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Byun, Minjae, Lee, Yongjun, Choi, Jin-Young.  2019.  Risk and avoidance strategy for blocking mechanism of SDN-based security service. 2019 21st International Conference on Advanced Communication Technology (ICACT). :187–190.

Software-Defined Network (SDN) is the dynamic network technology to address the issues of traditional networks. It provides centralized view of the whole network through decoupling the control planes and data planes of a network. Most SDN-based security services globally detect and block a malicious host based on IP address. However, the IP address is not verified during the forwarding process in most cases and SDN-based security service may block a normal host with forged IP address in the whole network, which means false-positive. In this paper, we introduce an attack scenario that uses forged packets to make the security service consider a victim host as an attacker so that block the victim. We also introduce cost-effective risk avoidance strategy.

Byun, Jin Wook.  2019.  An efficient multi-factor authenticated key exchange with physically unclonable function. 2019 International Conference on Electronics, Information, and Communication (ICEIC). :1–4.

In this paper, we propose an efficient and secure physically unclonable function based multi-factor authenticated key exchange (PUF-MAKE). In a PUF-MAKE setting, we suppose two participants; a user and a server. The user keeps multi-factor authenticators and securely holds a PUF-embedded device while the server maintains PUF outputs for authentication. We first study on how to efficiently construct a PUF-MAKE protocol. The main difficulty comes from that it should establish a common key from both multi-factor authenticators and a PUF-embedded device. Our construction is the first secure PUF-MAKE protocol that just needs three communication flows.

Byrne, K., Marín, C..  2018.  Human Trust in Robots When Performing a Service. 2018 IEEE 27th International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE). :9—14.

The presence of robots is becoming more apparent as technology progresses and the market focus transitions from smart phones to robotic personal assistants such as those provided by Amazon and Google. The integration of robots in our societies is an inevitable tendency in which robots in many forms and with many functionalities will provide services to humans. This calls for an understanding of how humans are affected by both the presence of and the reliance on robots to perform services for them. In this paper we explore the effects that robots have on humans when a service is performed on request. We expose three groups of human participants to three levels of service completion performed by robots. We record and analyse human perceptions such as propensity to trust, competency, responsiveness, sociability, and team work ability. Our results demonstrate that humans tend to trust robots and are more willing to interact with them when they autonomously recover from failure by requesting help from other robots to fulfil their service. This supports the view that autonomy and team working capabilities must be brought into robots in an effort to strengthen trust in robots performing a service.

Byrenheid, M., Rossberg, M., Schaefer, G., Dorn, R..  2017.  Covert-channel-resistant congestion control for traffic normalization in uncontrolled networks. 2017 IEEE International Conference on Communications (ICC). :1–7.

Traffic normalization, i.e. enforcing a constant stream of fixed-length packets, is a well-known measure to completely prevent attacks based on traffic analysis. In simple configurations, the enforced traffic rate can be statically configured by a human operator, but in large virtual private networks (VPNs) the traffic pattern of many connections may need to be adjusted whenever the overlay topology or the transport capacity of the underlying infrastructure changes. We propose a rate-based congestion control mechanism for automatic adjustment of traffic patterns that does not leak any information about the actual communication. Overly strong rate throttling in response to packet loss is avoided, as the control mechanism does not change the sending rate immediately when a packet loss was detected. Instead, an estimate of the current packet loss rate is obtained and the sending rate is adjusted proportionally. We evaluate our control scheme based on a measurement study in a local network testbed. The results indicate that the proposed approach avoids network congestion, enables protected TCP flows to achieve an increased goodput, and yet ensures appropriate traffic flow confidentiality.

Bychkov, Igor, Feoktistov, Alexander, Gorsky, Sergey, Edelev, Alexei, Sidorov, Ivan, Kostromin, Roman, Fereferov, Evgeniy, Fedorov, Roman.  2020.  Supercomputer Engineering for Supporting Decision-making on Energy Systems Resilience. 2020 IEEE 14th International Conference on Application of Information and Communication Technologies (AICT). :1—6.
We propose a new approach to creating a subject-oriented distributed computing environment. Such an environment is used to support decision-making in solving relevant problems of ensuring energy systems resilience. The proposed approach is based on the idea of advancing and integrating the following important capabilities in supercomputer engineering: continuous integration, delivery, and deployment of the system and applied software, high-performance computing in heterogeneous environments, multi-agent intelligent computation planning and resource allocation, big data processing and geo-information servicing for subject information, including weakly structured data, and decision-making support. This combination of capabilities and their advancing are unique to the subject domain under consideration, which is related to combinatorial studying critical objects of energy systems. Evaluation of decision-making alternatives is carrying out through applying combinatorial modeling and multi-criteria selection rules. The Orlando Tools framework is used as the basis for an integrated software environment. It implements a flexible modular approach to the development of scientific applications (distributed applied software packages).
Byabazaire, J., O'Hare, G., Delaney, D..  2020.  Data Quality and Trust : A Perception from Shared Data in IoT. 2020 IEEE International Conference on Communications Workshops (ICC Workshops). :1—6.

Internet of Things devices and data sources areseeing increased use in various application areas. The pro-liferation of cheaper sensor hardware has allowed for widerscale data collection deployments. With increased numbers ofdeployed sensors and the use of heterogeneous sensor typesthere is increased scope for collecting erroneous, inaccurate orinconsistent data. This in turn may lead to inaccurate modelsbuilt from this data. It is important to evaluate this data asit is collected to determine its validity. This paper presents ananalysis of data quality as it is represented in Internet of Things(IoT) systems and some of the limitations of this representation. The paper discusses the use of trust as a heuristic to drive dataquality measurements. Trust is a well-established metric that hasbeen used to determine the validity of a piece or source of datain crowd sourced or other unreliable data collection techniques. The analysis extends to detail an appropriate framework forrepresenting data quality effectively within the big data modeland why a trust backed framework is important especially inheterogeneously sourced IoT data streams.

Buzdalov, Maxim.  2016.  An Algorithm for Computing Lower Bounds for Unrestricted Black-Box Complexities. Proceedings of the 2016 on Genetic and Evolutionary Computation Conference Companion. :147–148.

Finding and proving lower bounds on black-box complexities is one of the hardest problems in theory of randomized search heuristics. Until recently, there were no general ways of doing this, except for information theoretic arguments similar to the one of Droste, Jansen and Wegener. In a recent paper by Buzdalov, Kever and Doerr, a theorem is proven which may yield tighter bounds on unrestricted black-box complexity using certain problem-specific information. To use this theorem, one should split the search process into a finite number of states, describe transitions between states, and for each state specify (and prove) the maximum number of different answers to any query. We augment these state constraints by one more kind of constraints on states, namely, the maximum number of different currently possible optima. An algorithm is presented for computing the lower bounds based on these constraints. We also empirically show improved lower bounds on black-box complexity of OneMax and Mastermind.

Butun, Ismail, Österberg, Patrik, Gidlund, Mikael.  2019.  Preserving Location Privacy in Cyber-Physical Systems. 2019 IEEE Conference on Communications and Network Security (CNS). :1–6.
The trending technological research platform is Internet of Things (IoT)and most probably it will stay that way for a while. One of the main application areas of IoT is Cyber-Physical Systems (CPSs), in which IoT devices can be leveraged as actuators and sensors in accordance with the system needs. The public acceptance and adoption of CPS services and applications will create a huge amount of privacy issues related to the processing, storage and disclosure of the user location information. As a remedy, our paper proposes a methodology to provide location privacy for the users of CPSs. Our proposal takes advantage of concepts such as mix-zone, context-awareness, and location-obfuscation. According to our best knowledge, the proposed methodology is the first privacy-preserving location service for CPSs that offers adaptable privacy levels related to the current context of the user.
Butun, I., Morgera, S.D., Sankar, R..  2014.  A Survey of Intrusion Detection Systems in Wireless Sensor Networks. Communications Surveys Tutorials, IEEE. 16:266-282.

Wireless Sensor Networking is one of the most promising technologies that have applications ranging from health care to tactical military. Although Wireless Sensor Networks (WSNs) have appealing features (e.g., low installation cost, unattended network operation), due to the lack of a physical line of defense (i.e., there are no gateways or switches to monitor the information flow), the security of such networks is a big concern, especially for the applications where confidentiality has prime importance. Therefore, in order to operate WSNs in a secure way, any kind of intrusions should be detected before attackers can harm the network (i.e., sensor nodes) and/or information destination (i.e., data sink or base station). In this article, a survey of the state-of-the-art in Intrusion Detection Systems (IDSs) that are proposed for WSNs is presented. Firstly, detailed information about IDSs is provided. Secondly, a brief survey of IDSs proposed for Mobile Ad-Hoc Networks (MANETs) is presented and applicability of those systems to WSNs are discussed. Thirdly, IDSs proposed for WSNs are presented. This is followed by the analysis and comparison of each scheme along with their advantages and disadvantages. Finally, guidelines on IDSs that are potentially applicable to WSNs are provided. Our survey is concluded by highlighting open research issues in the field.

Buttigieg, R., Farrugia, M., Meli, C..  2017.  Security issues in controller area networks in automobiles. 2017 18th International Conference on Sciences and Techniques of Automatic Control and Computer Engineering (STA). :93–98.
Modern vehicles may contain a considerable number of ECUs (Electronic Control Units) which are connected through various means of communication, with the CAN (Controller Area Network) protocol being the most widely used. However, several vulnerabilities such as the lack of authentication and the lack of data encryption have been pointed out by several authors, which ultimately render vehicles unsafe to their users and surroundings. Moreover, the lack of security in modern automobiles has been studied and analyzed by other researchers as well as several reports about modern car hacking have (already) been published. The contribution of this work aimed to analyze and test the level of security and how resilient is the CAN protocol by taking a BMW E90 (3-series) instrument cluster as a sample for a proof of concept study. This investigation was carried out by building and developing a rogue device using cheap commercially available components while being connected to the same CAN-Bus as a man in the middle device in order to send spoofed messages to the instrument cluster.
Butt, M.I.A..  2014.  BIOS integrity an advanced persistent threat. Information Assurance and Cyber Security (CIACS), 2014 Conference on. :47-50.

Basic Input Output System (BIOS) is the most important component of a computer system by virtue of its role i.e., it holds the code which is executed at the time of startup. It is considered as the trusted computing base, and its integrity is extremely important for smooth functioning of the system. On the contrary, BIOS of new computer systems (servers, laptops, desktops, network devices, and other embedded systems) can be easily upgraded using a flash or capsule mechanism which can add new vulnerabilities either through malicious code, or by accidental incidents, and deliberate attack. The recent attack on Iranian Nuclear Power Plant (Stuxnet) [1:2] is an example of advanced persistent attack. This attack vector adds a new dimension into the information security (IS) spectrum, which needs to be guarded by implementing a holistic approach employed at enterprise level. Malicious BIOS upgrades can also cause denial of service, stealing of information or addition of new backdoors which can be exploited by attackers for causing business loss, passive eaves dropping or total destruction of system without knowledge of user. To address this challenge a capability for verification of BIOS integrity needs to be developed and due diligence must be observed for proactive resolution of the issue. This paper explains the BIOS Integrity threats and presents a prevention strategy for effective and proactive resolution.

Buthelezi, M. P., Poll, J. A. van der, Ochola, E. O..  2016.  Ambiguity as a Barrier to Information Security Policy Compliance: A Content Analysis. 2016 International Conference on Computational Science and Computational Intelligence (CSCI). :1360–1367.

Institutions use the information security (InfoSec) policy document as a set of rules and guidelines to govern the use of the institutional information resources. However, a common problem is that these policies are often not followed or complied with. This study explores the extent to which the problem lies with the policy documents themselves. The InfoSec policies are documented in the natural languages, which are prone to ambiguity and misinterpretation. Subsequently such policies may be ambiguous, thereby making it hard, if not impossible for users to comply with. A case study approach with a content analysis was conducted. The research explores the extent of the problem by using a case study of an educational institution in South Africa.

Busygin, Alexey, Konoplev, Artem, Kalinin, Maxim, Zegzhda, Dmitry.  2018.  Floating Genesis Block Enhancement for Blockchain Based Routing Between Connected Vehicles and Software-defined VANET Security Services. Proceedings of the 11th International Conference on Security of Information and Networks. :24:1–24:2.
The paper reviews the issue of secure routing in unmanned vehicle ad-hoc networks. Application of the Blockchain technology for routing and authentication information storage and distribution is proposed. A blockchain with the floating genesis block is introduced to solve problems associated with blockchain size growth in the systems using transactions with limited lifetime.
Bushouse, Micah, Ahn, Sanghyun, Reeves, Douglas.  2017.  Arav: Monitoring a Cloud's Virtual Routers. Proceedings of the 12th Annual Conference on Cyber and Information Security Research. :3:1–3:8.

Virtual Routers (VRs) are increasingly common in cloud environments. VRs route traffic between network segments and support network services. Routers, including VRs, have been the target of several recent high-profile attacks, emphasizing the need for more security measures, including security monitoring. However, existing agent-based monitoring systems are incompatible with a VR's temporary nature, stripped-down operating system, and placement in the cloud. As a result, VRs are often not monitored, leading to undetected security incidents. This paper proposes a new security monitoring design that leverages virtualization instead of in-guest agents. Its hypervisor-based system, Arav, scrutinizes VRs by novel application of Virtual Machine Introspection (VMI) breakpoint injection. Arav monitored and addressed security-related events in two common VRs, pfSense and VyOS, and detected four attacks against two popular VR services, Quagga and OpenVPN. Arav's performance overhead is negligible, less than 0.63%, demonstrating VMI's utility in monitoring virtual machines unsuitable for traditional security monitoring.

Bushouse, Micah, Reeves, Douglas.  2018.  Hyperagents: Migrating Host Agents to the Hypervisor. Proceedings of the Eighth ACM Conference on Data and Application Security and Privacy. :212–223.

Third-party software daemons called host agents are increasingly responsible for a modern host's security, automation, and monitoring tasks. Because of their location within the host, these agents are at risk of manipulation by malware and users. Additionally, in virtualized environments where multiple adjacent guests each run their own set of agents, the cumulative resources that agents consume adds up rapidly. Consolidating agents onto the hypervisor can address these problems, but places a technical burden on agent developers. This work presents a development methodology to re-engineer a host agent in to a hyperagent, an out-of-guest agent that gains unique hypervisor-based advantages while retaining its original in-guest capabilities. This three-phase methodology makes integrating Virtual Machine Introspection (VMI) functionality in to existing code easier and more accessible, minimizing an agent developer's re-engineering effort. The benefits of hyperagents are illustrated by porting the GRR live forensics agent, which retains 89% of its codebase, uses 40% less memory than its in-guest counterparts, and enables a 4.9x speedup for a representative data-intensive workload. This work shows that a conventional off-the-shelf host agent can be feasibly transformed into a hyperagent and provide a powerful, efficient tool for defending virtualized systems.

Bushnag, Anas, Abuzneid, Abdelshakour, Mahmood, Ausif.  2017.  An Efficient Source Anonymity Technique Based on Exponential Distribution Against a Global Adversary Model Using Fake Injections. Proceedings of the 13th ACM Symposium on QoS and Security for Wireless and Mobile Networks. :15–21.

The security of Wireless Sensor Networks (WSNs) is vital in several applications such as the tracking and monitoring of endangered species such as pandas in a national park or soldiers in a battlefield. This kind of applications requires the anonymity of the source, known as Source Location Privacy (SLP). The main aim is to prevent an adversary from tracing back a real event to the originator by analyzing the network traffic. Previous techniques have achieved high anonymity such as Dummy Uniform Distribution (DUD), Dummy Adaptive Distribution (DAD) and Controlled Dummy Adaptive Distribution (CAD). However, these techniques increase the overall overhead of the network. To overcome this shortcoming, a new technique is presented: Exponential Dummy Adaptive Distribution (EDAD). In this technique, an exponential distribution is used instead of the uniform distribution to reduce the overhead without sacrificing the anonymity of the source. The exponential distribution improves the lifetime of the network since it decreases the number of transmitted packets within the network. It is straightforward and easy to implement because it has only one parameter $łambda$ that controls the transmitting rate of the network nodes. The conducted adversary model is global, which has a full view of the network and is able to perform sophisticated attacks such as rate monitoring and time correlation. The simulation results show that the proposed technique provides less overhead and high anonymity with reasonable delay and delivery ratio. Three different analysis models are developed to confirm the validation of our technique. These models are visualization model, a neural network model, and a steganography model.

Bursztein, E., Bethard, S., Fabry, C., Mitchell, J.C., Jurafsky, D..  2010.  How Good Are Humans at Solving CAPTCHAs? A Large Scale Evaluation Security and Privacy (SP), 2010 IEEE Symposium on. :399-413.

Captchas are designed to be easy for humans but hard for machines. However, most recent research has focused only on making them hard for machines. In this paper, we present what is to the best of our knowledge the first large scale evaluation of captchas from the human perspective, with the goal of assessing how much friction captchas present to the average user. For the purpose of this study we have asked workers from Amazon’s Mechanical Turk and an underground captchabreaking service to solve more than 318 000 captchas issued from the 21 most popular captcha schemes (13 images schemes and 8 audio scheme). Analysis of the resulting data reveals that captchas are often difficult for humans, with audio captchas being particularly problematic. We also find some demographic trends indicating, for example, that non-native speakers of English are slower in general and less accurate on English-centric captcha schemes. Evidence from a week’s worth of eBay captchas (14,000,000 samples) suggests that the solving accuracies found in our study are close to real-world values, and that improving audio captchas should become a priority, as nearly 1% of all captchas are delivered as audio rather than images. Finally our study also reveals that it is more effective for an attacker to use Mechanical Turk to solve captchas than an underground service.

Burr, B., Wang, S., Salmon, G., Soliman, H..  2020.  On the Detection of Persistent Attacks using Alert Graphs and Event Feature Embeddings. NOMS 2020 - 2020 IEEE/IFIP Network Operations and Management Symposium. :1—4.
Intrusion Detection Systems (IDS) generate a high volume of alerts that security analysts do not have the resources to explore fully. Modelling attacks, especially the coordinated campaigns of Advanced Persistent Threats (APTs), in a visually-interpretable way is a useful approach for network security. Graph models combine multiple alerts and are well suited for visualization and interpretation, increasing security effectiveness. In this paper, we use feature embeddings, learned from network event logs, and community detection to construct and segment alert graphs of related alerts and networks hosts. We posit that such graphs can aid security analysts in investigating alerts and may capture multiple aspects of an APT attack. The eventual goal of this approach is to construct interpretable attack graphs and extract causality information to identify coordinated attacks.
Burow, Nathan, Zhang, Xinping, Payer, Mathias.  2019.  SoK: Shining Light on Shadow Stacks. 2019 IEEE Symposium on Security and Privacy (SP). :985–999.

Control-Flow Hijacking attacks are the dominant attack vector against C/C++ programs. Control-Flow Integrity (CFI) solutions mitigate these attacks on the forward edge, i.e., indirect calls through function pointers and virtual calls. Protecting the backward edge is left to stack canaries, which are easily bypassed through information leaks. Shadow Stacks are a fully precise mechanism for protecting backwards edges, and should be deployed with CFI mitigations. We present a comprehensive analysis of all possible shadow stack mechanisms along three axes: performance, compatibility, and security. For performance comparisons we use SPEC CPU2006, while security and compatibility are qualitatively analyzed. Based on our study, we renew calls for a shadow stack design that leverages a dedicated register, resulting in low performance overhead, and minimal memory overhead, but sacrifices compatibility. We present case studies of our implementation of such a design, Shadesmar, on Phoronix and Apache to demonstrate the feasibility of dedicating a general purpose register to a security monitor on modern architectures, and Shadesmar's deployability. Our comprehensive analysis, including detailed case studies for our novel design, allows compiler designers and practitioners to select the correct shadow stack design for different usage scenarios. Shadow stacks belong to the class of defense mechanisms that require metadata about the program's state to enforce their defense policies. Protecting this metadata for deployed mitigations requires in-process isolation of a segment of the virtual address space. Prior work on defenses in this class has relied on information hiding to protect metadata. We show that stronger guarantees are possible by repurposing two new Intel x86 extensions for memory protection (MPX), and page table control (MPK). Building on our isolation efforts with MPX and MPK, we present the design requirements for a dedicated hardware mechanism to support intra-process memory isolation, and discuss how such a mechanism can empower the next wave of highly precise software security mitigations that rely on partially isolated information in a process.

Burow, Nathan, Carr, Scott A., Nash, Joseph, Larsen, Per, Franz, Michael, Brunthaler, Stefan, Payer, Mathias.  2017.  Control-Flow Integrity: Precision, Security, and Performance. ACM Comput. Surv.. 50:16:1–16:33.
Memory corruption errors in C/C++ programs remain the most common source of security vulnerabilities in today’s systems. Control-flow hijacking attacks exploit memory corruption vulnerabilities to divert program execution away from the intended control flow. Researchers have spent more than a decade studying and refining defenses based on Control-Flow Integrity (CFI); this technique is now integrated into several production compilers. However, so far, no study has systematically compared the various proposed CFI mechanisms nor is there any protocol on how to compare such mechanisms. We compare a broad range of CFI mechanisms using a unified nomenclature based on (i) a qualitative discussion of the conceptual security guarantees, (ii) a quantitative security evaluation, and (iii) an empirical evaluation of their performance in the same test environment. For each mechanism, we evaluate (i) protected types of control-flow transfers and (ii) precision of the protection for forward and backward edges. For open-source, compiler-based implementations, we also evaluate (iii) generated equivalence classes and target sets and (iv) runtime performance.
Burnap, P., Javed, A., Rana, O. F., Awan, M. S..  2015.  Real-time classification of malicious URLs on Twitter using machine activity data. 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM). :970–977.

Massive online social networks with hundreds of millions of active users are increasingly being used by Cyber criminals to spread malicious software (malware) to exploit vulnerabilities on the machines of users for personal gain. Twitter is particularly susceptible to such activity as, with its 140 character limit, it is common for people to include URLs in their tweets to link to more detailed information, evidence, news reports and so on. URLs are often shortened so the endpoint is not obvious before a person clicks the link. Cyber criminals can exploit this to propagate malicious URLs on Twitter, for which the endpoint is a malicious server that performs unwanted actions on the person's machine. This is known as a drive-by-download. In this paper we develop a machine classification system to distinguish between malicious and benign URLs within seconds of the URL being clicked (i.e. `real-time'). We train the classifier using machine activity logs created while interacting with URLs extracted from Twitter data collected during a large global event - the Superbowl - and test it using data from another large sporting event - the Cricket World Cup. The results show that machine activity logs produce precision performances of up to 0.975 on training data from the first event and 0.747 on a test data from a second event. Furthermore, we examine the properties of the learned model to explain the relationship between machine activity and malicious software behaviour, and build a learning curve for the classifier to illustrate that very small samples of training data can be used with only a small detriment to performance.

Burmester, Mike, Munilla, Jorge.  2011.  Lightweight RFID Authentication with Forward and Backward Security. ACM Trans. Inf. Syst. Secur.. 14:11:1–11:26.

We propose a lightweight RFID authentication protocol that supports forward and backward security. The only cryptographic mechanism that this protocol uses is a pseudorandom number generator (PRNG) that is shared with the backend Server. Authentication is achieved by exchanging a few numbers (3 or 5) drawn from the PRNG. The lookup time is constant, and the protocol can be easily adapted to prevent online man-in-the-middle relay attacks. Security is proven in the UC security framework.

Burley, Diana L., Eisenberg, Jon, Goodman, Seymour E..  2014.  Would Cybersecurity Professionalization Help Address the Cybersecurity Crisis? Commun. ACM. 57:24–27.

Evaluating the trade-offs involved in cybersecurity professionalization.

Burley, Diana, Bishop, Matt, Hawthorne, Elizabeth, Kaza, Siddharth, Buck, Scott, Futcher, Lynn.  2016.  Special Session: ACM Joint Task Force on Cyber Education. Proceedings of the 47th ACM Technical Symposium on Computing Science Education. :234–235.

In this special session, members of the ACM Joint Task Force on Cyber Education to Develop Undergraduate Curricular Guidance will provide an overview of the task force mission, objectives, and work plan. After the overview, task force members will engage session participants in the curricular development process.