Biblio

Security-critical systems demand multiple well-balanced mechanisms to detect ill-intentioned actions and protect valuable assets from damage while keeping costs in acceptable levels. The use of deception to enhance security has been studied for more than two decades. However, deception is still included in the software development process in an ad-hoc fashion, typically realized as single tools or entire solutions repackaged as honeypot machines. We propose a multi-paradigm modeling approach to specify deception tactics during the software development process so that conflicts and risks can be found in the initial phases of the development, reducing costs of ill-planned decisions. We describe a metamodel containing deception concepts that integrates other models, such as a goal-oriented model, feature model, and behavioral UML models to specify static and dynamic aspects of a deception operation. The outcome of this process is a set of deception tactics that is realized by a set of deception components integrated with the system components. The feasibility of this multi-paradigm approach is shown by designing deception defense strategies for a students’ presence control system for the Faculty of Science and Technology of Universidade NOVA de Lisboa.

The key factors for deploying successful services is centered on the service design practices adopted by an enterprise. The design level information should be validated and measures are required to quantify the structural attributes. The metrics at this stage will support an early discovery of design flaws and help designers to predict the capabilities of service oriented architecture (SOA) adoption. In this work, we take a deeper look at how we can forecast the key SOA capabilities infrastructure efficiency and service reuse from the service designs modeled by SOA modeling language. The proposed approach defines metrics based on the structural and domain level similarity of service operations. The proposed metrics are analytically validated with respect to software engineering metrics properties. Moreover, a tool has been developed to automate the proposed approach and the results indicate that the metrics predict the SOA capabilities at the service design stage. This work can be further extended to predict the business based capabilities of SOA adoption such as flexibility and agility.

First standardized by the IETF in the 1990's, SSL/TLS is the most widely-used encryption protocol on the Internet. This makes it imperative to study its usage across different platforms and applications to ensure proper usage and robustness against attacks and vulnerabilities. While previous efforts have focused on the usage of TLS in the desktop ecosystem, there have been no studies of TLS usage by mobile apps at scale. In our study, we use anonymized data collected by the Lumen mobile measurement app to analyze TLS usage by Android apps in the wild. We analyze and fingerprint handshake messages to characterize the TLS APIs and libraries that apps use, and evaluate their weaknesses. We find that 84% of apps use the default TLS libraries provided by the operating system, and the remaining apps use other TLS libraries for various reasons such as using TLS extensions and features that are not supported by the Android TLS libraries, some of which are also not standardized by the IETF. Our analysis reveals the strengths and weaknesses of each approach, demonstrating that the path to improving TLS security in the mobile platform is not straightforward. Based on work published at: Abbas Razaghpanah, Arian Akhavan Niaki, Narseo Vallina-Rodriguez, Srikanth Sundaresan, Johanna Amann, and Phillipa Gill. 2017. Studying TLS Usage in Android Apps. In Proceedings of CoNEXT '17. ACM, New York, NY, USA, 13 pages. https://doi.org/10.1145/3143361.3143400

In the digital age, drug makers have never been more exposed to cyber threats, from a wide range of actors pursuing very different motivations. These threats can have unpredictable consequences for the reliability and integrity of the pharmaceutical supply chain. Cyber threats do not have to target drug makers directly; a recent wargame by the Atlantic Council highlighted how malware affecting one entity can degrade equipment and systems functions using the same software. The NotPetya ransomware campaign in mid-2017 was not specifically interested in affecting the pharmaceutical industry, but nevertheless disrupted Merck’s HPV vaccine production line. Merck lost 310 million dollars in revenue subsequent quarter, as a result of lost productivity and a halt in production for almost a week.

Capturing the patterns in adversarial movement can provide valuable information regarding how the adversaries progress through cyberattacks. This information can be further employed for making comparisons and interpretations of decision making of the adversaries. In this study, we propose a framework based on concepts of social networks to characterize and compare the patterns, variations and shifts in the movements made by an adversarial team during a real-time cybersecurity exercise. We also explore the possibility of movement association with the skill sets using topological sort networks. This research provides preliminary insight on adversarial movement complexity and linearity and decision-making as cyberattacks unfold.

We propose a novel cross-stack sensor framework for realizing lightweight, context-aware, high-interaction network and endpoint deceptions for attacker disinformation, misdirection, monitoring, and analysis. In contrast to perimeter-based honeypots, the proposed method arms production workloads with deceptive attack-response capabilities via injection of booby-traps at the network, endpoint, operating system, and application layers. This provides defenders with new, potent tools for more effectively harvesting rich cyber-threat data from the myriad of attacks launched by adversaries whose identities and methodologies can be better discerned through direct engagement rather than purely passive observations of probe attempts. Our research provides new tactical deception capabilities for cyber operations, including new visibility into both enterprise and national interest networks, while equipping applications and endpoints with attack awareness and active mitigation capabilities.

The Internet of Things (IoT) is a vast collection of interconnected sensors, devices, and services that share data and information over the Internet with the objective of leveraging multiple information sources to optimize related systems. The technologies associated with the IoT have significantly improved the quality of many existing applications by reducing costs, improving functionality, increasing access to resources, and enhancing automation. The adoption of IoT by industries has led to the next industrial revolution: Industry 4.0. The rise of the Industrial IoT (IIoT) promises to enhance factory management, process optimization, worker safety, and more. However, the rollout of the IIoT is not without significant issues, and many of these act as major barriers that prevent fully achieving the vision of Industry 4.0. One major area of concern is the security and privacy of the massive datasets that are captured and stored, which may leak information about intellectual property, trade secrets, and other competitive knowledge. As a way forward toward solving security and privacy concerns, we aim in this paper to identify common input-output (I/O) design patterns that exist in applications of the IIoT. These design patterns enable constructing an abstract model representation of data flow semantics used by such applications, and therefore better understand how to secure the information related to IIoT operations. In this paper, we describe communication protocols and identify common I/O design patterns for IIoT applications with an emphasis on data flow in edge devices, which, in the industrial control system (ICS) setting, are most often involved in process control or monitoring.

The growing use of ICT in complex and critical infrastructures in the energy- and maritime domain leads to the development of system-of-system engineering efforts especially for system architectures. Such efforts need to integrate a standardized elicitation and harmonization of requirements between different interoperability perspectives and with domain-specific aspects. According to this, the paper adapts the existing architecture management approaches SGAM and MAF for a methodology to structure the identification and harmonization of requirements considering domain specific characteristics and interoperability.

Airports are at the forefront of technological innovation, mainly due to the fact that the number of air travel passengers is exponentially increasing every year. As a result, airports enhance infrastructure's intelligence and evolve as smart facilities to support growth, by offering a pleasurable travel experience, which plays a vital role in increasing revenue of aviation sector. New challenges are coming up, which aviation has to deal and adapt, such as the integration of Industrial IoT in airport facilities and the increased use of Bring Your Own Device from travelers and employees. Cybersecurity is becoming a key enabler for safety, which is paramount in the aviation context. Smart airports strive to provide optimal services in a reliable and sustainable manner, by working around the domains of growth, efficiency, safety andsecurity. This paper researches the implementation rate of cybersecurity measures and best practices to improve airports cyber resilience. With the aim to enhance operational practices anddevelop robust cybersecurity governance in smart airports, we analyze security gaps in different areas including technical, organizational practices and policies.

Cloud computing is an emerging technology that provides services to its users via Internet. It also allows sharing of resources there by reducing cost, money and space. With the popularity of cloud and its advantages, the trend of information industry shifting towards cloud services is increasing tremendously. Different cloud service providers are there on internet to provide services to the users. These services provided have certain parameters to provide better usage. It is difficult for the users to select a cloud service that is best suited to their requirements. Our proposed approach is based on data mining classification technique with fuzzy logic. Proposed algorithm uses cloud service design factors (security, agility and assurance etc.) and international standards to suggest the cloud service. The main objective of this research is to enable the end cloud users to choose best service as per their requirements and meeting international standards. We test our system with major cloud provider Google, Microsoft and Amazon.

In this paper we examine the use of covert channels based on CPU load in order to achieve persistent user identification through browser sessions. In particular, we demonstrate that an HTML5 video, a GIF image, or CSS animations on a webpage can be used to force the CPU to produce a sequence of distinct load levels, even without JavaScript or any client-side code. These load levels can be then captured either by another browsing session, running on the same or a different browser in parallel to the browsing session we want to identify, or by a malicious app installed on the device. To get a good estimation of the CPU load caused by the target session, the receiver can observe system statistics about CPU activity (app), or constantly measure time it takes to execute a known code segment (app and browser). Furthermore, for mobile devices we propose a sensor-based approach to estimate the CPU load, based on exploiting disturbances of the magnetometer sensor data caused by the high CPU activity. Captured loads can be decoded and translated into an identifying bit string, which is transmitted back to the attacker. Due to the way loads are produced, these methods are applicable even in highly restrictive browsers, such as the Tor Browser, and run unnoticeably to the end user. Therefore, unlike existing ways of web tracking, our methods circumvent most of the existing countermeasures, as they store the identifying information outside the browsing session being targeted. Finally, we also thoroughly evaluate and assess each presented method of generating and receiving the signal, and provide an overview of potential countermeasures.

In the computer based solutions of the problems in today's world; if the problem has a high complexity value, different requirements can be addressed such as necessity of simultaneous operation of many computers, the long processing times for the operation of algorithms, and computers with hardware features that can provide high performance. For this reason, it is inevitable to use a computer based on quantum physics in the near future in order to make today's cryptosystems unsafe, search the servers and other information storage centers on internet very quickly, solve optimization problems in the NP-hard category with a very wide solution space and analyze information on large-scale data processing and to process high-resolution image for artificial intelligence applications. In this study, an examination of quantum approaches and quantum computers, which will be widely used in the near future, was carried out and the areas in which such innovation can be used was evaluated. Malicious or non-malicious use of quantum computers with this capacity, the advantages and disadvantages of the high performance which it provides were examined under the head of security, the effect of this recent technology on the existing security systems was investigated.

Nowadays, most of the world's population has become much dependent on computers for banking, healthcare, shopping, and telecommunication. Security has now become a basic norm for computers and its resources since it has become inherently insecure. Security issues like Denial of Service attacks, TCP SYN Flooding attacks, Packet Dropping attacks and Distributed Denial of Service attacks are some of the methods by which unauthorized users make the resource unavailable to authorized users. There are several security mechanisms like Intrusion Detection System, Anomaly detection and Trust model by which we can be able to identify and counter the abuse of computer resources by unauthorized users. This paper presents a survey of several security mechanisms which have been implemented using Fuzzy logic. Fuzzy logic is one of the rapidly developing technologies, which is used in a sophisticated control system. Fuzzy logic deals with the degree of truth rather than the Boolean logic, which carries the values of either true or false. So instead of providing only two values, we will be able to define intermediate values.

In this study, we have used the Image Similarity technique to detect the unknown or new type of malware using CNN ap- proach. CNN was investigated and tested with three types of datasets i.e. one from Vision Research Lab, which contains 9458 gray-scale images that have been extracted from the same number of malware samples that come from 25 differ- ent malware families, and second was benign dataset which contained 3000 different kinds of benign software. Benign dataset and dataset vision research lab were initially exe- cutable files which were converted in to binary code and then converted in to image files. We obtained a testing ac- curacy of 98% on Vision Research dataset.

This work explores attack and attacker profiles using a VoIP-based Honeypot. We implemented a low interaction honeypot environment to identify the behaviors of the attackers and the services most frequently used. We watched honeypot for 180 days and collected 242.812 events related to FTP, SIP, MSSQL, MySQL, SSH, SMB protocols. The results provide an in-depth analysis about both attacks and attackers profile, their tactics and purposes. It also allows understanding user interaction with a vulnerable honeypot environment.

As 5G transitions from an industrial vision to a tangible, next-generation mobile technology, security remains key business driver. Heterogeneous environment, new networking paradigms and novel use cases makes 5G vulnerable to new security threats. This in turn necessitates a flexible and dependable security mechanism. End-to-End (E2E) data protection provides better security, avoids repeated security operations like encryption/decryption and provides differentiated security based on the services. E2E security deals with authentication, integrity, key management and confidentiality. The attack surface of a 5G system is larger as 5G aims for a heterogeneous networked society. Hence attack resistance needs to be a design consideration when defining new 5G protocols. This framework has been designed for accessing the manifold applications with high security and trust by offering E2E security for various services. The proposed framework is evaluated based on computation complexity, communication complexity, attack resistance rate and security defensive rate. The protocol is also evaluated for correctness, and resistance against passive, active and dictionary attacks using random oracle model and Automated Validation of Internet Security Protocols and Applications (AVISPA) tool.

With the pervasiveness of the Internet of Things (IoT) and the rapid progress of wireless communications, Wireless Body Area Networks (WBANs) have attracted significant interest from the research community in recent years. As a promising networking paradigm, it is adopted to improve the healthcare services and create a highly reliable ubiquitous healthcare system. However, the flourish of WBANs still faces many challenges related to security and privacy preserving. In such pervasive environment where the context conditions dynamically and frequently change, context-aware solutions are needed to satisfy the users' changing needs. Therefore, it is essential to design an adaptive access control scheme that can simultaneously authorize and authenticate users while considering the dynamic context changes. In this paper, we propose a context-aware access control and anonymous authentication approach based on a secure and efficient Hybrid Certificateless Signcryption (H-CLSC) scheme. The proposed scheme combines the merits of Ciphertext-Policy Attribute-Based Signcryption (CP-ABSC) and Identity-Based Broadcast Signcryption (IBBSC) in order to satisfy the security requirements and provide an adaptive contextual privacy. From a security perspective, it achieves confidentiality, integrity, anonymity, context-aware privacy, public verifiability, and ciphertext authenticity. Moreover, the key escrow and public key certificate problems are solved through this mechanism. Performance analysis demonstrates the efficiency and the effectiveness of the proposed scheme compared to benchmark schemes in terms of functional security, storage, communication and computational cost.

The concept of cyber-physical production systems is highly discussed amongst researchers and industry experts, however, the implementation options for these systems rely mainly on obsolete technologies. Despite the fact that the blockchain is most often associated with cryptocurrency, it is fundamentally wrong to deny the universality of this technology and the prospects for its application in other industries. For example, in the insurance sector or in a number of identity verification services. This article discusses the deployment of the CPPS backbone network based on the Ethereum private blockchain system. The structure of the network is described as well as its interaction with the help of smart contracts, based on the consumption of cryptocurrency for various operations.

This paper explores low cost technical solutions that can help organizations prevent, detect, and respond to insider incidents. Features and functionality associated with insider risk mitigation are presented. A taxonomy for high-level categories of insider threat tools is presented. A discussion of the relationship between the types of tools points out the nuances of insider threat control deployment, and considerations for selecting, implementing, and operating insider threat tools are provided.

In rural/remote areas, resource constrained smart micro-grid (RCSMG) architectures can offer a cost-effective power management and supply alternative to national power grid connections. RCSMG architectures handle communications over distributed lossy networks to minimize operation costs. However, the unreliable nature of lossy networks makes privacy an important consideration. Existing anonymisation works on data perturbation work mainly by distortion with additive noise. Apply these solutions to RCSMGs is problematic, because deliberate noise additions must be distinguishable both from system and adversarial generated noise. In this paper, we present a brief survey of privacy risks in RCSMGs centered on inference, and propose a method of mitigating these risks. The lesson here is that while RCSMGs give users more control over power management and distribution, good anonymisation is essential to protecting personal information on RCSMGs.

The interconnection of networks between several techno-socio-economic sectors such as energy, transport, and communication, questions the manageability and resilience of the digital society. System interdependencies alter the fundamental dynamics that govern isolated systems, which can unexpectedly trigger catastrophic instabilities such as cascading failures. This paper envisions a general-purpose, yet simple prototyping of self-management software systems that can turn system interdependencies from a cause of instability to an opportunity for higher resilience. Such prototyping proves to be challenging given the highly interdisciplinary scope of interdependent networks. Different system dynamics and organizational constraints such as the distributed nature of interdependent networks or the autonomy and authority of system operators over their controlled infrastructure perplex the design for a general prototyping approach, which earlier work has not yet addressed. This paper contributes such a modular design solution implemented as an open source software extension of SFINA, the Simulation Framework for Intelligent Network Adaptations. The applicability of the software artifact is demonstrated with the introduction of a novel self-healing mechanism for interdependent power networks, which optimizes power flow exchanges between a damaged and a healer network to mitigate power cascading failures. Results show a significant decrease in the damage spread by self-healing synergies, while the degree of interconnectivity between the power networks indicates a tradeoff between links survivability and load served. The contributions of this paper aspire to bring closer several research communities working on modeling and simulation of different domains with an economic and societal impact on the resilience of real-world interdependent networks.

The Java platform and its third-party libraries provide useful features to facilitate secure coding. However, misusing them can cost developers time and effort, as well as introduce security vulnerabilities in software. We conducted an empirical study on StackOverflow posts, aiming to understand developers' concerns on Java secure coding, their programming obstacles, and insecure coding practices. We observed a wide adoption of the authentication and authorization features provided by Spring Security - a third-party framework designed to secure enterprise applications. We found that programming challenges are usually related to APIs or libraries, including the complicated cross-language data handling of cryptography APIs, and the complex Java-based or XML-based approaches to configure Spring Security. In addition, we reported multiple security vulnerabilities in the suggested code of accepted answers on the StackOverflow forum. The vulnerabilities included disabling the default protection against Cross-Site Request Forgery (CSRF) attacks, breaking SSL/TLS security through bypassing certificate validation, and using insecure cryptographic hash functions. Our findings reveal the insufficiency of secure coding assistance and documentation, as well as the huge gap between security theory and coding practices.

This paper proposes an architecture of Secure Shell (SSH) honeypot using port knocking and Intrusion Detection System (IDS) to learn the information about attacks on SSH service and determine proper security mechanisms to deal with the attacks. Rapid development of information technology is directly proportional to the number of attacks, destruction, and data theft of a system. SSH service has become one of the popular targets from the whole vulnerabilities which is existed. Attacks on SSH service have various characteristics. Therefore, it is required to learn these characteristics by typically utilizing honeypots so that proper mechanisms can be applied in the real servers. Various attempts to learn the attacks and mitigate them have been proposed, however, attacks on SSH service are kept occurring. This research proposes a different and effective strategy to deal with the SSH service attack. This is done by combining port knocking and IDS to make the server keeps the service on a closed port and open it under user demand by sending predefined port sequence as an authentication process to control the access to the server. In doing so, it is evident that port knocking is effective in protecting SSH service. The number of login attempts obtained by using our proposed method is zero.