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2020-05-18
Thejaswini, S, Indupriya, C.  2019.  Big Data Security Issues and Natural Language Processing. 2019 3rd International Conference on Trends in Electronics and Informatics (ICOEI). :1307–1312.
Whenever we talk about big data, the concern is always about the security of the data. In recent days the most heard about technology is the Natural Language Processing. This new and trending technology helps in solving the ever ending security problems which are not completely solved using big data. Starting with the big data security issues, this paper deals with addressing the topics related to cyber security and information security using the Natural Language Processing technology. Including the well-known cyber-attacks such as phishing identification and spam detection, this paper also addresses issues on information assurance and security such as detection of Advanced Persistent Threat (APT) in DNS and vulnerability analysis. The goal of this paper is to provide the overview of how natural language processing can be used to address cyber security issues.
2020-05-11
Üzüm, İbrahim, Can, Özgü.  2018.  An anomaly detection approach for enterprise file integration. 2018 6th International Symposium on Digital Forensic and Security (ISDFS). :1–4.
An information system based on real-time file integrations has an important role in today's organizations' work process management. By connecting to the network, file flow and integration between corporate systems have gained a great significance. In addition, network and security issues have emerged depending on the file structure and transfer processes. Thus, there has become a need for an effective and self-learning anomaly detection module for file transfer processes in order to provide the persistence of integration channels, accountability of transfer logs and data integrity. This paper proposes a novel anomaly detection approach that focuses on file size and integration duration of file transfers between enterprise systems. For this purpose, size and time anomalies on transferring files will be detected by a machine learning-based structure. Later, an alarm system is going to be developed in order to inform the authenticated individuals about the anomalies.
Kinkelin, Holger, Hauner, Valentin, Niedermayer, Heiko, Carle, Georg.  2018.  Trustworthy configuration management for networked devices using distributed ledgers. NOMS 2018 - 2018 IEEE/IFIP Network Operations and Management Symposium. :1–5.
Numerous IoT applications, like building automation or process control of industrial sites, exist today. These applications inherently have a strong connection to the physical world. Hence, IT security threats cannot only cause problems like data leaks but also safety issues which might harm people. Attacks on IT systems are not only performed by outside attackers but also insiders like administrators. For this reason, we present ongoing work on a Byzantine fault tolerant configuration management system (CMS) that provides control over administrators, restrains their rights, and enforces separation of concerns. We reach this goal by conducting a configuration management process that requires multi-party authorization for critical configurations to prevent individual malicious administrators from performing undesired actions. Only after a configuration has been authorized by multiple experts, it is applied to the targeted devices. For the whole configuration management process, our CMS guarantees accountability and traceability. Lastly, our system is tamper-resistant as we leverage Hyperledger Fabric, which provides a distributed execution environment for our CMS and a blockchain-based distributed ledger that we use to store the configurations. A beneficial side effect of this approach is that our CMS is also suitable to manage configurations for infrastructure shared across different organizations that do not need to trust each other.
2020-05-04
Zalozhnev, Alexey Yu., Andros, Denis A., Ginz, Vasiliy N., Loktionov, Anatoly Eu..  2019.  Information Systems and Network Technologies for Personal Data Cyber Security in Public Health. 2019 International Multidisciplinary Information Technology and Engineering Conference (IMITEC). :1–5.
The article focuses on Personal Data Cyber Security Systems. These systems are the critical components for Health Information Management Systems of Public Health enterprises. The purpose of this article is to inform and provide the reader with Personal Data Cyber Security Legislation and Regulation in Public Health Sector and enlighten him with the Information Systems that were designed and implemented for Personal Data Cyber Security in Public Health.
2020-04-20
Esquivel-Quiros, Luis Gustavo, Barrantes, Elena Gabriela, Darlington, Fernando Esponda.  2018.  Measuring data privacy preserving and machine learning. 2018 7th International Conference On Software Process Improvement (CIMPS). :85–94.

The increasing publication of large amounts of data, theoretically anonymous, can lead to a number of attacks on the privacy of people. The publication of sensitive data without exposing the data owners is generally not part of the software developers concerns. The regulations for the data privacy-preserving create an appropriate scenario to focus on privacy from the perspective of the use or data exploration that takes place in an organization. The increasing number of sanctions for privacy violations motivates the systematic comparison of three known machine learning algorithms in order to measure the usefulness of the data privacy preserving. The scope of the evaluation is extended by comparing them with a known privacy preservation metric. Different parameter scenarios and privacy levels are used. The use of publicly available implementations, the presentation of the methodology, explanation of the experiments and the analysis allow providing a framework of work on the problem of the preservation of privacy. Problems are shown in the measurement of the usefulness of the data and its relationship with the privacy preserving. The findings motivate the need to create optimized metrics on the privacy preferences of the owners of the data since the risks of predicting sensitive attributes by means of machine learning techniques are not usually eliminated. In addition, it is shown that there may be a hundred percent, but it cannot be measured. As well as ensuring adequate performance of machine learning models that are of interest to the organization that data publisher.

2020-04-17
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.
2020-04-13
Horne, Benjamin D., Gruppi, Mauricio, Adali, Sibel.  2019.  Trustworthy Misinformation Mitigation with Soft Information Nudging. 2019 First IEEE International Conference on Trust, Privacy and Security in Intelligent Systems and Applications (TPS-ISA). :245–254.
Research in combating misinformation reports many negative results: facts may not change minds, especially if they come from sources that are not trusted. Individuals can disregard and justify lies told by trusted sources. This problem is made even worse by social recommendation algorithms which help amplify conspiracy theories and information confirming one's own biases due to companies' efforts to optimize for clicks and watch time over individuals' own values and public good. As a result, more nuanced voices and facts are drowned out by a continuous erosion of trust in better information sources. Most misinformation mitigation techniques assume that discrediting, filtering, or demoting low veracity information will help news consumers make better information decisions. However, these negative results indicate that some news consumers, particularly extreme or conspiracy news consumers will not be helped. We argue that, given this background, technology solutions to combating misinformation should not simply seek facts or discredit bad news sources, but instead use more subtle nudges towards better information consumption. Repeated exposure to such nudges can help promote trust in better information sources and also improve societal outcomes in the long run. In this article, we will talk about technological solutions that can help us in developing such an approach, and introduce one such model called Trust Nudging.
2020-04-03
Sadique, Farhan, Bakhshaliyev, Khalid, Springer, Jeff, Sengupta, Shamik.  2019.  A System Architecture of Cybersecurity Information Exchange with Privacy (CYBEX-P). 2019 IEEE 9th Annual Computing and Communication Workshop and Conference (CCWC). :0493—0498.
Rapid evolution of cyber threats and recent trends in the increasing number of cyber-attacks call for adopting robust and agile cybersecurity techniques. Cybersecurity information sharing is expected to play an effective role in detecting and defending against new attacks. However, reservations and or-ganizational policies centering the privacy of shared data have become major setbacks in large-scale collaboration in cyber defense. The situation is worsened by the fact that the benefits of cyber-information exchange are not realized unless many actors participate. In this paper, we argue that privacy preservation of shared threat data will motivate entities to share threat data. Accordingly, we propose a framework called CYBersecurity information EXchange with Privacy (CYBEX-P) to achieve this. CYBEX-P is a structured information sharing platform with integrating privacy-preserving mechanisms. We propose a complete system architecture for CYBEX-P that guarantees maximum security and privacy of data. CYBEX-P outlines the details of a cybersecurity information sharing platform. The adoption of blind processing, privacy preservation, and trusted computing paradigms make CYBEX-P a versatile and secure information exchange platform.
Ayache, Meryeme, Khoumsi, Ahmed, Erradi, Mohammed.  2019.  Managing Security Policies within Cloud Environments Using Aspect-Oriented State Machines. 2019 International Conference on Advanced Communication Technologies and Networking (CommNet). :1—10.
Cloud Computing is the most suitable environment for the collaboration of multiple organizations via its multi-tenancy architecture. However, due to the distributed management of policies within these collaborations, they may contain several anomalies, such as conflicts and redundancies, which may lead to both safety and availability problems. On the other hand, current cloud computing solutions do not offer verification tools to manage access control policies. In this paper, we propose a cloud policy verification service (CPVS), that facilitates to users the management of there own security policies within Openstack cloud environment. Specifically, the proposed cloud service offers a policy verification approach to dynamically choose the adequate policy using Aspect-Oriented Finite State Machines (AO-FSM), where pointcuts and advices are used to adopt Domain-Specific Language (DSL) state machine artifacts. The pointcuts define states' patterns representing anomalies (e.g., conflicts) that may occur in a security policy, while the advices define the actions applied at the selected pointcuts to remove the anomalies. In order to demonstrate the efficiency of our approach, we provide time and space complexities. The approach was implemented as middleware service within Openstack cloud environment. The implementation results show that the middleware can detect and resolve different policy anomalies in an efficient manner.
Kozlov, Aleksandr, Noga, Nikolai.  2019.  The Method of Assessing the Level of Compliance of Divisions of the Complex Network for the Corporate Information Security Policy Indicators. 2019 Twelfth International Conference "Management of large-scale system development" (MLSD). :1—5.

The method of assessment of degree of compliance of divisions of the complex distributed corporate information system to a number of information security indicators is offered. As a result of the methodology implementation a comparative assessment of compliance level of each of the divisions for the corporate information security policy requirements may be given. This assessment may be used for the purpose of further decision-making by the management of the corporation on measures to minimize risks as a result of possible implementation of threats to information security.

Mishra, Menaka, Upadhyay, A.K..  2019.  Need of Private and Public Sector Information Security. 2019 9th International Conference on Cloud Computing, Data Science Engineering (Confluence). :168—173.
In this research paper author surveys the need of data protection from intelligent systems in the private and public sectors. For this, she identifies that the Smart Information Security Intel processes needs to be the suggestive key policy for both sectors of governance either public or private. The information is very sensitive for any organization. When the government offices are concerned, information needs to be abstracted and encapsulated so that there is no information stealing. For this purposes, the art of skill set and new optimized technology needs to be stationed. Author identifies that digital bar-coded air port like security using conveyor belts and digital bar-coded conveyor boxes to scan switched ON articles like internet of things needs to be placed. As otherwise, there can potentially be data, articles or information stealing from the operational sites where access is unauthorized. Such activities shall need to be scrutinized, minutely. The biometric such as fingerprints, iris, voice and face recognition pattern updates in the virtual data tables must be taken to keep data entry-exit log up to-date. The information technicians of the sentinel systems must help catch the anomalies in the professional working time in private and public sectors if there is red flag as indicator. The author in this research paper shall discuss in detail what we shall station, how we shall station and what all measures we might need to undertake to safeguard the stealing of sensitive information from the organizations like administration buildings, government buildings, educational schools, hospitals, courts, private buildings, banks and all other offices nation-wide. The TO-BE new processes shall make the AS-IS office system more information secured, data protected and personnel security stronger.
2020-03-30
Mao, Huajian, Chi, Chenyang, Yu, Jinghui, Yang, Peixiang, Qian, Cheng, Zhao, Dongsheng.  2019.  QRStream: A Secure and Convenient Method for Text Healthcare Data Transferring. 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). :3458–3462.
With the increasing of health awareness, the users become more and more interested in their daily health information and healthcare activities results from healthcare organizations. They always try to collect them together for better usage. Traditionally, the healthcare data is always delivered by paper format from the healthcare organizations, and it is not easy and convenient for data usage and management. They would have to translate these data on paper to digital version which would probably introduce mistakes into the data. It would be necessary if there is a secure and convenient method for electronic health data transferring between the users and the healthcare organizations. However, for the security and privacy problems, almost no healthcare organization provides a stable and full service for health data delivery. In this paper, we propose a secure and convenient method, QRStream, which splits original health data and loads them onto QR code frame streaming for the data transferring. The results shows that QRStream can transfer text health data smoothly with an acceptable performance, for example, transferring 10K data in 10 seconds.
2020-03-23
Karlsson, Linus, Paladi, Nicolae.  2019.  Privacy-Enabled Recommendations for Software Vulnerabilities. 2019 IEEE Intl Conf on Dependable, Autonomic and Secure Computing, Intl Conf on Pervasive Intelligence and Computing, Intl Conf on Cloud and Big Data Computing, Intl Conf on Cyber Science and Technology Congress (DASC/PiCom/CBDCom/CyberSciTech). :564–571.
New software vulnerabilities are published daily. Prioritizing vulnerabilities according to their relevance to the collection of software an organization uses is a costly and slow process. While recommender systems were earlier proposed to address this issue, they ignore the security of the vulnerability prioritization data. As a result, a malicious operator or a third party adversary can collect vulnerability prioritization data to identify the security assets in the enterprise deployments of client organizations. To address this, we propose a solution that leverages isolated execution to protect the privacy of vulnerability profiles without compromising data integrity. To validate an implementation of the proposed solution we integrated it with an existing recommender system for software vulnerabilities. The evaluation of our implementation shows that the proposed solution can effectively complement existing recommender systems for software vulnerabilities.
2020-03-18
Kumar Mangi, S.V.V. Satya Surya Sravan, Hussian S.K., Saddam, Leelavathy, N..  2019.  An Approach for Sending a Confidential Message to the Restricted Users in Defence Based Organization. 2019 International Conference on Vision Towards Emerging Trends in Communication and Networking (ViTECoN). :1–5.
After the creation of the internet, the file sharing process has been changed. Several third-party applications have come to live for sharing and chatting purposes. A spammer can profit by these applications in different ways like, can achieve countless data, can acquire the user's personal information, and furthermore. Later that untrusted cloud storages are used for uploading a file even it is maintained by the third party If they use an untrusted cloud, there is a security problem. We need to give more security for file transfer in the defense-based organization. So, we developed a secure application for group member communication in a secure medium. The user belongs to a specific department from a specific group can access the data from the storage node and decrypt it. Every user in the group needs to register in the node to send or receive the data. Group Manager can restrict the access of the users in a Defense Network and he generates a user list, users in that list can only login to the node and share or download the files. We created a secure platform to upload files and share the data with multiple users by using Dynamic broadcasting Encryption. Users in the list can only download and decrypt the files from the storage node.
Nikoue, Jean Claude, Butakov, Sergey, Malik, Yasir.  2019.  Security Evaluation Methodology for Software Defined Network Solutions. 2019 International Conference on Platform Technology and Service (PlatCon). :1–6.

Software Defined Networking (SDN) has introduced both innovative opportunities and additional risks in the computer networking. Among disadvantages of SDNs one can mention their susceptibility to vulnerabilities associated with both virtualization and the traditional networking. Selecting a proper controller for an organization may not be a trivial task as there is a variety of SDN controllers on the market and each of them may come with its own pros and cons from the security point of view. This research proposes a comprehensive methodology for organizations to evaluate security-related features available in SDN controllers. The methodology can serve as a guideline in the decisions related to SDN choice. The proposed security assessment follows a structured approach to evaluate each layer of the SDN architecture and each metrics defined in presented research has been matched with the security controls defined in NIST 800-53. Through the tests on actual controllers the paper provides an example on how the proposed methodology can be used to evaluate existing SDN solutions.

2020-03-12
Kumar, Randhir, Tripathi, Rakesh.  2019.  Traceability of Counterfeit Medicine Supply Chain through Blockchain. 2019 11th International Conference on Communication Systems Networks (COMSNETS). :568–570.

The main issues with drug safety in the counterfeit medicine supply chain, are to do with how the drugs are initially manufactured. The traceability of right and active pharmaceutical ingredients during actual manufacture is a difficult process, so detecting drugs that do not contain the intended active ingredients can ultimately lead to end-consumer patient harm or even death. Blockchain's advanced features make it capable of providing a basis for complete traceability of drugs, from manufacturer to end consumer, and the ability to identify counterfeit-drug. This paper aims to address the issue of drug safety using Blockchain and encrypted QR(quick response) code security.

2020-03-09
Khan, Iqra, Durad, Hanif, Alam, Masoom.  2019.  Data Analytics Layer For high-interaction Honeypots. 2019 16th International Bhurban Conference on Applied Sciences and Technology (IBCAST). :681–686.

Security of VMs is now becoming a hot topic due to their outsourcing in cloud computing paradigm. All VMs present on the network are connected to each other, making exploited VMs danger to other VMs. and threats to organization. Rejuvenation of virtualization brought the emergence of hyper-visor based security services like VMI (Virtual machine introspection). As there is a greater chance for any intrusion detection system running on the same system, of being dis-abled by the malware or attacker. Monitoring of VMs using VMI, is one of the most researched and accepted technique, that is used to ensure computer systems security mostly in the paradigm of cloud computing. This thesis presents a work that is to integrate LibVMI with Volatility on a KVM, a Linux based hypervisor, to introspect memory of VMs. Both of these tools are used to monitor the state of live VMs. VMI capability of monitoring VMs is combined with the malware analysis and virtual honeypots to achieve the objective of this project. A testing environment is deployed, where a network of VMs is used to be introspected using Volatility plug-ins. Time execution of each plug-in executed on live VMs is calculated to observe the performance of Volatility plug-ins. All these VMs are deployed as Virtual Honeypots having honey-pots configured on them, which is used as a detection mechanism to trigger alerts when some malware attack the VMs. Using STIX (Structure Threat Information Expression), extracted IOCs are converted into the understandable, flexible, structured and shareable format.

2020-03-02
Hamadah, Siham, Aqel, Darah.  2019.  A Proposed Virtual Private Cloud-Based Disaster Recovery Strategy. 2019 IEEE Jordan International Joint Conference on Electrical Engineering and Information Technology (JEEIT). :469–473.

Disaster is an unexpected event in a system lifetime, which can be made by nature or even human errors. Disaster recovery of information technology is an area of information security for protecting data against unsatisfactory events. It involves a set of procedures and tools for returning an organization to a state of normality after an occurrence of a disastrous event. So the organizations need to have a good plan in place for disaster recovery. There are many strategies for traditional disaster recovery and also for cloud-based disaster recovery. This paper focuses on using cloud-based disaster recovery strategies instead of the traditional techniques, since the cloud-based disaster recovery has proved its efficiency in providing the continuity of services faster and in less cost than the traditional ones. The paper introduces a proposed model for virtual private disaster recovery on cloud by using two metrics, which comprise a recovery time objective and a recovery point objective. The proposed model has been evaluated by experts in the field of information technology and the results show that the model has ensured the security and business continuity issues, as well as the faster recovery of a disaster that could face an organization. The paper also highlights the cloud computing services and illustrates the most benefits of cloud-based disaster recovery.

2020-02-26
Bhatnagar, Dev, Som, Subhranil, Khatri, Sunil Kumar.  2019.  Advance Persistant Threat and Cyber Spying - The Big Picture, Its Tools, Attack Vectors and Countermeasures. 2019 Amity International Conference on Artificial Intelligence (AICAI). :828–839.

Advance persistent threat is a primary security concerns to the big organizations and its technical infrastructure, from cyber criminals seeking personal and financial information to state sponsored attacks designed to disrupt, compromising infrastructure, sidestepping security efforts thus causing serious damage to organizations. A skilled cybercriminal using multiple attack vectors and entry points navigates around the defenses, evading IDS/Firewall detection and breaching the network in no time. To understand the big picture, this paper analyses an approach to advanced persistent threat by doing the same things the bad guys do on a network setup. We will walk through various steps from foot-printing and reconnaissance, scanning networks, gaining access, maintaining access to finally clearing tracks, as in a real world attack. We will walk through different attack tools and exploits used in each phase and comparative study on their effectiveness, along with explaining their attack vectors and its countermeasures. We will conclude the paper by explaining the factors which actually qualify to be an Advance Persistent Threat.

2020-02-18
Quan, Guocong, Tan, Jian, Eryilmaz, Atilla.  2019.  Counterintuitive Characteristics of Optimal Distributed LRU Caching Over Unreliable Channels. IEEE INFOCOM 2019 - IEEE Conference on Computer Communications. :694–702.
Least-recently-used (LRU) caching and its variants have conventionally been used as a fundamental and critical method to ensure fast and efficient data access in computer and communication systems. Emerging data-intensive applications over unreliable channels, e.g., mobile edge computing and wireless content delivery networks, have imposed new challenges in optimizing LRU caching systems in environments prone to failures. Most existing studies focus on reliable channels, e.g., on wired Web servers and within data centers, which have already yielded good insights with successful algorithms on how to reduce cache miss ratios. Surprisingly, we show that these widely held insights do not necessarily hold true for unreliable channels. We consider a single-hop multi-cache distributed system with data items being dispatched by random hashing. The objective is to achieve efficient cache organization and data placement. The former allocates the total memory space to each of the involved caches. The latter decides data routing strategies and data replication schemes. Analytically we characterize the unreliable LRU caches by explicitly deriving their asymptotic miss probabilities. Based on these results, we optimize the system design. Remarkably, these results sometimes are counterintuitive, differing from the ones obtained for reliable caches. We discover an interesting phenomenon: asymmetric cache organization is optimal even for symmetric channels. Specifically, even when channel unreliability probabilities are equal, allocating the cache spaces unequally can achieve a better performance. We also propose an explicit unequal allocation policy that outperforms the equal allocation. In addition, we prove that splitting the total cache space into separate LRU caches can achieve a lower asymptotic miss probability than resource pooling that organizes the total space in a single LRU cache. These results provide new and even counterintuitive insights that motivate novel designs for caching systems over unreliable channels. They can potentially be exploited to further improve the system performance in real practice.
2020-02-17
Yee, George O. M..  2019.  Designing Good Security Metrics. 2019 IEEE 43rd Annual Computer Software and Applications Conference (COMPSAC). 2:580–585.

This paper begins with an introduction to security metrics, describing the need for security metrics, followed by a discussion of the nature of security metrics, including the challenges found with some security metrics used in the past. The paper then discusses what makes a good security metric and proposes a rigorous step-by-step method that can be applied to design good security metrics, and to test existing security metrics to see if they are good metrics. Application examples are included to illustrate the method.

Hadar, Ethan, Hassanzadeh, Amin.  2019.  Big Data Analytics on Cyber Attack Graphs for Prioritizing Agile Security Requirements. 2019 IEEE 27th International Requirements Engineering Conference (RE). :330–339.
In enterprise environments, the amount of managed assets and vulnerabilities that can be exploited is staggering. Hackers' lateral movements between such assets generate a complex big data graph, that contains potential hacking paths. In this vision paper, we enumerate risk-reduction security requirements in large scale environments, then present the Agile Security methodology and technologies for detection, modeling, and constant prioritization of security requirements, agile style. Agile Security models different types of security requirements into the context of an attack graph, containing business process targets and critical assets identification, configuration items, and possible impacts of cyber-attacks. By simulating and analyzing virtual adversary attack paths toward cardinal assets, Agile Security examines the business impact on business processes and prioritizes surgical requirements. Thus, handling these requirements backlog that are constantly evaluated as an outcome of employing Agile Security, gradually increases system hardening, reduces business risks and informs the IT service desk or Security Operation Center what remediation action to perform next. Once remediated, Agile Security constantly recomputes residual risk, assessing risk increase by threat intelligence or infrastructure changes versus defender's remediation actions in order to drive overall attack surface reduction.
Skopik, Florian, Filip, Stefan.  2019.  Design principles for national cyber security sensor networks: Lessons learned from small-scale demonstrators. 2019 International Conference on Cyber Security and Protection of Digital Services (Cyber Security). :1–8.
The timely exchange of information on new threats and vulnerabilities has become a cornerstone of effective cyber defence in recent years. Especially national authorities increasingly assume their role as information brokers through national cyber security centres and distribute warnings on new attack vectors and vital recommendations on how to mitigate them. Although many of these initiatives are effective to some degree, they also suffer from severe limitations. Many steps in the exchange process require extensive human involvement to manually review, vet, enrich, analyse and distribute security information. Some countries have therefore started to adopt distributed cyber security sensor networks to enable the automatic collection, analysis and preparation of security data and thus effectively overcome limiting scalability factors. The basic idea of IoC-centric cyber security sensor networks is that the national authorities distribute Indicators of Compromise (IoCs) to organizations and receive sightings in return. This effectively helps them to estimate the spreading of malware, anticipate further trends of spreading and derive vital findings for decision makers. While this application case seems quite simple, there are some tough questions to be answered in advance, which steer the further design decisions: How much can the monitored organization be trusted to be a partner in the search for malware? How much control of the scanning process should be delegated to the organization? What is the right level of search depth? How to deal with confidential indicators? What can be derived from encrypted traffic? How are new indicators distributed, prioritized, and scan targets selected in a scalable manner? What is a good strategy to re-schedule scans to derive meaningful data on trends, such as rate of spreading? This paper suggests a blueprint for a sensor network and raises related questions, outlines design principles, and discusses lessons learned from small-scale pilots.
Prajanti, Anisa Dewi, Ramli, Kalamullah.  2019.  A Proposed Framework for Ranking Critical Information Assets in Information Security Risk Assessment Using the OCTAVE Allegro Method with Decision Support System Methods. 2019 34th International Technical Conference on Circuits/Systems, Computers and Communications (ITC-CSCC). :1–4.
The security of an organization lies not only in physical buildings, but also in its information assets. Safeguarding information assets requires further study to establish optimal security mitigation steps. In determining the appropriate mitigation of information assets, both an information security risk assessment and a clear and measurable rating are required. Most risk management methods do not provide the right focus on ranking the critical information assets of an organization. This paper proposes a framework approach for ranking critical information assets. The proposed framework uses the OCTAVE Allegro method, which focuses on profiling information assets by combining ranking priority measurements using decision support system methods, such as Simple Additive Weighting (SAW) and Analytic Hierarchy Process (AHP). The combined OCTAVE Allegro-SAW and OCTAVE Allegro-AHP methods are expected to better address risk priority as an input to making mitigation decisions for critical information assets. These combinations will help management to avoid missteps in adjusting budget needs allocation or time duration by selecting asset information mitigation using the ranking results of the framework.
Rindell, Kalle, Holvitie, Johannes.  2019.  Security Risk Assessment and Management as Technical Debt. 2019 International Conference on Cyber Security and Protection of Digital Services (Cyber Security). :1–8.
The endeavor to achieving software security consists of a set of risk-based security engineering processes during software development. In iterative software development, the software design typically evolves as the project matures, and the technical environment may undergo considerable changes. This increases the work load of identifying, assessing and managing the security risk by each iteration, and after every change. Besides security risk, the changes also accumulate technical debt, an allegory for postponed or sub-optimally performed work. To manage the security risk in software development efficiently, and in terms and definitions familiar to software development organizations, the concept of technical debt is extended to contain security debt. To accommodate new technical debt with potential security implications, a security debt management approach is introduced. The selected approach is an extension to portfolio-based technical debt management framework. This includes identifying security risk in technical debt, and also provides means to expose debt by security engineering techniques that would otherwise remained hidden. The proposed approach includes risk-based extensions to prioritization mechanisms in existing technical debt management systems. Identification, management and repayment techniques are presented to identify, assess, and mitigate the security debt.