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Abdelhakim, Boudhir Anouar, Mohamed, Ben Ahmed, Mohammed, Bouhorma, Ikram, Ben Abdel Ouahab.  2018.  New Security Approach for IoT Communication Systems. Proceedings of the 3rd International Conference on Smart City Applications. :2:1–2:8.

The Security is a real permanent problem in wired and wireless communication systems. This issue becomes more and more complex in the internet of things context where the security solution still poor and insufficient where the number of these noeud hugely increase (around 26 milliards in 2020). In this paper we propose a new security schema which avoid the use of cryptography mechanism based on the exchange of symmetric or asymmetric keys which aren't recommended in IoT devices due to their limitation in processing, stockage and energy. The proposed solution is based on the use of the multi-agent ensuring the security of connected objects. These objects programmed with agents are able to communicate with other objects without any need to compute keys. The main objective in this work is to maintain a high level of security with an optimization of the energy consumption of IoT devices.

Abdelhamid, N., Thabtah, F., Abdel-jaber, H..  2017.  Phishing detection: A recent intelligent machine learning comparison based on models content and features. 2017 IEEE International Conference on Intelligence and Security Informatics (ISI). :72–77.

In the last decade, numerous fake websites have been developed on the World Wide Web to mimic trusted websites, with the aim of stealing financial assets from users and organizations. This form of online attack is called phishing, and it has cost the online community and the various stakeholders hundreds of million Dollars. Therefore, effective counter measures that can accurately detect phishing are needed. Machine learning (ML) is a popular tool for data analysis and recently has shown promising results in combating phishing when contrasted with classic anti-phishing approaches, including awareness workshops, visualization and legal solutions. This article investigates ML techniques applicability to detect phishing attacks and describes their pros and cons. In particular, different types of ML techniques have been investigated to reveal the suitable options that can serve as anti-phishing tools. More importantly, we experimentally compare large numbers of ML techniques on real phishing datasets and with respect to different metrics. The purpose of the comparison is to reveal the advantages and disadvantages of ML predictive models and to show their actual performance when it comes to phishing attacks. The experimental results show that Covering approach models are more appropriate as anti-phishing solutions, especially for novice users, because of their simple yet effective knowledge bases in addition to their good phishing detection rate.

Abdelzaher, T., Ayanian, N., Basar, T., Diggavi, S., Diesner, J., Ganesan, D., Govindan, R., Jha, S., Lepoint, T., Marlin, B. et al..  2018.  Toward an Internet of Battlefield Things: A Resilience Perspective. Computer. 51:24—36.

The Internet of Battlefield Things (IoBT) might be one of the most expensive cyber-physical systems of the next decade, yet much research remains to develop its fundamental enablers. A challenge that distinguishes the IoBT from its civilian counterparts is resilience to a much larger spectrum of threats.

Abedin, Zain Ul, Guan, Zhitao, Arif, Asad Ullah, Anwar, Usman.  2019.  An Advance Cryptographic Solutions in Cloud Computing Security. 2019 2nd International Conference on Computing, Mathematics and Engineering Technologies (iCoMET). :1–6.

Cryptographically cloud computing may be an innovative safe cloud computing design. Cloud computing may be a huge size dispersed computing model that ambitious by the economy of the level. It integrates a group of inattentive virtualized animatedly scalable and managed possessions like computing control storage space platform and services. External end users will approach to resources over the net victimization fatal particularly mobile terminals, Cloud's architecture structures are advances in on-demand new trends. That are the belongings are animatedly assigned to a user per his request and hand over when the task is finished. So, this paper projected biometric coding to boost the confidentiality in Cloud computing for biometric knowledge. Also, this paper mentioned virtualization for Cloud computing also as statistics coding. Indeed, this paper overviewed the safety weaknesses of Cloud computing and the way biometric coding will improve the confidentiality in Cloud computing atmosphere. Excluding this confidentiality is increased in Cloud computing by victimization biometric coding for biometric knowledge. The novel approach of biometric coding is to reinforce the biometric knowledge confidentiality in Cloud computing. Implementation of identification mechanism can take the security of information and access management in the cloud to a higher level. This section discusses, however, a projected statistics system with relation to alternative recognition systems to date is a lot of advantageous and result oriented as a result of it does not work on presumptions: it's distinctive and provides quick and contact less authentication. Thus, this paper reviews the new discipline techniques accustomed to defend methodology encrypted info in passing remote cloud storage.

Abeykoon, I., Feng, X..  2019.  Challenges in ROS Forensics. 2019 IEEE SmartWorld, Ubiquitous Intelligence Computing, Advanced Trusted Computing, Scalable Computing Communications, Cloud Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI). :1677—1682.

The usage of robot is rapidly growth in our society. The communication link and applications connect the robots to their clients or users. This communication link and applications are normally connected through some kind of network connections. This network system is amenable of being attached and vulnerable to the security threats. It is a critical part for ensuring security and privacy for robotic platforms. The paper, also discusses about several cyber-physical security threats that are only for robotic platforms. The peer to peer applications use in the robotic platforms for threats target integrity, availability and confidential security purposes. A Remote Administration Tool (RAT) was introduced for specific security attacks. An impact oriented process was performed for analyzing the assessment outcomes of the attacks. Tests and experiments of attacks were performed in simulation environment which was based on Gazbo Turtlebot simulator and physically on the robot. A software tool was used for simulating, debugging and experimenting on ROS platform. Integrity attacks performed for modifying commands and manipulated the robot behavior. Availability attacks were affected for Denial-of-Service (DoS) and the robot was not listened to Turtlebot commands. Integrity and availability attacks resulted sensitive information on the robot.

Abeysekara, P., Dong, H., Qin, A. K..  2019.  Machine Learning-Driven Trust Prediction for MEC-Based IoT Services. 2019 IEEE International Conference on Web Services (ICWS). :188—192.

We propose a distributed machine-learning architecture to predict trustworthiness of sensor services in Mobile Edge Computing (MEC) based Internet of Things (IoT) services, which aligns well with the goals of MEC and requirements of modern IoT systems. The proposed machine-learning architecture models training a distributed trust prediction model over a topology of MEC-environments as a Network Lasso problem, which allows simultaneous clustering and optimization on large-scale networked-graphs. We then attempt to solve it using Alternate Direction Method of Multipliers (ADMM) in a way that makes it suitable for MEC-based IoT systems. We present analytical and simulation results to show the validity and efficiency of the proposed solution.

Abidin, Aysajan, Argones Rúa, Enrique, Peeters, Roel.  2017.  Uncoupling Biometrics from Templates for Secure and Privacy-Preserving Authentication. Proceedings of the 22Nd ACM on Symposium on Access Control Models and Technologies. :21–29.

Biometrics are widely used for authentication in several domains, services and applications. However, only very few systems succeed in effectively combining highly secure user authentication with an adequate privacy protection of the biometric templates, due to the difficulty associated with jointly providing good authentication performance, unlinkability and irreversibility to biometric templates. This thwarts the use of biometrics in remote authentication scenarios, despite the advantages that this kind of architectures provides. We propose a user-specific approach for decoupling the biometrics from their binary representation before using biometric protection schemes based on fuzzy extractors. This allows for more reliable, flexible, irreversible and unlinkable protected biometric templates. With the proposed biometrics decoupling procedures, biometric metadata, that does not allow to recover the original biometric template, is generated. However, different biometric metadata that are generated starting from the same biometric template remain statistically linkable, therefore we propose to additionally protect these using a second authentication factor (e.g., knowledge or possession based). We demonstrate the potential of this approach within a two-factor authentication protocol for remote biometric authentication in mobile scenarios.

Abie, Habtamu.  2019.  Cognitive Cybersecurity for CPS-IoT Enabled Healthcare Ecosystems. 2019 13th International Symposium on Medical Information and Communication Technology (ISMICT). :1–6.

Cyber Physical Systems (CPS)-Internet of Things (IoT) enabled healthcare services and infrastructures improve human life, but are vulnerable to a variety of emerging cyber-attacks. Cybersecurity specialists are finding it hard to keep pace of the increasingly sophisticated attack methods. There is a critical need for innovative cognitive cybersecurity for CPS-IoT enabled healthcare ecosystem. This paper presents a cognitive cybersecurity framework for simulating the human cognitive behaviour to anticipate and respond to new and emerging cybersecurity and privacy threats to CPS-IoT and critical infrastructure systems. It includes the conceptualisation and description of a layered architecture which combines Artificial Intelligence, cognitive methods and innovative security mechanisms.

Abou-Zahra, Shadi, Brewer, Judy, Cooper, Michael.  2018.  Artificial Intelligence (AI) for Web Accessibility: Is Conformance Evaluation a Way Forward? Proceedings of the Internet of Accessible Things. :20:1–20:4.

The term "artificial intelligence" is a buzzword today and is heavily used to market products, services, research, conferences, and more. It is scientifically disputed which types of products and services do actually qualify as "artificial intelligence" versus simply advanced computer technologies mimicking aspects of natural intelligence. Yet it is undisputed that, despite often inflationary use of the term, there are mainstream products and services today that for decades were only thought to be science fiction. They range from industrial automation, to self-driving cars, robotics, and consumer electronics for smart homes, workspaces, education, and many more contexts. Several technological advances enable what is commonly referred to as "artificial intelligence". It includes connected computers and the Internet of Things (IoT), open and big data, low cost computing and storage, and many more. Yet regardless of the definition of the term artificial intelligence, technological advancements in this area provide immense potential, especially for people with disabilities. In this paper we explore some of these potential in the context of web accessibility. We review some existing products and services, and their support for web accessibility. We propose accessibility conformance evaluation as one potential way forward, to accelerate the uptake of artificial intelligence, to improve web accessibility.

Abusitta, Adel, Bellaiche, Martine, Dagenais, Michel.  2018.  A trust-based game theoretical model for cooperative intrusion detection in multi-cloud environments. 2018 21st Conference on Innovation in Clouds, Internet and Networks and Workshops (ICIN). :1—8.

Cloud systems are becoming more complex and vulnerable to attacks. Cyber attacks are also becoming more sophisticated and harder to detect. Therefore, it is increasingly difficult for a single cloud-based intrusion detection system (IDS) to detect all attacks, because of limited and incomplete knowledge about attacks. The recent researches in cyber-security have shown that a co-operation among IDSs can bring higher detection accuracy in such complex computer systems. Through collaboration, a cloud-based IDS can consult other IDSs about suspicious intrusions and increase the decision accuracy. The problem of existing cooperative IDS approaches is that they overlook having untrusted (malicious or not) IDSs that may negatively effect the decision about suspicious intrusions in the cloud. Moreover, they rely on a centralized architecture in which a central agent regulates the cooperation, which contradicts the distributed nature of the cloud. In this paper, we propose a framework that enables IDSs to distributively form trustworthy IDSs communities. We devise a novel decentralized algorithm, based on coalitional game theory, that allows a set of cloud-based IDSs to cooperatively set up their coalition in such a way to make their individual detection accuracy increase, even in the presence of untrusted IDSs.

Abuzainab, N., Saad, W..  2018.  A Multiclass Mean-Field Game for Thwarting Misinformation Spread in the Internet of Battlefield Things (IoBT). IEEE Transactions on Communications. :1–1.

In this paper, the problem of misinformation propagation is studied for an Internet of Battlefield Things (IoBT) system in which an attacker seeks to inject false information in the IoBT nodes in order to compromise the IoBT operations. In the considered model, each IoBT node seeks to counter the misinformation attack by finding the optimal probability of accepting a given information that minimizes its cost at each time instant. The cost is expressed in terms of the quality of information received as well as the infection cost. The problem is formulated as a mean-field game with multiclass agents which is suitable to model a massive heterogeneous IoBT system. For this game, the mean-field equilibrium is characterized, and an algorithm based on the forward backward sweep method is proposed to find the mean-field equilibrium. Then, the finite IoBT case is considered, and the conditions of convergence of the equilibria in the finite case to the mean-field equilibrium are presented. Numerical results show that the proposed scheme can achieve a 1.2-fold increase in the quality of information (QoI) compared to a baseline scheme in which the IoBT nodes are always transmitting. The results also show that the proposed scheme can reduce the proportion of infected nodes by 99% compared to the baseline.

Abuzainab, N., Saad, W..  2018.  Dynamic Connectivity Game for Adversarial Internet of Battlefield Things Systems. IEEE Internet of Things Journal. 5:378–390.

In this paper, the problem of network connectivity is studied for an adversarial Internet of Battlefield Things (IoBT) system in which an attacker aims at disrupting the connectivity of the network by choosing to compromise one of the IoBT nodes at each time epoch. To counter such attacks, an IoBT defender attempts to reestablish the IoBT connectivity by either deploying new IoBT nodes or by changing the roles of existing nodes. This problem is formulated as a dynamic multistage Stackelberg connectivity game that extends classical connectivity games and that explicitly takes into account the characteristics and requirements of the IoBT network. In particular, the defender's payoff captures the IoBT latency as well as the sum of weights of disconnected nodes at each stage of the game. Due to the dependence of the attacker's and defender's actions at each stage of the game on the network state, the feedback Stackelberg solution [feedback Stackelberg equilibrium (FSE)] is used to solve the IoBT connectivity game. Then, sufficient conditions under which the IoBT system will remain connected, when the FSE solution is used, are determined analytically. Numerical results show that the expected number of disconnected sensors, when the FSE solution is used, decreases up to 46% compared to a baseline scenario in which a Stackelberg game with no feedback is used, and up to 43% compared to a baseline equal probability policy.

Abuzainab, N., Saad, W..  2018.  Misinformation Control in the Internet of Battlefield Things: A Multiclass Mean-Field Game. 2018 IEEE Global Communications Conference (GLOBECOM). :1—7.

In this paper, the problem of misinformation propagation is studied for an Internet of Battlefield Things (IoBT) system in which an attacker seeks to inject false information in the IoBT nodes in order to compromise the IoBT operations. In the considered model, each IoBT node seeks to counter the misinformation attack by finding the optimal probability of accepting a given information that minimizes its cost at each time instant. The cost is expressed in terms of the quality of information received as well as the infection cost. The problem is formulated as a mean-field game with multiclass agents which is suitable to model a massive heterogeneous IoBT system. For this game, the mean-field equilibrium is characterized, and an algorithm based on the forward backward sweep method is proposed. Then, the finite IoBT case is considered, and the conditions of convergence of the equilibria in the finite case to the mean-field equilibrium are presented. Numerical results show that the proposed scheme can achieve a two-fold increase in the quality of information (QoI) compared to the baseline when the nodes are always transmitting.

Abuzainab, N., Saad, W..  2018.  A Multiclass Mean-Field Game for Thwarting Misinformation Spread in the Internet of Battlefield Things. IEEE Transactions on Communications. 66:6643—6658.

In this paper, the problem of misinformation propagation is studied for an Internet of Battlefield Things (IoBT) system, in which an attacker seeks to inject false information in the IoBT nodes in order to compromise the IoBT operations. In the considered model, each IoBT node seeks to counter the misinformation attack by finding the optimal probability of accepting given information that minimizes its cost at each time instant. The cost is expressed in terms of the quality of information received as well as the infection cost. The problem is formulated as a mean-field game with multiclass agents, which is suitable to model a massive heterogeneous IoBT system. For this game, the mean-field equilibrium is characterized, and an algorithm based on the forward backward sweep method is proposed to find the mean-field equilibrium. Then, the finite-IoBT case is considered, and the conditions of convergence of the equilibria in the finite case to the mean-field equilibrium are presented. Numerical results show that the proposed scheme can achieve a 1.2-fold increase in the quality of information compared with a baseline scheme, in which the IoBT nodes are always transmitting. The results also show that the proposed scheme can reduce the proportion of infected nodes by 99% compared with the baseline.

Acharjamayum, Irani, Patgiri, Ripon, Devi, Dhruwajita.  2018.  Blockchain: A Tale of Peer to Peer Security. 2018 IEEE Symposium Series on Computational Intelligence (SSCI). :609-617.

The underlying or core technology of Bitcoin cryptocurrency has become a blessing for human being in this era. Everything is gradually changing to digitization in this today's epoch. Bitcoin creates virtual money using Blockchain that's become popular over the world. Blockchain is a shared public ledger, and it includes all transactions which are confirmed. It is almost impossible to crack the hidden information in the blocks of the Blockchain. However, there are certain security and technical challenges like scalability, privacy leakage, selfish mining, etc. which hampers the wide application of Blockchain. In this paper, we briefly discuss this emerging technology namely Blockchain. In addition, we extrapolate in-depth insight on Blockchain technology.

Adams, M., Bhargava, V. K..  2017.  Using friendly jamming to improve route security and quality in ad hoc networks. 2017 IEEE 30th Canadian Conference on Electrical and Computer Engineering (CCECE). :1–6.

Friendly jamming is a physical layer security technique that utilizes extra available nodes to jam any eavesdroppers. This paper considers the use of additional available nodes as friendly jammers in order to improve the security performance of a route through a wireless area network. One of the unresolved technical challenges is the combining of security metrics with typical service quality metrics. In this context, this paper considers the problem of routing through a D2D network while jointly minimizing the secrecy outage probability (SOP) and connection outage probability (COP), using friendly jamming to improve the SOP of each link. The jamming powers are determined to place nulls at friendly receivers while maximizing the power to eavesdroppers. Then the route metrics are derived, and the problem is framed as a convex optimization problem. We also consider that not all network users equally value SOP and COP, and so introduce an auxiliary variable to tune the optimization between the two metrics.

Adams, S., Carter, B., Fleming, C., Beling, P. A..  2018.  Selecting System Specific Cybersecurity Attack Patterns Using Topic Modeling. 2018 17th IEEE International Conference On Trust, Security And Privacy In Computing And Communications/ 12th IEEE International Conference On Big Data Science And Engineering (TrustCom/BigDataSE). :490–497.

One challenge for cybersecurity experts is deciding which type of attack would be successful against the system they wish to protect. Often, this challenge is addressed in an ad hoc fashion and is highly dependent upon the skill and knowledge base of the expert. In this study, we present a method for automatically ranking attack patterns in the Common Attack Pattern Enumeration and Classification (CAPEC) database for a given system. This ranking method is intended to produce suggested attacks to be evaluated by a cybersecurity expert and not a definitive ranking of the "best" attacks. The proposed method uses topic modeling to extract hidden topics from the textual description of each attack pattern and learn the parameters of a topic model. The posterior distribution of topics for the system is estimated using the model and any provided text. Attack patterns are ranked by measuring the distance between each attack topic distribution and the topic distribution of the system using KL divergence.

Adetunji, Akinbobola Oluwaseun, Butakov, Sergey, Zavarsky, Pavol.  2018.  Automated Security Configuration Checklist for Apple iOS Devices Using SCAP v1.2. 2018 International Conference on Platform Technology and Service (PlatCon). :1–6.
The security content automation includes configurations of large number of systems, installation of patches securely, verification of security-related configuration settings, compliance with security policies and regulatory requirements, and ability to respond quickly when new threats are discovered [1]. Although humans are important in information security management, humans sometimes introduce errors and inconsistencies in an organization due to manual nature of their tasks [2]. Security Content Automation Protocol was developed by the U.S. NIST to automate information security management tasks such as vulnerability and patch management, and to achieve continuous monitoring of security configurations in an organization. In this paper, SCAP is employed to develop an automated security configuration checklist for use in verifying Apple iOS device configuration against the defined security baseline to enforce policy compliance in an enterprise.
Adeyemi, I. R., Razak, S. A., Venter, H. S., Salleh, M..  2017.  High-Level Online User Attribution Model Based on Human Polychronic-Monochronic Tendency. 2017 IEEE International Conference on Big Data and Smart Computing (BigComp). :445–450.

User attribution process based on human inherent dynamics and preference is one area of research that is capable of elucidating and capturing human dynamics on the Internet. Prior works on user attribution concentrated on behavioral biometrics, 1-to-1 user identification process without consideration for individual preference and human inherent temporal tendencies, which is capable of providing a discriminatory baseline for online users, as well as providing a higher level classification framework for novel user attribution. To address these limitations, the study developed a temporal model, which comprises the human Polyphasia tendency based on Polychronic-Monochronic tendency scale measurement instrument and the extraction of unique human-centric features from server-side network traffic of 48 active users. Several machine-learning algorithms were applied to observe distinct pattern among the classes of the Polyphasia tendency, through which a logistic model tree was observed to provide higher classification accuracy for a 1-to-N user attribution process. The study further developed a high-level attribution model for higher-level user attribution process. The result from this study is relevant in online profiling process, forensic identification and profiling process, e-learning profiling process as well as in social network profiling process.

Adhatarao, S. S., Arumaithurai, M., Fu, X..  2017.  FOGG: A Fog Computing Based Gateway to Integrate Sensor Networks to Internet. 2017 29th International Teletraffic Congress (ITC 29). 2:42–47.
Internet of Things (IoT) is a growing topic of interest along with 5G. Billions of IoT devices are expected to connect to the Internet in the near future. These devices differ from the traditional devices operated in the Internet. We observe that Information Centric Networking (ICN), is a more suitable architecture for the IoT compared to the prevailing IP basednetwork. However, we observe that recent works that propose to use ICN for IoT, either do not cover the need to integrate Sensor Networks with the Internet to realize IoT or do so inefficiently. Fog computing is a promising technology that has many benefits to offer especially for IoT. In this work, we discover a need to integrate various heterogeneous Sensor Networks with the Internet to realize IoT and propose FOGG: A Fog Computing Based Gateway to Integrate Sensor Networks to Internet. FOGG uses a dedicated device to function as an IoT gateway. FOGG provides the needed integration along with additional services like name/protocol translation, security and controller functionalities.
Adil, M., Khan, R., Ghani, M. A. Nawaz Ul.  2020.  Preventive Techniques of Phishing Attacks in Networks. 2020 3rd International Conference on Advancements in Computational Sciences (ICACS). :1—8.

Internet is the most widely used technology in the current era of information technology and it is embedded in daily life activities. Due to its extensive use in everyday life, it has many applications such as social media (Face book, WhatsApp, messenger etc.,) and other online applications such as online businesses, e-counseling, advertisement on websites, e-banking, e-hunting websites, e-doctor appointment and e-doctor opinion. The above mentioned applications of internet technology makes things very easy and accessible for human being in limited time, however, this technology is vulnerable to various security threats. A vital and severe threat associated with this technology or a particular application is “Phishing attack” which is used by attacker to usurp the network security. Phishing attacks includes fake E-mails, fake websites, fake applications which are used to steal their credentials or usurp their security. In this paper, a detailed overview of various phishing attacks, specifically their background knowledge, and solutions proposed in literature to address these issues using various techniques such as anti-phishing, honey pots and firewalls etc. Moreover, installation of intrusion detection systems (IDS) and intrusion detection and prevention system (IPS) in the networks to allow the authentic traffic in an operational network. In this work, we have conducted end use awareness campaign to educate and train the employs in order to minimize the occurrence probability of these attacks. The result analysis observed for this survey was quite excellent by means of its effectiveness to address the aforementioned issues.

Afanasev, M. Y., Krylova, A. A., Shorokhov, S. A., Fedosov, Y. V., Sidorenko, A. S..  2018.  A Design of Cyber-Physical Production System Prototype Based on an Ethereum Private Network. 2018 22nd Conference of Open Innovations Association (FRUCT). :3–11.

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

Afrin, S., Mishra, S..  2017.  On the Analysis of Collaborative Anonymity Set Formation (CASF) Method for Privacy in the Smart Grid. 2017 IEEE International Symposium on Technologies for Homeland Security (HST). :1–6.

The collection of high frequency metering data in the emerging smart grid gives rise to the concern of consumer privacy. Anonymization of metering data is one of the proposed approaches in the literature, which enables transmission of unmasked data while preserving the privacy of the sender. Distributed anonymization methods can reduce the dependency on service providers, thus promising more privacy for the consumers. However, the distributed communication among the end-users introduces overhead and requires methods to prevent external attacks. In this paper, we propose four variants of a distributed anonymization method for smart metering data privacy, referred to as the Collaborative Anonymity Set Formation (CASF) method. The performance overhead analysis and security analysis of the variants are done using NS-3 simulator and the Scyther tool, respectively. It is shown that the proposed scheme enhances the privacy preservation functionality of an existing anonymization scheme, while being robust against external attacks.

Agadakos, I., Ciocarlie, G. F., Copos, B., George, J., Leslie, N., Michaelis, J..  2019.  Security for Resilient IoBT Systems: Emerging Research Directions. IEEE INFOCOM 2019 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS). :1—6.

Continued advances in IoT technology have prompted new investigation into its usage for military operations, both to augment and complement existing military sensing assets and support next-generation artificial intelligence and machine learning systems. Under the emerging Internet of Battlefield Things (IoBT) paradigm, a multitude of operational conditions (e.g., diverse asset ownership, degraded networking infrastructure, adversary activities) necessitate the development of novel security techniques, centered on establishment of trust for individual assets and supporting resilience of broader systems. To advance current IoBT efforts, a set of research directions are proposed that aim to fundamentally address the issues of trust and trustworthiness in contested battlefield environments, building on prior research in the cybersecurity domain. These research directions focus on two themes: (1) Supporting trust assessment for known/unknown IoT assets; (2) Ensuring continued trust of known IoBT assets and systems.

Agadakos, I., Ciocarlie, G. F., Copos, B., Emmi, M., George, J., Leslie, N., Michaelis, J..  2019.  Application of Trust Assessment Techniques to IoBT Systems. MILCOM 2019 - 2019 IEEE Military Communications Conference (MILCOM). :833—840.

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