot topic in recent years. There are two main focuses in this area: Firstly, what kind of attacks can avoid detection, i.e., the stealthiness of attacks. Secondly, what kind of systems can stay stable under stealthy attacks, i.e., the invulnerability of systems. In this paper, we will give a detailed characterization for stealthy attacks and detection criterion for such attacks. We will also study conditions for the vulnerability of a stochastic linear system under stealthy attacks.

Previous research on internal threats was mostly focused on modeling threat behaviors. These studies have paid little attention to risk measurement. This paper analyzed the internal threat scenarios, introduced the operation related protection model into the firewall-password model, constructed a series of sub models. By analyzing the illegal data out process, the analysis model of target network can be rapidly generated based on four protection sub-models. Then the risk value of an assessment point can be computed dynamically according to the Petri net computing characteristics and the effectiveness of overall network protection can be measured. This method improves the granularity of the model and simplifies the complexity of modeling complex networks and can realize dynamic and real-time risk measurement.

Internet of Battlefield Things (IoBT) devices such as actuators, sensors, wearable devises, robots, drones, and autonomous vehicles, facilitate the Intelligence, Surveillance and Reconnaissance (ISR) to Command and Control and battlefield services. IoBT devices have the ability to collect operational field data, to compute on the data, and to upload its information to the network. Securing the IoBT presents additional challenges compared with traditional information technology (IT) systems. First, IoBT devices are mass produced rapidly to be low-cost commodity items without security protection in their original design. Second, IoBT devices are highly dynamic, mobile, and heterogeneous without common standards. Third, it is imperative to understand the natural world, the physical process(es) under IoBT control, and how these real-world processes can be compromised before recommending any relevant security counter measure. Moreover, unprotected IoBT devices can be used as “stepping stones” by attackers to launch more sophisticated attacks such as advanced persistent threats (APTs). As a result of these challenges, IoBT systems are the frequent targets of sophisticated cyber attack that aim to disrupt mission effectiveness.

Continued advances in IoT technology have prompted new investigation into its usage for military operations, both to augment and complement existing military sensing assets and support next-generation artificial intelligence and machine learning systems. Under the emerging Internet of Battlefield Things (IoBT) paradigm, current operational conditions necessitate the development of novel security techniques, centered on establishment of trust for individual assets and supporting resilience of broader systems. To advance current IoBT efforts, a collection of prior-developed cybersecurity techniques is reviewed for applicability to conditions presented by IoBT operational environments (e.g., diverse asset ownership, degraded networking infrastructure, adversary activities) through use of supporting case study examples. The research techniques covered focus on two themes: (1) Supporting trust assessment for known/unknown IoT assets; (2) ensuring continued trust of known IoT assets and IoBT systems.

The security threats to mobile applications are growing explosively. Mobile apps flaws and security defects open doors for hackers to break in and access sensitive information. Defensive requirements analysis should be an integral part of secure mobile SDLC. Developers need to consider the information confidentiality and data integrity, to verify the security early in the development lifecycle rather than fixing the security holes after attacking and data leaks take place. Early eliminating known security vulnerabilities will help developers increase the security of apps and reduce the likelihood of exploitation. However, many software developers lack the necessary security knowledge and skills at the development stage, and that's why Secure Mobile Software Development education is very necessary for mobile software engineers. In this paper, we propose a guided security requirement analysis based on OWASP Mobile Top ten security risk recommendations for Android mobile software development and its traceability of the developmental controls in SDLC. Building secure apps immune to the OWASP Mobile Top ten risks would be an effective approach to provide very useful mobile security guidelines.

The paper provides an analysis of the performance of an administrative component that helps the hypervisor to manage the resources of guest operating systems under fluctuation workload. The additional administrative component provides an extra layer of security to the guest operating systems and system as a whole. In this study, an administrative component was implemented by using Xen-hypervisor based para-virtualization technique and assigned some additional roles and responsibilities that reduce hypervisor workload. The study measured the resource utilizations of an administrative component when excessive input/output load passes passing through the system. Performance was measured in terms of bandwidth and CPU utilisation Based on the analysis of administrative component performance recommendations have been provided with the goal to improve system availability. Recommendations included detection of the performance saturation point that indicates the necessity to start load balancing procedures for the administrative component in the virtualized environment.

Modern mobile operating systems store a lot of excessive information that can be used against its owner or organization, like a call history or various system logs. This article describes a universal way of preventing any mobile operating system or application from saving its data in device's internal storage without reducing their functionality. The goal of this work is creation of a software that solves the described problem and works on the bootloading stage. A general algorithm of the designed software, along with its main solutions and requirements, is presented in this paper. Hardware requirement, software testing results and general applications of this software are also listed in this paper.

The following topics are dealt with: Internet of Things; invasive software; security of data; program testing; reverse engineering; product codes; binary codes; decoding; maximum likelihood decoding; field programmable gate arrays.

The lack of strong cyber-physical modeling capabilities presents many challenges across the design, development, verification, and maintenance phases of a system [7]. Novel techniques for modeling the cyber-grid components, along with analysis and verification techniques, are imperative to the deployment of a resilient and robust power grid. Several works address False Data Injection (FDI) attacks to the power grid. However, most of them suffer from the lack of a model to investigate the effects of attacks. This paper proposed a cyber-physical model using Architecture Analysis & Design Language (AADL) [15] and power system information models to address different attacks in power systems.

Today's highly interconnected and technology reliant environment places great emphasis on the need for secure cyber-physical systems. This work addresses this need by detailing a top down systems security requirements analysis approach for understanding and eliciting security requirements for a notional space system. More specifically, the System-Theoretic Process Analysis approach for Security (STPA-Sec) is used to understand and elicit systems security requirements during the conceptual stage of development. This work employs STPA-Sec in a notional space system to detail the development of functional-level security requirements, design-level engineering considerations, and architectural-level security specifications early in the system life cycle when the solution trade-space is largest rather than merely examining components and adding protections during system operation, maintenance, or sustainment. Lastly, this approach employs a holistic viewpoint which aligns with the systems and software engineering processes as detailed in ISO/IEC/IEEE 152SS and NIST SP SOO-160 Volume 1. This work seeks to advance the science of systems security by providing insight into a viable systems security requirements analysis approach which results in traceable security, safety, and resiliency requirements that can be designed-for, built-to, and verified with confidence.

Communications play a fundamental role in the economic and social well-being of the citizens and on operations of most of the critical infrastructures (CIs). Extreme weather events, natural disasters and criminal attacks represent a challenge due to their increase in frequency and intensity requiring smarter resilience of the Communication CIs, which are extremely vulnerable due to the ever-increasing complexity of the architecture also in light of the evolution towards 5G, the extensive use of programmable platforms and exponential growth of connected devices. In this paper, we present the aim of RESISTO H2020 EU-funded project, which constitutes an innovative solution for Communication CIs holistic situation awareness and enhanced resilience.

Cyber resiliency of Energy Delivery Systems (EDS) is critical for secure and resilient cyber infrastructure. Defense-in-depth architecture forces attackers to conduct lateral propagation until the target is compromised. Researchers developed techniques based on graph spectral matrices to model lateral propagation. However, these techniques ignore host criticality which is critical in EDS. In this paper, we model attacker's opportunity by developing three criticality metrics for each host along the path to the target. The first metric refers the opportunity of attackers before they penetrate the infrastructure. The second metric measure the opportunity a host provides by allowing attackers to propagate through the network. Along with vulnerability we also take into account the attributes of hosts and links within each path. Then, we derive third criticality metric to reflect the information flow dependency from each host to target. Finally, we provide system design for instantiating the proposed metrics for real network scenarios in EDS. We present simulation results which illustrates the effectiveness of the metrics for efficient defense deployment in EDS cyber infrastructure.

Cyber-Physical-Systems are subject to cyber-attacks due to existing vulnerabilities in the various components constituting them. System Resiliency is concerned with the extent the system is able to bounce back to a normal state under attacks. In this paper, two communication Networks are analyzed, formally described, and modeled using Architecture Analysis & Design Language (AADL), identifying their architecture, connections, vulnerabilities, resources, possible attack instances as well as their pre-and post-conditions. The generated network models are then verified against a security property using JKind model checker integrated tool. The union of the generated attack sequences/scenarios resulting in overall network compromise (given by its loss of stability) is the Attack graph. The generated Attack graph is visualized graphically using Unity software, and then used to assess the worst Level of Resilience for both networks.

Model Based Systems Engineering (MBSE) adds efficiency during all phases of the design lifecycle. MBSE tools enforce design policies and rules to capture the design elements, inter-element relationships, and their attributes in a consistent manner. The system elements, and attributes are captured and stored in a centralized MBSE database for future retrieval. Systems that depend on computer networks can be designed using MBSE to meet cybersecurity and resilience requirements. At each step of a structured systems engineering methodology, decisions need to be made regarding the selection of architecture and designs that mitigate cyber risk and enhance cyber resilience. Detailed risk and decision analysis methods involve complex models and computations which are often characterized as a Big Data analytic problem. In this paper, we argue in favor of using graph analytic methods with model based systems engineering to support risk and decision analyses when engineering cyber resilient systems.