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Serras, Paula, Ibarra-Berastegi, Gabriel, Saénz, Jon, Ulazia, Alain, Esnaola, Ganix.  2019.  Analysis of Wells-type turbines’ operational parameters during winter of 2014 at Mutriku wave farm. OCEANS 2019 – Marseille. :1—5.

Mutriku wave farm is the first commercial plant all around the world. Since July 2011 it has been continuously selling electricity to the grid. It operates with the OWC technology and has 14 operating Wells-type turbines. In the plant there is a SCADA data recording system that collects the most important parameters of the turbines; among them, the pressure in the inlet chamber, the position of the security valve (from fully open to fully closed) and the generated power in the last 5 minutes. There is also an electricity meter which provides information about the amount of electric energy sold to the grid. The 2014 winter (January, February and March), and especially the first fortnight of February, was a stormy winter with rough sea state conditions. This was reflected both in the performance of the turbines (high pressure values, up to 9234.2 Pa; low opening degrees of the security valve, down to 49.4°; and high power generation of about 7681.6 W, all these data being average values) and in the calculated capacity factor (CF = 0.265 in winter and CF = 0.294 in February 2014). This capacity factor is a good tool for the comparison of different WEC technologies or different locations and shows an important seasonal behavior.

Balijabudda, Venkata Sreekanth, Thapar, Dhruv, Santikellur, Pranesh, Chakraborty, Rajat Subhra, Chakrabarti, Indrajit.  2019.  Design of a Chaotic Oscillator based Model Building Attack Resistant Arbiter PUF. 2019 Asian Hardware Oriented Security and Trust Symposium (AsianHOST). :1—6.

Physical Unclonable Functions (PUFs) are vulnerable to various modelling attacks. The chaotic behaviour of oscillating systems can be leveraged to improve their security against these attacks. We have integrated an Arbiter PUF implemented on a FPGA with Chua's oscillator circuit to obtain robust final responses. These responses are tested against conventional Machine Learning and Deep Learning attacks for verifying security of the design. It has been found that such a design is robust with prediction accuracy of nearly 50%. Moreover, the quality of the PUF architecture is evaluated for uniformity and uniqueness metrics and Monte Carlo analysis at varying temperatures is performed for determining reliability.

Huang, Zhen, Lie, David, Tan, Gang, Jaeger, Trent.  2019.  Using Safety Properties to Generate Vulnerability Patches. 2019 IEEE Symposium on Security and Privacy (SP). :539–554.
Security vulnerabilities are among the most critical software defects in existence. When identified, programmers aim to produce patches that prevent the vulnerability as quickly as possible, motivating the need for automatic program repair (APR) methods to generate patches automatically. Unfortunately, most current APR methods fall short because they approximate the properties necessary to prevent the vulnerability using examples. Approximations result in patches that either do not fix the vulnerability comprehensively, or may even introduce new bugs. Instead, we propose property-based APR, which uses human-specified, program-independent and vulnerability-specific safety properties to derive source code patches for security vulnerabilities. Unlike properties that are approximated by observing the execution of test cases, such safety properties are precise and complete. The primary challenge lies in mapping such safety properties into source code patches that can be instantiated into an existing program. To address these challenges, we propose Senx, which, given a set of safety properties and a single input that triggers the vulnerability, detects the safety property violated by the vulnerability input and generates a corresponding patch that enforces the safety property and thus, removes the vulnerability. Senx solves several challenges with property-based APR: it identifies the program expressions and variables that must be evaluated to check safety properties and identifies the program scopes where they can be evaluated, it generates new code to selectively compute the values it needs if calling existing program code would cause unwanted side effects, and it uses a novel access range analysis technique to avoid placing patches inside loops where it could incur performance overhead. Our evaluation shows that the patches generated by Senx successfully fix 32 of 42 real-world vulnerabilities from 11 applications including various tools or libraries for manipulating graphics/media files, a programming language interpreter, a relational database engine, a collection of programming tools for creating and managing binary programs, and a collection of basic file, shell, and text manipulation tools.
Lefebvre, Dimitri, Hadjicostis, Christoforos N..  2019.  Trajectory-observers of timed stochastic discrete event systems: Applications to privacy analysis. 2019 6th International Conference on Control, Decision and Information Technologies (CoDIT). :1078–1083.
Various aspects of security and privacy in many application domains can be assessed based on proper analysis of successive measurements that are collected on a given system. This work is devoted to such issues in the context of timed stochastic Petri net models. We assume that certain events and part of the marking trajectories are observable to adversaries who aim to determine when the system is performing secret operations, such as time intervals during which the system is executing certain critical sequences of events (as captured, for instance, in language-based opacity formulations). The combined use of the k-step trajectory-observer and the Markov model of the stochastic Petri net leads to probabilistic indicators helpful for evaluating language-based opacity of the given system, related timing aspects, and possible strategies to improve them.
Djoudi, Aghiles, Pujolle, Guy.  2019.  Social Privacy Score Through Vulnerability Contagion Process. 2019 Fifth Conference on Mobile and Secure Services (MobiSecServ). :1–6.
The exponential usage of messaging services for communication raises many questions in privacy fields. Privacy issues in such services strongly depend on the graph-theoretical properties of users' interactions representing the real friendships between users. One of the most important issues of privacy is that users may disclose information of other users beyond the scope of the interaction, without realizing that such information could be aggregated to reveal sensitive information. Determining vulnerable interactions from non-vulnerable ones is difficult due to the lack of awareness mechanisms. To address this problem, we analyze the topological relationships with the level of trust between users to notify each of them about their vulnerable social interactions. Particularly, we analyze the impact of trusting vulnerable friends in infecting other users' privacy concerns by modeling a new vulnerability contagion process. Simulation results show that over-trusting vulnerable users speeds the vulnerability diffusion process through the network. Furthermore, vulnerable users with high reputation level lead to a high convergence level of infection, this means that the vulnerability contagion process infects the biggest number of users when vulnerable users get a high level of trust from their interlocutors. This work contributes to the development of privacy awareness framework that can alert users of the potential private information leakages in their communications.
Lecuyer, Mathias, Atlidakis, Vaggelis, Geambasu, Roxana, Hsu, Daniel, Jana, Suman.  2019.  Certified Robustness to Adversarial Examples with Differential Privacy. 2019 IEEE Symposium on Security and Privacy (SP). :656–672.
Adversarial examples that fool machine learning models, particularly deep neural networks, have been a topic of intense research interest, with attacks and defenses being developed in a tight back-and-forth. Most past defenses are best effort and have been shown to be vulnerable to sophisticated attacks. Recently a set of certified defenses have been introduced, which provide guarantees of robustness to norm-bounded attacks. However these defenses either do not scale to large datasets or are limited in the types of models they can support. This paper presents the first certified defense that both scales to large networks and datasets (such as Google's Inception network for ImageNet) and applies broadly to arbitrary model types. Our defense, called PixelDP, is based on a novel connection between robustness against adversarial examples and differential privacy, a cryptographically-inspired privacy formalism, that provides a rigorous, generic, and flexible foundation for defense.
Sule, Rupali, Chaudhari, Sangita.  2018.  Preserving Location Privacy in Geosocial Applications using Error Based Transformation. 2018 International Conference on Smart City and Emerging Technology (ICSCET). :1–4.
Geo-social applications deal with constantly sharing user's current geographic information in terms of location (Latitude and Longitude). Such application can be used by many people to get information about their surrounding with the help of their friend's locations and their recommendations. But without any privacy protection, these systems can be easily misused by tracking the users. We are proposing Error Based Transformation (ERB) approach for location transformation which provides significantly improved location privacy without adding uncertainty in to query results or relying on strong assumptions about server security. The key insight is to apply secure user-specific, distance-preserving coordinate transformations to all location data shared with the server. Only the friends of a user can get exact co-ordinates by applying inverse transformation with secret key shared with them. Servers can evaluate all location queries correctly on transformed data. ERB privacy mechanism guarantee that servers are unable to see or infer actual location data from the transformed data. ERB privacy mechanism is successful against a powerful adversary model where prototype measurements used to show that it provides with very little performance overhead making it suitable for today's mobile device.
Sule, Rupali, Chaudhari, Sangita.  2018.  Preserving Location Privacy in Geosocial Applications using Error Based Transformation. 2018 International Conference on Smart City and Emerging Technology (ICSCET). :1–4.
Geo-social applications deal with constantly sharing user's current geographic information in terms of location (Latitude and Longitude). Such application can be used by many people to get information about their surrounding with the help of their friend's locations and their recommendations. But without any privacy protection, these systems can be easily misused by tracking the users. We are proposing Error Based Transformation (ERB) approach for location transformation which provides significantly improved location privacy without adding uncertainty in to query results or relying on strong assumptions about server security. The key insight is to apply secure user-specific, distance-preserving coordinate transformations to all location data shared with the server. Only the friends of a user can get exact co-ordinates by applying inverse transformation with secret key shared with them. Servers can evaluate all location queries correctly on transformed data. ERB privacy mechanism guarantee that servers are unable to see or infer actual location data from the transformed data. ERB privacy mechanism is successful against a powerful adversary model where prototype measurements used to show that it provides with very little performance overhead making it suitable for today's mobile device.
Gorbenko, Anatoliy, Romanovsky, Alexander, Tarasyuk, Olga, Biloborodov, Oleksandr.  2020.  From Analyzing Operating System Vulnerabilities to Designing Multiversion Intrusion-Tolerant Architectures. IEEE Transactions on Reliability. 69:22—39.

This paper analyzes security problems of modern computer systems caused by vulnerabilities in their operating systems (OSs). Our scrutiny of widely used enterprise OSs focuses on their vulnerabilities by examining the statistical data available on how vulnerabilities in these systems are disclosed and eliminated, and by assessing their criticality. This is done by using statistics from both the National Vulnerabilities Database and the Common Vulnerabilities and Exposures System. The specific technical areas the paper covers are the quantitative assessment of forever-day vulnerabilities, estimation of days-of-grey-risk, the analysis of the vulnerabilities severity and their distributions by attack vector and impact on security properties. In addition, the study aims to explore those vulnerabilities that have been found across a diverse range of OSs. This leads us to analyzing how different intrusion-tolerant architectures deploying the OS diversity impact availability, integrity, and confidentiality.

Khorsandroo, Sajad, Tosun, Ali Saman.  2019.  White Box Analysis at the Service of Low Rate Saturation Attacks on Virtual SDN Data Plane. 2019 IEEE 44th LCN Symposium on Emerging Topics in Networking (LCN Symposium). :100—107.

Today's virtual switches not only support legacy network protocols and standard network management interfaces, but also become adapted to OpenFlow as a prevailing communication protocol. This makes them a core networking component of today's virtualized infrastructures which are able to handle sophisticated networking scenarios in a flexible and software-defined manner. At the same time, these virtual SDN data planes become high-value targets because a compromised switch is hard to detect while it affects all components of a virtualized/SDN-based environment.Most of the well known programmable virtual switches in the market are open source which makes them cost-effective and yet highly configurable options in any network infrastructure deployment. However, this comes at a cost which needs to be addressed. Accordingly, this paper raises an alarm on how attackers may leverage white box analysis of software switch functionalities to lunch effective low profile attacks against it. In particular, we practically present how attackers can systematically take advantage of static and dynamic code analysis techniques to lunch a low rate saturation attack on virtual SDN data plane in a cloud data center.

Mohsen, Fadi, Jafaarian, Haadi.  2019.  Raising the Bar Really High: An MTD Approach to Protect Data in Embedded Browsers. 2019 IEEE 43rd Annual Computer Software and Applications Conference (COMPSAC). 1:786—794.
The safety of web browsers is essential to the privacy of Internet users and the security of their computing systems. In the last few years, there have been several cyber attacks geared towards compromising surfers' data and systems via exploiting browser-based vulnerabilities. Android and a number of mobile operating systems have been supporting a UI component called WebView, which can be embedded in any mobile application to render the web contents. Yet, this mini-browser component has been found to be vulnerable to various kinds of attacks. For instance, an attacker in her WebView-Embedded app can inject malicious JavaScripts into the WebView to modify the web contents or to steal user's input values. This kind of attack is particularly challenging due to the full control of attackers over the content of the loaded pages. In this paper, we are proposing and testing a server-side moving target defense technique to counter the risk of JavaScript injection attacks on mobile WebViews. The solution entails creating redundant HTML forms, randomizing their attributes and values, and asserting stealthy prompts for the user data. The solution does not dictate any changes to the browser or applications codes, neither it requires key sharing with benign clients. The results of our performance and security analysis suggest that our proposed approach protects the confidentiality and integrity of user input values with minimum overhead.
Stark, Emily, Sleevi, Ryan, Muminovic, Rijad, O'Brien, Devon, Messeri, Eran, Felt, Adrienne Porter, McMillion, Brendan, Tabriz, Parisa.  2019.  Does Certificate Transparency Break the Web? Measuring Adoption and Error Rate 2019 IEEE Symposium on Security and Privacy (SP). :211—226.
Certificate Transparency (CT) is an emerging system for enabling the rapid discovery of malicious or misissued certificates. Initially standardized in 2013, CT is now finally beginning to see widespread support. Although CT provides desirable security benefits, web browsers cannot begin requiring all websites to support CT at once, due to the risk of breaking large numbers of websites. We discuss challenges for deployment, analyze the adoption of CT on the web, and measure the error rates experienced by users of the Google Chrome web browser. We find that CT has so far been widely adopted with minimal breakage and warnings. Security researchers often struggle with the tradeoff between security and user frustration: rolling out new security requirements often causes breakage. We view CT as a case study for deploying ecosystem-wide change while trying to minimize end user impact. We discuss the design properties of CT that made its success possible, as well as draw lessons from its risks and pitfalls that could be avoided in future large-scale security deployments.
Oest, Adam, Safaei, Yeganeh, Doupé, Adam, Ahn, Gail-Joon, Wardman, Brad, Tyers, Kevin.  2019.  PhishFarm: A Scalable Framework for Measuring the Effectiveness of Evasion Techniques against Browser Phishing Blacklists. 2019 IEEE Symposium on Security and Privacy (SP). :1344—1361.

Phishing attacks have reached record volumes in recent years. Simultaneously, modern phishing websites are growing in sophistication by employing diverse cloaking techniques to avoid detection by security infrastructure. In this paper, we present PhishFarm: a scalable framework for methodically testing the resilience of anti-phishing entities and browser blacklists to attackers' evasion efforts. We use PhishFarm to deploy 2,380 live phishing sites (on new, unique, and previously-unseen .com domains) each using one of six different HTTP request filters based on real phishing kits. We reported subsets of these sites to 10 distinct anti-phishing entities and measured both the occurrence and timeliness of native blacklisting in major web browsers to gauge the effectiveness of protection ultimately extended to victim users and organizations. Our experiments revealed shortcomings in current infrastructure, which allows some phishing sites to go unnoticed by the security community while remaining accessible to victims. We found that simple cloaking techniques representative of real-world attacks- including those based on geolocation, device type, or JavaScript- were effective in reducing the likelihood of blacklisting by over 55% on average. We also discovered that blacklisting did not function as intended in popular mobile browsers (Chrome, Safari, and Firefox), which left users of these browsers particularly vulnerable to phishing attacks. Following disclosure of our findings, anti-phishing entities are now better able to detect and mitigate several cloaking techniques (including those that target mobile users), and blacklisting has also become more consistent between desktop and mobile platforms- but work remains to be done by anti-phishing entities to ensure users are adequately protected. Our PhishFarm framework is designed for continuous monitoring of the ecosystem and can be extended to test future state-of-the-art evasion techniques used by malicious websites.

Kiss, Ákos, Hodován, Renáta.  2019.  Security-Related Commits in Open Source Web Browser Projects. 2019 34th IEEE/ACM International Conference on Automated Software Engineering Workshop (ASEW). :57—60.
The security of web browsers is of paramount importance, these days perhaps more than ever. Unfortunately, acquiring real data for security-related research is not an easy task, as access to sensitive information is rarely granted to researchers who are not members of a trusted security team. In this paper, we describe a method to mine security-related commits from open source software repositories, even if the reports of already fixed security issues have access restrictions, and we show the applicability of the method on two popular web browser projects. We also made the mined dataset available, listing more than 13,000 security-related commits, with which we hope to facilitate research on security-targeted bug prediction.
Jmila, Houda, Blanc, Gregory.  2019.  Designing Security-Aware Service Requests for NFV-Enabled Networks. 2019 28th International Conference on Computer Communication and Networks (ICCCN). :1—9.

Network Function Virtualization (NFV) is a recent concept where virtualization enables the shift from network functions (e.g., routers, switches, load-balancers, proxies) on specialized hardware appliances to software images running on all-purpose, high-volume servers. The resource allocation problem in the NFV environment has received considerable attention in the past years. However, little attention was paid to the security aspects of the problem in spite of the increasing number of vulnerabilities faced by cloud-based applications. Securing the services is an urgent need to completely benefit from the advantages offered by NFV. In this paper, we show how a network service request, composed of a set of service function chains (SFC) should be modified and enriched to take into consideration the security requirements of the supported service. We examine the well-known security best practices and propose a two-step algorithm that extends the initial SFC requests to a more complex chaining model that includes the security requirements of the service.

Yang, Zihan, Mi, Zeyu, Xia, Yubin.  2019.  Undertow: An Intra-Kernel Isolation Mechanism for Hardware-Assisted Virtual Machines. 2019 IEEE International Conference on Service-Oriented System Engineering (SOSE). :257—2575.
The prevalence of Cloud Computing has appealed many users to put their business into low-cost and flexible cloud servers instead of bare-metal machines. Most virtual machines in the cloud run commodity operating system(e.g., linux), and the complexity of such operating systems makes them more bug-prone and easier to be compromised. To mitigate the security threats, previous works attempt to mediate and filter system calls, transform all unpopular paths into popular paths, or implement a nested kernel along with the untrusted outter kernel to enforce certain security policies. However, such solutions only enforce read-only protection or assume that popular paths in the kernel to contain almost no bug, which is not always the case in the real world. To overcome their shortcomings and combine their advantages as much as possible, we propose a hardware-assisted isolation mechanism that isolates untrusted part of the kernel. To achieve isolation, we prepare multiple restricted Extended Page Table (EPT) during boot time, each of which has certain critical data unmapped from it so that the code executing in the isolated environment could not access sensitive data. We leverage the VMFUNC instruction already available in recent Intel processors to directly switch to another pre-defined EPT inside guest virtual machine without trapping into the underlying hypervisor, which is faster than the traditional trap-and-emulate procedure. The semantic gap is minimized and real-time check is achieved by allowing EPT violations to be converted to Virtualization Exception (VE), which could be handled inside guest kernel in non-root mode. Our preliminary evaluation shows that with hardware virtualization feature, we are able to run the untrusted code in an isolated environment with negligible overhead.
Vladimirovich, Menshikh Valerii, Iurevich, Kalkov Dmitrii, Evgenevna, Spiridonova Natalia.  2019.  Model of optimization of arrangement of video surveillance means with regard to ensuring their own security. 2019 1st International Conference on Control Systems, Mathematical Modelling, Automation and Energy Efficiency (SUMMA). :4–7.
Currently, video surveillance systems play an important role in ensuring the safety of citizens, their property, etc., which greatly contributes to the reduction of crime. Due to the high intrinsic value and/or high efficiency of their use for the prevention and detection of crimes, they themselves often become the objects of illegal actions (theft, damage). The main purpose of video surveillance systems is to provide continuous visual monitoring of the situation at a particular facility or territory, as well as event registration. The breakdown of the camera is detected by the loss of signal in the control center. However, the absence of a signal for reasons other than these can also be caused by an accident on the power line, a communication channel break, software or hardware breakdown of the camera itself. In this regard, there is a problem of determining the exact cause of the lack of signal and, consequently, the need for a rapid response to it. The paper proposes an approach of video surveillance arrangement according to their main functional purpose, as well as their ability to monitor each other. Based on this approach, a mathematical model of the choice of locations and conditions of location of video surveillance equipment from a set of potentially acceptable as a problem of nonlinear Boolean programming is developed. This model maximizes the functionality of the video surveillance system, taking into account the importance of areas and objects of surveillance with restrictions on the number of video surveillance of each type, the nature of the terrain and existing buildings. An algorithm for solving this problem is proposed.
Mohanta, Bhabendu K., Panda, Soumyashree S., Satapathy, Utkalika, Jena, Debasish, Gountia, Debasis.  2019.  Trustworthy Management in Decentralized IoT Application using Blockchain. 2019 10th International Conference on Computing, Communication and Networking Technologies (ICCCNT). :1–5.
Internet of Things (IoT) as per estimated will connect 50 billion devices by 2020. Since its evolution, IoT technology provides lots of flexibility to develop and implement any application. Most of the application improves the human living standard and also makes life easy to access and monitoring the things in real time. Though there exist some security and privacy issues in IoT system like authentication, computation, data modification, trust among users. In this paper, we have identified the IoT application like insurance, supply chain system, smart city and smart car where trust among associated users is an major issue. The current centralized system does not provide enough trust between users. Using Blockchain technology we have shown that trust issue among users can be managed in a decentralized way so that information can be traceable and identify/verify any time. Blockchain has properties like distributed, digitally share and immutable which enhance security. For Blockchain implementation, Ethereum platform is used.
Brito, Andrey, Brasileiro, Francisco, Blanquer, Ignacio, Silva, Altigran, Carvalho, André.  2019.  ATMOSPHERE: Adaptive, Trustworthy, Manageable, Orchestrated, Secure, Privacy-Assuring, Hybrid Ecosystem for Resilient Cloud Computing. 2019 9th Latin-American Symposium on Dependable Computing (LADC). :1–4.
This paper describes the goals of the ATMOSPHERE project, which is a multi-institutional research and development (R&D) effort aiming at designing and implementing a framework and platform to develop, build, deploy, measure and evolve trustworthy, cloud-enabled applications. The proposed system addresses the federation of geographically distributed cloud computing providers that rely on lightweight virtualization, and provide access to heterogeneous sets of resources. In addition, the system also considers both classic trustworthiness properties from the systems community, such as dependability and security, and from the machine learning community, such as fairness and transparency. We present the architecture that has been proposed to address these challenges and discuss some preliminary results.
Rivera, Sean, Lagraa, Sofiane, Nita-Rotaru, Cristina, Becker, Sheila, State, Radu.  2019.  ROS-Defender: SDN-Based Security Policy Enforcement for Robotic Applications. 2019 IEEE Security and Privacy Workshops (SPW). :114–119.
In this paper we propose ROS-Defender, a holistic approach to secure robotics systems, which integrates a Security Event Management System (SIEM), an intrusion prevention system (IPS) and a firewall for a robotic system. ROS-Defender combines anomaly detection systems at application (ROS) level and network level, with dynamic policy enforcement points using software defined networking (SDN) to provide protection against a large class of attacks. Although SIEMs, IPS, and firewall have been previously used to secure computer networks, ROSDefender is applying them for the specific use case of robotic systems, where security is in many cases an afterthought.
Papachristou, Konstantinos, Theodorou, Traianos, Papadopoulos, Stavros, Protogerou, Aikaterini, Drosou, Anastasios, Tzovaras, Dimitrios.  2019.  Runtime and Routing Security Policy Verification for Enhanced Quality of Service of IoT Networks. 2019 Global IoT Summit (GIoTS). :1–6.
The Internet of Things (IoT) is growing rapidly controlling and connecting thousands of devices every day. The increased number of interconnected devices increase the network traffic leading to energy and Quality of Service efficiency problems of the IoT network. Therefore, IoT platforms and networks are susceptible to failures and attacks that have significant economic and security consequences. In this regard, implementing effective secure IoT platforms and networks are valuable for both the industry and society. In this paper, we propose two frameworks that aim to verify a number of security policies related to runtime information of the network and dynamic flow routing paths, respectively. The underlying rationale is to allow the operator of an IoT network in order to have an overall control of the network and to define different policies based on the demands of the network and the use cases (e.g., achieving more secure or faster network).
O’Raw, John, Laverty, David, Morrow, D. John.  2019.  Securing the Industrial Internet of Things for Critical Infrastructure (IIoT-CI). 2019 IEEE 5th World Forum on Internet of Things (WF-IoT). :70–75.
The Industrial Internet of Things (IIoT) is a term applied to the industrial application of M2M devices. The security of IIoT devices is a difficult problem and where the automation of critical infrastructure is intended, risks may be unacceptable. Remote attacks are a significant threat and solutions are sought which are secure by default. The problem space may be analyzed using threat modelling methods. Software Defined Networks (SDN) provide mitigation for remote attacks which exploit local area networks. Similar concepts applied to the WAN may improve availability and performance and provide granular data on link characteristics. Schemes such as the Software Defined Perimeter allow IIoT devices to communicate on the Internet, mitigating avenues of remote attack. Finally, separation of duties at the IIoT device may prevent attacks on the integrity of the device or the confidentiality and integrity of its communications. Work remains to be done on the mitigation of DDoS.
Morishita, Shun, Hoizumi, Takuya, Ueno, Wataru, Tanabe, Rui, Gañán, Carlos, van Eeten, Michel J.G., Yoshioka, Katsunari, Matsumoto, Tsutomu.  2019.  Detect Me If You… Oh Wait. An Internet-Wide View of Self-Revealing Honeypots. 2019 IFIP/IEEE Symposium on Integrated Network and Service Management (IM). :134–143.
Open-source honeypots are a vital component in the protection of networks and the observation of trends in the threat landscape. Their open nature also enables adversaries to identify the characteristics of these honeypots in order to detect and avoid them. In this study, we investigate the prevalence of 14 open- source honeypots running more or less default configurations, making them easily detectable by attackers. We deploy 20 simple signatures and test them for false positives against servers for domains in the Alexa top 10,000, official FTP mirrors, mail servers in real operation, and real IoT devices running telnet. We find no matches, suggesting good accuracy. We then measure the Internet-wide prevalence of default open-source honeypots by matching the signatures with Censys scan data and our own scans. We discovered 19,208 honeypots across 637 Autonomous Systems that are trivially easy to identify. Concentrations are found in research networks, but also in enterprise, cloud and hosting networks. While some of these honeypots probably have no operational relevance, e.g., they are student projects, this explanation does not fit the wider population. One cluster of honeypots was confirmed to belong to a well-known security center and was in use for ongoing attack monitoring. Concentrations in an another cluster appear to be the result of government incentives. We contacted 11 honeypot operators and received response from 4 operators, suggesting the problem of lack of network hygiene. Finally, we find that some honeypots are actively abused by attackers for hosting malicious binaries. We notified the owners of the detected honeypots via their network operators and provided recommendations for customization to avoid simple signature-based detection. We also shared our results with the honeypot developers.
Wadsworth, Anthony, Thanoon, Mohammed I., McCurry, Charles, Sabatto, Saleh Zein.  2019.  Development of IIoT Monitoring and Control Security Scheme for Cyber Physical Systems. 2019 SoutheastCon. :1–5.
Industry 4.0 or the fourth industrial revolution encapsulates future industry development trends to achieve more intelligent manufacturing processes, including reliance on Cyber Physical Systems (CPS). The increase in online access and control given by the incorporation of CPSs introduces a new challenge securing the operations of the CPS in that they are not supported by standard security protocols. This paper describes a process used to effectively protect the operations of an IIoT system by implementing security protocols on the CPS within the IIoT. A series of predefined boundary conditions of the safety critical parameters for which a heating and cooling CPS can safely operate within were established. If the CPS is commended to operate outside of these boundaries, it will disconnect from all external communication network and default to some pre-defined safe-operation mode until the system has been evaluated locally by an administrator and released from the safe-mode. This method was tested and validated by establishing a sample IIoT and CPS testbed setup which monitor and control the temperature of a target environment. An attack was initiated to force the target environment outside of the determined safety-critical parameters. The system responded by disabling all network ports and defaulted to the safe-operation mode established previously.
Chowdhury, Nahida Sultana, Raje, Rajeev R..  2019.  SERS: A Security-Related and Evidence-Based Ranking Scheme for Mobile Apps. 2019 First IEEE International Conference on Trust, Privacy and Security in Intelligent Systems and Applications (TPS-ISA). :130–139.
In recent years, the number of smart mobile devices has rapidly increased worldwide. This explosion of continuously connected mobile devices has resulted in an exponential growth in the number of publically available mobile Apps. To facilitate the selection of mobile Apps, from various available choices, the App distribution platforms typically rank/recommend Apps based on average star ratings, the number of downloads, and associated reviews - the external aspect of an App. However, these ranking schemes typically tend to ignore critical internal aspects (e.g., security vulnerabilities) of the Apps. Such an omission of internal aspects is certainly not desirable, especially when many of the users do not possess the necessary skills to evaluate the internal aspects and choose an App based on the default ranking scheme which uses the external aspect. In this paper, we build upon our earlier efforts by focusing specifically on the security-related internal aspect of an App and its combination with the external aspect computed from the user reviews by identifying security-related comments.We use this combination to rank-order similar Apps. We evaluate our approach on publicly available Apps from the Google PlayStore and compare our ranking with prevalent ranking techniques such as the average star ratings. The experimental results indicate the effectiveness of our proposed approach.