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Pham, Cuong, Tang, Dat, Chinen, Ken-ichi, Beuran, Razvan.  2016.  CyRIS: A Cyber Range Instantiation System for Facilitating Security Training. Proceedings of the Seventh Symposium on Information and Communication Technology. :251–258.

Cyber ranges are well-defined controlled virtual environments used in cybersecurity training as an efficient way for trainees to gain practical knowledge through hands-on activities. However, creating an environment that contains all the necessary features and settings, such as virtual machines, network topology and security-related content, is not an easy task, especially for a large number of participants. Therefore, we propose CyRIS (Cyber Range Instantiation System) as a solution towards this problem. CyRIS provides a mechanism to automatically prepare and manage cyber ranges for cybersecurity education and training based on specifications defined by the instructors. In this paper, we first describe the design and implementation of CyRIS, as well as its utilization. We then present an evaluation of CyRIS in terms of feature coverage compared to the Technical Guide to Information Security Testing and Assessment of the U.S National Institute of Standards and Technology, and in terms of functionality compared to other similar tools. We also discuss the execution performance of CyRIS for several representative scenarios.

Karbab, ElMouatez Billah, Debbabi, Mourad, Derhab, Abdelouahid, Mouheb, Djedjiga.  2016.  Cypider: Building Community-based Cyber-defense Infrastructure for Android Malware Detection. Proceedings of the 32Nd Annual Conference on Computer Security Applications. :348–362.

The popularity of Android OS has dramatically increased malware apps targeting this mobile OS. The daily amount of malware has overwhelmed the detection process. This fact has motivated the need for developing malware detection and family attribution solutions with the least manual intervention. In response, we propose Cypider framework, a set of techniques and tools aiming to perform a systematic detection of mobile malware by building an efficient and scalable similarity network infrastructure of malicious apps. Our detection method is based on a novel concept, namely malicious community, in which we consider, for a given family, the instances that share common features. Under this concept, we assume that multiple similar Android apps with different authors are most likely to be malicious. Cypider leverages this assumption for the detection of variants of known malware families and zero-day malware. It is important to mention that Cypider does not rely on signature-based or learning-based patterns. Alternatively, it applies community detection algorithms on the similarity network, which extracts sub-graphs considered as suspicious and most likely malicious communities. Furthermore, we propose a novel fingerprinting technique, namely community fingerprint, based on a learning model for each malicious community. Cypider shows excellent results by detecting about 50% of the malware dataset in one detection iteration. Besides, the preliminary results of the community fingerprint are promising as we achieved 87% of the detection.

Matthews, I., Mace, J., Soudjani, S., Moorsel, A. van.  2020.  Cyclic Bayesian Attack Graphs: A Systematic Computational Approach. 2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom). :129–136.
Attack graphs are commonly used to analyse the security of medium-sized to large networks. Based on a scan of the network and likelihood information of vulnerabilities, attack graphs can be transformed into Bayesian Attack Graphs (BAGs). These BAGs are used to evaluate how security controls affect a network and how changes in topology affect security. A challenge with these automatically generated BAGs is that cycles arise naturally, which make it impossible to use Bayesian network theory to calculate state probabilities. In this paper we provide a systematic approach to analyse and perform computations over cyclic Bayesian attack graphs. We present an interpretation of Bayesian attack graphs based on combinational logic circuits, which facilitates an intuitively attractive systematic treatment of cycles. We prove properties of the associated logic circuit and present an algorithm that computes state probabilities without altering the attack graphs (e.g., remove an arc to remove a cycle). Moreover, our algorithm deals seamlessly with any cycle without the need to identify their type. A set of experiments demonstrates the scalability of the algorithm on computer networks with hundreds of machines, each with multiple vulnerabilities.
Naik, Nitin, Jenkins, Paul, Savage, Nick, Yang, Longzhi.  2019.  Cyberthreat Hunting - Part 2: Tracking Ransomware Threat Actors Using Fuzzy Hashing and Fuzzy C-Means Clustering. 2019 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). :1–6.

Threat actors are constantly seeking new attack surfaces, with ransomeware being one the most successful attack vectors that have been used for financial gain. This has been achieved through the dispersion of unlimited polymorphic samples of ransomware whilst those responsible evade detection and hide their identity. Nonetheless, every ransomware threat actor adopts some similar style or uses some common patterns in their malicious code writing, which can be significant evidence contributing to their identification. he first step in attempting to identify the source of the attack is to cluster a large number of ransomware samples based on very little or no information about the samples, accordingly, their traits and signatures can be analysed and identified. T herefore, this paper proposes an efficient fuzzy analysis approach to cluster ransomware samples based on the combination of two fuzzy techniques fuzzy hashing and fuzzy c-means (FCM) clustering. Unlike other clustering techniques, FCM can directly utilise similarity scores generated by a fuzzy hashing method and cluster them into similar groups without requiring additional transformational steps to obtain distance among objects for clustering. Thus, it reduces the computational overheads by utilising fuzzy similarity scores obtained at the time of initial triaging of whether the sample is known or unknown ransomware. The performance of the proposed fuzzy method is compared against k-means clustering and the two fuzzy hashing methods SSDEEP and SDHASH which are evaluated based on their FCM clustering results to understand how the similarity score affects the clustering results.

Naik, Nitin, Jenkins, Paul, Savage, Nick, Yang, Longzhi.  2019.  Cyberthreat Hunting - Part 1: Triaging Ransomware using Fuzzy Hashing, Import Hashing and YARA Rules. 2019 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). :1–6.

Ransomware is currently one of the most significant cyberthreats to both national infrastructure and the individual, often requiring severe treatment as an antidote. Triaging ran-somware based on its similarity with well-known ransomware samples is an imperative preliminary step in preventing a ransomware pandemic. Selecting the most appropriate triaging method can improve the precision of further static and dynamic analysis in addition to saving significant t ime a nd e ffort. Currently, the most popular and proven triaging methods are fuzzy hashing, import hashing and YARA rules, which can ascertain whether, or to what degree, two ransomware samples are similar to each other. However, the mechanisms of these three methods are quite different and their comparative assessment is difficult. Therefore, this paper presents an evaluation of these three methods for triaging the four most pertinent ransomware categories WannaCry, Locky, Cerber and CryptoWall. It evaluates their triaging performance and run-time system performance, highlighting the limitations of each method.

Dionísio, Nuno, Alves, Fernando, Ferreira, Pedro M., Bessani, Alysson.  2019.  Cyberthreat Detection from Twitter using Deep Neural Networks. 2019 International Joint Conference on Neural Networks (IJCNN). :1—8.

To be prepared against cyberattacks, most organizations resort to security information and event management systems to monitor their infrastructures. These systems depend on the timeliness and relevance of the latest updates, patches and threats provided by cyberthreat intelligence feeds. Open source intelligence platforms, namely social media networks such as Twitter, are capable of aggregating a vast amount of cybersecurity-related sources. To process such information streams, we require scalable and efficient tools capable of identifying and summarizing relevant information for specified assets. This paper presents the processing pipeline of a novel tool that uses deep neural networks to process cybersecurity information received from Twitter. A convolutional neural network identifies tweets containing security-related information relevant to assets in an IT infrastructure. Then, a bidirectional long short-term memory network extracts named entities from these tweets to form a security alert or to fill an indicator of compromise. The proposed pipeline achieves an average 94% true positive rate and 91% true negative rate for the classification task and an average F1-score of 92% for the named entity recognition task, across three case study infrastructures.

Kim, Jaewon, Ko, Woo-Hyun, Kumar, P. R..  2021.  Cyber-Security through Dynamic Watermarking for 2-rotor Aerial Vehicle Flight Control Systems. 2021 International Conference on Unmanned Aircraft Systems (ICUAS). :1277–1283.
We consider the problem of security for unmanned aerial vehicle flight control systems. To provide a concrete setting, we consider the security problem in the context of a helicopter which is compromised by a malicious agent that distorts elevation measurements to the control loop. This is a particular example of the problem of the security of stochastic control systems under erroneous observation measurements caused by malicious sensors within the system. In order to secure the control system, we consider dynamic watermarking, where a private random excitation signal is superimposed onto the control input of the flight control system. An attack detector at the actuator can then check if the reported sensor measurements are appropriately correlated with the private random excitation signal. This is done via two specific statistical tests whose violation signifies an attack. We apply dynamic watermarking technique to a 2-rotor-based 3-DOF helicopter control system test-bed. We demonstrate through both simulation and experimental results the performance of the attack detector on two attack models: a stealth attack, and a random bias injection attack.
Winnefeld Jr., James A.(Sandy), Christopher Kirchhoff, David M. Upton.  2015.  Cybersecurity’s Human Factor: Lessons from the Pentagon. Harvard Business Review.

The vast majority of companies are more exposed to cyberattacks than they have to be. To close the gaps in their security, CEOs can take a cue from the U.S. military. Once a vulnerable IT colossus, it is becoming an adroit operator of well-defended networks. Today the military can detect and remedy intrusions within hours, if not minutes. From September 2014 to June 2015 alone, it repelled more than 30 million known malicious attacks at the boundaries of its networks. Of the small number that did get through, fewer than 0.1% compromised systems in any way. Given the sophistication of the military’s cyberadversaries, that record is a significant feat.

Fejrskov, M., Pedersen, J. M., Vasilomanolakis, E..  2020.  Cyber-security research by ISPs: A NetFlow and DNS Anonymization Policy. :1—8.

Internet Service Providers (ISPs) have an economic and operational interest in detecting malicious network activity relating to their subscribers. However, it is unclear what kind of traffic data an ISP has available for cyber-security research, and under which legal conditions it can be used. This paper gives an overview of the challenges posed by legislation and of the data sources available to a European ISP. DNS and NetFlow logs are identified as relevant data sources and the state of the art in anonymization and fingerprinting techniques is discussed. Based on legislation, data availability and privacy considerations, a practically applicable anonymization policy is presented.

Langone, M., Setola, R., Lopez, J..  2017.  Cybersecurity of Wearable Devices: An Experimental Analysis and a Vulnerability Assessment Method. 2017 IEEE 41st Annual Computer Software and Applications Conference (COMPSAC). 2:304–309.

The widespread diffusion of the Internet of Things (IoT) is introducing a huge number of Internet-connected devices in our daily life. Mainly, wearable devices are going to have a large impact on our lifestyle, especially in a healthcare scenario. In this framework, it is fundamental to secure exchanged information between these devices. Among other factors, it is important to take into account the link between a wearable device and a smart unit (e.g., smartphone). This connection is generally obtained via specific wireless protocols such as Bluetooth Low Energy (BLE): the main topic of this work is to analyse the security of this communication link. In this paper we expose, via an experimental campaign, a methodology to perform a vulnerability assessment (VA) on wearable devices communicating with a smartphone. In this way, we identify several security issues in a set of commercial wearable devices.

Hellman, Martin E..  2016.  Cybersecurity, Nuclear Security, Alan Turing, and Illogical Logic. Proceedings of the 2016 ACM SIGSAC Conference on Computer and Communications Security. :1–2.

My work that is being recognized by the 2015 ACM A. M. Turing Award is in cybersecurity, while my primary interest for the last thirty-five years is concerned with reducing the risk that nuclear deterrence will fail and destroy civilization. This Turing Lecture draws connections between those seemingly disparate areas as well as Alan Turing's elegant proof that the computable real numbers, while denumerable, are not effectively denumerable.

Stafford, Tom.  2017.  On Cybersecurity Loafing and Cybercomplacency. SIGMIS Database. 48:8–10.
As we begin to publish more articles in the area of cybersecurity, a case in point being the fine set of security papers presented in this particular issue as well as the upcoming special issue on Advances in Behavioral Cybersecurity Research which is currently in the review phase, it comes to mind that there is an emerging rubric of interest to the research community involved in security. That rubric concerns itself with the increasingly odd and inexplicable degree of comfort that computer users appear to have while operating in an increasingly threat-rich online environment. In my own work, I have noticed over time that users are blissfully unconcerned about malware threats (Poston et al., 2005; Stafford, 2005; Stafford and Poston, 2010; Stafford and Urbaczewski, 2004). This often takes the avenue of "it can't happen to me," or, "that's just not likely," but the fact is, since I first started noticing this odd nonchalance it seems like it is only getting worse, generally speaking. Mind you, a computer user who has been exploited and suffered harm from it will be vigilant to the end of his or her days, but for those who have scraped by, "no worries," is the order of the day, it seems to me. This is problematic because the exploits that are abroad in the online world these days are a whole order of magnitude more harmful than those that were around when I first started studying the matter a decade ago. I would not have commented on the matter, having long since chalked it up to the oddities of civilian computing, so to speak, but an odd pattern I encountered when engaging in a research study with trained corporate users brought the matter back to the fore recently. I have been collecting neurocogntive data on user response to security threats, and while my primary interest was to see if skin conductance or pupillary dilation varied during exposure to computer threat scenarios, I noticed an odd pattern that commanded my attention and actually derailed my study for a while as I dug in to examine it.
Lau, Pikkin, Wei, Wei, Wang, Lingfeng, Liu, Zhaoxi, Ten, Chee-Wooi.  2020.  A Cybersecurity Insurance Model for Power System Reliability Considering Optimal Defense Resource Allocation. IEEE Transactions on Smart Grid. 11:4403–4414.
With the increasing application of Information and Communication Technologies (ICTs), cyberattacks have become more prevalent against Cyber-Physical Systems (CPSs) such as the modern power grids. Various methods have been proposed to model the cybersecurity threats, but so far limited studies have been focused on the defensive strategies subject to the limited security budget. In this paper, the power supply reliability is evaluated considering the strategic allocation of defense resources. Specifically, the optimal mixed strategies are formulated by the Stackelberg Security Game (SSG) to allocate the defense resources on multiple targets subject to cyberattacks. The cyberattacks against the intrusion-tolerant Supervisory Control and Data Acquisition (SCADA) system are mathematically modeled by Semi-Markov Process (SMP) kernel. The intrusion tolerance capability of the SCADA system provides buffered residence time before the substation failure to enhance the network robustness against cyberattacks. Case studies of the cyberattack scenarios are carried out to demonstrate the intrusion tolerance capability. Depending on the defense resource allocation scheme, the intrusion-tolerant SCADA system possesses varying degrees of self-healing capability to restore to the good state and prevent the substations from failure. If more defense resources are invested on the substations, the intrusion tolerant capability can be further enhanced for protecting the substations. Finally, the actuarial insurance principle is designed to estimate transmission companies' individual premiums considering correlated cybersecurity risks. The proposed insurance premium principle is designed to provide incentive for investments on enhancing the intrusion tolerance capability, which is verified by the results of case studies.
Chatfield, A. T., Reddick, C. G..  2017.  Cybersecurity Innovation in Government: A Case Study of U.S. Pentagon's Vulnerability Reward Program. Proceedings of the 18th Annual International Conference on Digital Government Research. :64–73.
The U.S. federal governments and agencies face increasingly sophisticated and persistent cyber threats and cyberattacks from black hat hackers who breach cybersecurity for malicious purposes or for personal gain. With the rise of malicious attacks that caused untold financial damage and substantial reputational damage, private-sector high-tech firms such as Google, Microsoft and Yahoo have adopted an innovative practice known as vulnerability reward program (VRP) or bug bounty program which crowdsources software bug detection from the cybersecurity community. In an alignment with the 2016 U.S. Cybersecurity National Action Plan, the Department of Defense adopted a pilot VRP in 2016. This paper examines the Pentagon's VRP and examines how it may fit with the national cybersecurity policy and the need for new and enhanced cybersecurity capability development. Our case study results show the feasibility of the government adoption and implementation of the innovative concept of VRP to enhance the government cybersecurity posture.
Bertino, E., Hartman, N. W..  2015.  Cybersecurity for product lifecycle management a research roadmap. 2015 IEEE International Conference on Intelligence and Security Informatics (ISI). :114–119.

This paper introduces a research agenda focusing on cybersecurity in the context of product lifecycle management. The paper discusses research directions on critical protection techniques, including protection techniques from insider threat, access control systems, secure supply chains and remote 3D printing, compliance techniques, and secure collaboration techniques. The paper then presents an overview of DBSAFE, a system for protecting data from insider threat.

Schwab, Stephen, Kline, Erik.  2019.  Cybersecurity Experimentation at Program Scale: Guidelines and Principles for Future Testbeds. 2019 IEEE European Symposium on Security and Privacy Workshops (EuroS PW). :94–102.
Cybersecurity Experimentation is often viewed narrowly in terms of a single technology or experiment. This paper reviews the experimentation life-cycle for two large scale research efforts that span multiple technologies. We identify salient aspects of each cybersecurity program, and capture guidelines based on eight years of experience. Extrapolating, we identify four principles for building future experimental infrastructure: 1) Reduce the cognitive burden on experimenters when designing and operating experiments. 2) Allow experimenters to encode their goals and constraints. 3) Provide flexibility in experimental design. 4) Provide multifaceted guidance to help experimenters produce high-quality experiments. By following these principles, future cybersecurity testbeds can enable significantly higher-quality experiments.
Thomas, L. J., Balders, M., Countney, Z., Zhong, C., Yao, J., Xu, C..  2019.  Cybersecurity Education: From Beginners to Advanced Players in Cybersecurity Competitions. 2019 IEEE International Conference on Intelligence and Security Informatics (ISI). :149—151.

Cybersecurity competitions have been shown to be an effective approach for promoting student engagement through active learning in cybersecurity. Players can gain hands-on experience in puzzle-based or capture-the-flag type tasks that promote learning. However, novice players with limited prior knowledge in cybersecurity usually found difficult to have a clue to solve a problem and get frustrated at the early stage. To enhance student engagement, it is important to study the experiences of novices to better understand their learning needs. To achieve this goal, we conducted a 4-month longitudinal case study which involves 11 undergraduate students participating in a college-level cybersecurity competition, National Cyber League (NCL) competition. The competition includes two individual games and one team game. Questionnaires and in-person interviews were conducted before and after each game to collect the players' feedback on their experience, learning challenges and needs, and information about their motivation, interests and confidence level. The collected data demonstrate that the primary concern going into these competitions stemmed from a lack of knowledge regarding cybersecurity concepts and tools. Players' interests and confidence can be increased by going through systematic training.

Lukowiak, Marcin, Radziszowski, Stanisław, Vallino, James, Wood, Christopher.  2014.  Cybersecurity Education: Bridging the Gap Between Hardware and Software Domains. Trans. Comput. Educ.. 14:2:1–2:20.

With the continuous growth of cyberinfrastructure throughout modern society, the need for secure computing and communication is more important than ever before. As a result, there is also an increasing need for entry-level developers who are capable of designing and building practical solutions for systems with stringent security requirements. This calls for careful attention to algorithm choice and implementation method, as well as trade-offs between hardware and software implementations. This article describes motivation and efforts taken by three departments at Rochester Institute of Technology (Computer Engineering, Computer Science, and Software Engineering) that were focused on creating a multidisciplinary course that integrates the algorithmic, engineering, and practical aspects of security as exemplified by applied cryptography. In particular, the article presents the structure of this new course, topics covered, lab tools and results from the first two spring quarter offerings in 2011 and 2012.

Rajamäki, J., Nevmerzhitskaya, J., Virág, C..  2018.  Cybersecurity education and training in hospitals: Proactive resilience educational framework (Prosilience EF). 2018 IEEE Global Engineering Education Conference (EDUCON). :2042—2046.

Healthcare is a vital component of every nation's critical infrastructure, yet it is one of the most vulnerable sector for cyber-attacks. To enforce the knowledge on information security processes and data protection procedures, educational and training schemes should be establishedfor information technology (IT) staff working in healthcare settings. However, only training IT staff is not enough, as many of cybersecurity threats are caused by human errors or lack of awareness. Current awareness and training schemes are often implemented in silos, concentrating on one aspect of cybersecurity at a time. Proactive Resilience Educational Framework (Prosilience EF) provides a holistic cyber resilience and security framework for developing and delivering a multilateral educational and training scheme based on a proactive approach to cybersecurity. The framework is built on the principle that education and training must be interactive, guided, meaningful and directly relevant to the user' operational environment. The framework addresses capacity mapping, cyber resilience level measuring, utilizing available and mapping missing resources, adaptive learning technologies and dynamic content delivery. Prosilience EF launches an iterative process of awareness and training development with relevant stakeholders (end users - hospitals, healthcare authorities, cybersecurity training providers, industry members), evaluating the framework via joint exercises/workshops andfurther developing the framework.

Xu, Shouhuai.  2014.  Cybersecurity Dynamics. Proceedings of the 2014 Symposium and Bootcamp on the Science of Security. :14:1–14:2.

We explore the emerging field of Cybersecurity Dynamics, a candidate foundation for the Science of Cybersecurity.

Hastings, John C., Laverty, David M., Jahic, Admir, Morrow, D John, Brogan, Paul.  2020.  Cyber-security considerations for domestic-level automated demand-response systems utilizing public-key infrastructure and ISO/IEC 20922. 2020 31st Irish Signals and Systems Conference (ISSC). :1–6.
In this paper, the Authors present MQTT (ISO/IEC 20922), coupled with Public-key Infrastructure (PKI) as being highly suited to the secure and timely delivery of the command and control messages required in a low-latency Automated Demand Response (ADR) system which makes use of domestic-level electrical loads connected to the Internet. Several use cases for ADR are introduced, and relevant security considerations are discussed; further emphasizing the suitability of the proposed infrastructure. The authors then describe their testbed platform for testing ADR functionality, and finally discuss the next steps towards getting these kinds of technologies to the next stage.
Ionita, Drd. Irene.  2019.  Cybersecurity concerns on real time monitoring in electrical transmission and distribution systems (SMART GRIDS). 2019 54th International Universities Power Engineering Conference (UPEC). :1–4.
The virtual world does not observe national borders, has no uniform legal system, and does not have a common perception of security and privacy issues. It is however, relatively homogenous in terms of technology.A cyberattack on an energy delivery system can have significant impacts on the availability of a system to perform critical functions as well as the integrity of the system and the confidentiality of sensitive information.
Choejey, P., Fung, Chun Che, Wong, Kok Wai, Murray, D., Sonam, D..  2015.  Cybersecurity challenges for Bhutan. 2015 12th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON). :1–5.

Information and Communications Technologies (ICTs), especially the Internet, have become a key enabler for government organisations, businesses and individuals. With increasing growth in the adoption and use of ICT devices such as smart phones, personal computers and the Internet, Cybersecurity is one of the key concerns facing modern organisations in both developed and developing countries. This paper presents an overview of cybersecurity challenges in Bhutan, within the context that the nation is emerging as an ICT developing country. This study examines the cybersecurity incidents reported both in national media and government reports, identification and analysis of different types of cyber threats, understanding of the characteristics and motives behind cyber-attacks, and their frequency of occurrence since 1999. A discussion on an ongoing research study to investigate cybersecurity management and practices for Bhutan's government organisations is also highlighted.

Shah, P. R., Agarwal, A..  2020.  Cybersecurity Behaviour of Smartphone Users Through the Lens of Fogg Behaviour Model. 2020 3rd International Conference on Communication System, Computing and IT Applications (CSCITA). :79—82.

It is now a fact that human is the weakest link in the cybersecurity chain. Many theories from behavioural science like the theory of planned behaviour and protection motivation theory have been used to investigate the factors that affect the cybersecurity behaviour and practices of the end-user. In this paper, the researchers have used Fogg behaviour model (FBM) to study factors affecting the cybersecurity behaviour and practices of smartphone users. This study found that the odds of secure behaviour and practices by respondents with high motivation and high ability were 4.64 times more than the respondents with low motivation and low ability. This study describes how FBM may be used in the design and development of cybersecurity awareness program leading to a behaviour change.