Visible to the public Biblio

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2019-11-04
Khan, Muhammad Imran, O’Sullivan, Barry, Foley, Simon N..  2018.  Towards Modelling Insiders Behaviour as Rare Behaviour to Detect Malicious RDBMS Access. 2018 IEEE International Conference on Big Data (Big Data). :3094–3099.
The heart of any enterprise is its databases where the application data is stored. Organizations frequently place certain access control mechanisms to prevent access by unauthorized employees. However, there is persistent concern about malicious insiders. Anomaly-based intrusion detection systems are known to have the potential to detect insider attacks. Accurate modelling of insiders behaviour within the framework of Relational Database Management Systems (RDBMS) requires attention. The majority of past research considers SQL queries in isolation when modelling insiders behaviour. However, a query in isolation can be safe, while a sequence of queries might result in malicious access. In this work, we consider sequences of SQL queries when modelling behaviours to detect malicious RDBMS accesses using frequent and rare item-sets mining. Preliminary results demonstrate that the proposed approach has the potential to detect malicious RDBMS accesses by insiders.
2019-10-07
Aidan, J. S., Zeenia, Garg, U..  2018.  Advanced Petya Ransomware and Mitigation Strategies. 2018 First International Conference on Secure Cyber Computing and Communication (ICSCCC). :23–28.

In this cyber era, the cyber threats have reached a new level of menace and maturity. One of the major threat in this cyber world nowadays is ransomware attack which had affected millions of computers. Ransomware locks the valuable data with often unbreakable encryption codes making it inaccessible for both organization and consumers, thus demanding heavy ransom to decrypt the data. In this paper, advanced and improved version of the Petya ransomware has been introduced which has a reduced anti-virus detection of 33% which actually was 71% with the original version. System behavior is also monitored during the attack and analysis of this behavior is performed and described. Along with the behavioral analysis two mitigation strategies have also been proposed to defend the systems from the ransomware attack. This multi-layered approach for the security of the system will minimize the rate of infection as cybercriminals continue to refine their tactics, making it difficult for the organization's complacent development.

2019-09-26
Nelmiawati, Arifandi, W..  2018.  A Seamless Secret Sharing Scheme Implementation for Securing Data in Public Cloud Storage Service. 2018 International Conference on Applied Engineering (ICAE). :1-5.
Public cloud data storage services were considered as a potential alternative to store low-cost digital data in the short term. They are offered by different providers on the Internet. Some providers offer limited free plans for the users who are starting the service. However, data security concern arises when data stored are considered as a valuable asset. This study explores the usage of secret sharing scheme: Rabin's IDA and Shamir's SSA to implement a tool called dCloud for file protection stored in public cloud storage in a seamless way. It addresses data security by hiding its complexities when targeting ordinary non-technical users. The secret key is automatically generated by dCloud in a secure random way on Rabin's IDA. Shamir's SSA completes the process through dispersing the key into each of Rabin's IDA output files. Moreover, the Hash value of the original file is added to each of those output files to confirm the integrity of the file during reconstruction. Besides, the authentication key is used to communicate with all of the defined service providers during storage and reconstruction as well. It is stored into local secure key-store. By having a key to access the key-store, an ordinary non-technical user will be able to use dCloud to store and retrieve targeted file within defined public cloud storage services securely.
2019-08-26
Mavroeidis, V., Vishi, K., Jøsang, A..  2018.  A Framework for Data-Driven Physical Security and Insider Threat Detection. 2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM). :1108–1115.

This paper presents PSO, an ontological framework and a methodology for improving physical security and insider threat detection. PSO can facilitate forensic data analysis and proactively mitigate insider threats by leveraging rule-based anomaly detection. In all too many cases, rule-based anomaly detection can detect employee deviations from organizational security policies. In addition, PSO can be considered a security provenance solution because of its ability to fully reconstruct attack patterns. Provenance graphs can be further analyzed to identify deceptive actions and overcome analytical mistakes that can result in bad decision-making, such as false attribution. Moreover, the information can be used to enrich the available intelligence (about intrusion attempts) that can form use cases to detect and remediate limitations in the system, such as loosely-coupled provenance graphs that in many cases indicate weaknesses in the physical security architecture. Ultimately, validation of the framework through use cases demonstrates and proves that PS0 can improve an organization's security posture in terms of physical security and insider threat detection.

2019-07-01
Arabsorkhi, A., Ghaffari, F..  2018.  Security Metrics: Principles and Security Assessment Methods. 2018 9th International Symposium on Telecommunications (IST). :305–310.

Nowadays, Information Technology is one of the important parts of human life and also of organizations. Organizations face problems such as IT problems. To solve these problems, they have to improve their security sections. Thus there is a need for security assessments within organizations to ensure security conditions. The use of security standards and general metric can be useful for measuring the safety of an organization; however, it should be noted that the general metric which are applied to businesses in general cannot be effective in this particular situation. Thus it's important to select metric standards for different businesses to improve both cost and organizational security. The selection of suitable security measures lies in the use of an efficient way to identify them. Due to the numerous complexities of these metric and the extent to which they are defined, in this paper that is based on comparative study and the benchmarking method, taxonomy for security measures is considered to be helpful for a business to choose metric tailored to their needs and conditions.

Rasin, A., Wagner, J., Heart, K., Grier, J..  2018.  Establishing Independent Audit Mechanisms for Database Management Systems. 2018 IEEE International Symposium on Technologies for Homeland Security (HST). :1-7.

The pervasive use of databases for the storage of critical and sensitive information in many organizations has led to an increase in the rate at which databases are exploited in computer crimes. While there are several techniques and tools available for database forensic analysis, such tools usually assume an apriori database preparation, such as relying on tamper-detection software to already be in place and the use of detailed logging. Further, such tools are built-in and thus can be compromised or corrupted along with the database itself. In practice, investigators need forensic and security audit tools that work on poorlyconfigured systems and make no assumptions about the extent of damage or malicious hacking in a database.In this paper, we present our database forensics methods, which are capable of examining database content from a storage (disk or RAM) image without using any log or file system metadata. We describe how these methods can be used to detect security breaches in an untrusted environment where the security threat arose from a privileged user (or someone who has obtained such privileges). Finally, we argue that a comprehensive and independent audit framework is necessary in order to detect and counteract threats in an environment where the security breach originates from an administrator (either at database or operating system level).

2019-06-10
Debatty, T., Mees, W., Gilon, T..  2018.  Graph-Based APT Detection. 2018 International Conference on Military Communications and Information Systems (ICMCIS). :1-8.

In this paper we propose a new algorithm to detect Advanced Persistent Threats (APT's) that relies on a graph model of HTTP traffic. We also implement a complete detection system with a web interface that allows to interactively analyze the data. We perform a complete parameter study and experimental evaluation using data collected on a real network. The results show that the performance of our system is comparable to currently available antiviruses, although antiviruses use signatures to detect known malwares while our algorithm solely uses behavior analysis to detect new undocumented attacks.

2019-05-08
Moore, A. P., Cassidy, T. M., Theis, M. C., Bauer, D., Rousseau, D. M., Moore, S. B..  2018.  Balancing Organizational Incentives to Counter Insider Threat. 2018 IEEE Security and Privacy Workshops (SPW). :237–246.

Traditional security practices focus on negative incentives that attempt to force compliance through constraints, monitoring, and punishment. This paper describes a missing dimension of most organizations' insider threat defense-one that explicitly considers positive incentives for attracting individuals to act in the interests of the organization. Positive incentives focus on properties of the organizational context of workforce management practices - including those relating to organizational supportiveness, coworker connectedness, and job engagement. Without due attention to the organizational context in which insider threats occur, insider misbehaviors may simply reoccur as a natural response to counterproductive or dysfunctional management practices. A balanced combination of positive and negative incentives can improve employees' relationships with the organization and provide a means for employees to better cope with personal and professional stressors. An insider threat program that balances organizational incentives can become an advocate for the workforce and a means for improving employee work life - a welcome message to employees who feel threatened by programs focused on discovering insider wrongdoing.

Basu, S., Chua, Y. H. Victoria, Lee, M. Wah, Lim, W. G., Maszczyk, T., Guo, Z., Dauwels, J..  2018.  Towards a data-driven behavioral approach to prediction of insider-threat. 2018 IEEE International Conference on Big Data (Big Data). :4994–5001.

Insider threats pose a challenge to all companies and organizations. Identification of culprit after an attack is often too late and result in detrimental consequences for the organization. Majority of past research on insider threat has focused on post-hoc personality analysis of known insider threats to identify personality vulnerabilities. It has been proposed that certain personality vulnerabilities place individuals to be at risk to perpetuating insider threats should the environment and opportunity arise. To that end, this study utilizes a game-based approach to simulate a scenario of intellectual property theft and investigate behavioral and personality differences of individuals who exhibit insider-threat related behavior. Features were extracted from games, text collected through implicit and explicit measures, simultaneous facial expression recordings, and personality variables (HEXACO, Dark Triad and Entitlement Attitudes) calculated from questionnaire. We applied ensemble machine learning algorithms and show that they produce an acceptable balance of precision and recall. Our results showcase the possibility of harnessing personality variables, facial expressions and linguistic features in the modeling and prediction of insider-threat.

Mylrea, M., Gourisetti, S. N. G., Larimer, C., Noonan, C..  2018.  Insider Threat Cybersecurity Framework Webtool Methodology: Defending Against Complex Cyber-Physical Threats. 2018 IEEE Security and Privacy Workshops (SPW). :207–216.

This paper demonstrates how the Insider Threat Cybersecurity Framework (ITCF) web tool and methodology help provide a more dynamic, defense-in-depth security posture against insider cyber and cyber-physical threats. ITCF includes over 30 cybersecurity best practices to help organizations identify, protect, detect, respond and recover to sophisticated insider threats and vulnerabilities. The paper tests the efficacy of this approach and helps validate and verify ITCF's capabilities and features through various insider attacks use-cases. Two case-studies were explored to determine how organizations can leverage ITCF to increase their overall security posture against insider attacks. The paper also highlights how ITCF facilitates implementation of the goals outlined in two Presidential Executive Orders to improve the security of classified information and help owners and operators secure critical infrastructure. In realization of these goals, ITCF: provides an easy to use rapid assessment tool to perform an insider threat self-assessment; determines the current insider threat cybersecurity posture; defines investment-based goals to achieve a target state; connects the cybersecurity posture with business processes, functions, and continuity; and finally, helps develop plans to answer critical organizational cybersecurity questions. In this paper, the webtool and its core capabilities are tested by performing an extensive comparative assessment over two different high-profile insider threat incidents. 

2019-04-01
Wang, R., He, J., Liu, C., Li, Q., Tsai, W., Deng, E..  2018.  A Privacy-Aware PKI System Based on Permissioned Blockchains. 2018 IEEE 9th International Conference on Software Engineering and Service Science (ICSESS). :928–931.

Public key infrastructure (PKI) is the foundation and core of network security construction. Blockchain (BC) has many technical characteristics, such as decentralization, impossibility of being tampered with and forged, which makes it have incomparable advantages in ensuring information credibility, security, traceability and other aspects of traditional technology. In this paper, a method of constructing PKI certificate system based on permissioned BC is proposed. The problems of multi-CA mutual trust, poor certificate configuration efficiency and single point failure in digital certificate system are solved by using the characteristics of BC distribution and non-tampering. At the same time, in order to solve the problem of identity privacy on BC, this paper proposes a privacy-aware PKI system based on permissioned BCs. This system is an anonymous digital certificate publishing scheme., which achieves the separation of user registration and authorization, and has the characteristics of anonymity and conditional traceability, so as to realize to protect user's identity privacy. The system meets the requirements of certificate security and anonymity, reduces the cost of CA construction, operation and maintenance in traditional PKI technology, and improves the efficiency of certificate application and configuration.

2019-03-28
Stavrou, E..  2018.  Enhancing Cyber Situational Awareness: A New Perspective of Password Auditing Tools. 2018 International Conference On Cyber Situational Awareness, Data Analytics And Assessment (Cyber SA). :1-4.

Password auditing can enhance the cyber situational awareness of defenders, e.g. cyber security/IT professionals, with regards to the strength of text-based authentication mechanisms utilized in an organization. Auditing results can proactively indicate if weak passwords exist in an organization, decreasing the risks of compromisation. Password cracking is a typical and time-consuming way to perform password auditing. Given that defenders perform password auditing within a specific evaluation timeframe, the cracking process needs to be optimized to yield useful results. Existing password cracking tools do not provide holistic features to optimize the process. Therefore, the need arises to build new password auditing toolkits to assist defenders to achieve their task in an effective and efficient way. Moreover, to maximize the benefits of password auditing, a security policy should be utilized. Currently the efforts focus on the specification of password security policies, providing rules on how to construct passwords. This work proposes the functionality that should be supported by next-generation password auditing toolkits and provides guidelines to drive the specification of a relevant password auditing policy.

2019-03-15
Nicho, M., Khan, S. N..  2018.  A Decision Matrix Model to Identify and Evaluate APT Vulnerabilities at the User Plane. 2018 41st International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO). :1155-1160.
While advances in cyber-security defensive mechanisms have substantially prevented malware from penetrating into organizational Information Systems (IS) networks, organizational users have found themselves vulnerable to threats emanating from Advanced Persistent Threat (APT) vectors, mostly in the form of spear phishing. In this respect, the question of how an organizational user can differentiate between a genuine communication and a similar looking fraudulent communication in an email/APT threat vector remains a dilemma. Therefore, identifying and evaluating the APT vector attributes and assigning relative weights to them can assist the user to make a correct decision when confronted with a scenario that may be genuine or a malicious APT vector. In this respect, we propose an APT Decision Matrix model which can be used as a lens to build multiple APT threat vector scenarios to identify threat attributes and their weights, which can lead to systems compromise.
2019-03-04
Gugelmann, D., Sommer, D., Lenders, V., Happe, M., Vanbever, L..  2018.  Screen watermarking for data theft investigation and attribution. 2018 10th International Conference on Cyber Conflict (CyCon). :391–408.
Organizations not only need to defend their IT systems against external cyber attackers, but also from malicious insiders, that is, agents who have infiltrated an organization or malicious members stealing information for their own profit. In particular, malicious insiders can leak a document by simply opening it and taking pictures of the document displayed on the computer screen with a digital camera. Using a digital camera allows a perpetrator to easily avoid a log trail that results from using traditional communication channels, such as sending the document via email. This makes it difficult to identify and prove the identity of the perpetrator. Even a policy prohibiting the use of any device containing a camera cannot eliminate this threat since tiny cameras can be hidden almost everywhere. To address this leakage vector, we propose a novel screen watermarking technique that embeds hidden information on computer screens displaying text documents. The watermark is imperceptible during regular use, but can be extracted from pictures of documents shown on the screen, which allows an organization to reconstruct the place and time of the data leak from recovered leaked pictures. Our approach takes advantage of the fact that the human eye is less sensitive to small luminance changes than digital cameras. We devise a symbol shape that is invisible to the human eye, but still robust to the image artifacts introduced when taking pictures. We complement this symbol shape with an error correction coding scheme that can handle very high bit error rates and retrieve watermarks from cropped and compressed pictures. We show in an experimental user study that our screen watermarks are not perceivable by humans and analyze the robustness of our watermarks against image modifications.
2019-02-13
Joshi, M., Joshi, K., Finin, T..  2018.  Attribute Based Encryption for Secure Access to Cloud Based EHR Systems. 2018 IEEE 11th International Conference on Cloud Computing (CLOUD). :932–935.
Medical organizations find it challenging to adopt cloud-based electronic medical records services, due to the risk of data breaches and the resulting compromise of patient data. Existing authorization models follow a patient centric approach for EHR management where the responsibility of authorizing data access is handled at the patients' end. This however creates a significant overhead for the patient who has to authorize every access of their health record. This is not practical given the multiple personnel involved in providing care and that at times the patient may not be in a state to provide this authorization. Hence there is a need of developing a proper authorization delegation mechanism for safe, secure and easy cloud-based EHR management. We have developed a novel, centralized, attribute based authorization mechanism that uses Attribute Based Encryption (ABE) and allows for delegated secure access of patient records. This mechanism transfers the service management overhead from the patient to the medical organization and allows easy delegation of cloud-based EHR's access authority to the medical providers. In this paper, we describe this novel ABE approach as well as the prototype system that we have created to illustrate it.
2019-02-08
Polyakov, V. V., Lapin, S. A..  2018.  Architecture of the Honeypot System for Studying Targeted Attacks. 2018 XIV International Scientific-Technical Conference on Actual Problems of Electronics Instrument Engineering (APEIE). :202-205.
Among the threats to information systems of state institutions, enterprises and financial organizations of particular importance are those originating from organized criminal groups that specialize in obtaining unauthorized access to the computer information protected by law. Criminal groups often possess a material base including financial, technical, human and other resources that allow to perform targeted attacks on information resources as secretly as possible. The principal features of such targeted attacks are the use of software created or modified specifically for use in illegal purposes with respect to specific organizations. Due to these circumstances, the detection of such attacks is quite difficult, and their prevention is even more complicated. In this regard, the task of identifying and analyzing such threats is very relevant. One effective way to solve it is to implement the Honeypot system, which allows to research the strategy and tactics of the attackers. In the present article, there is proposed the original architecture of the Honeypot system designed to study targeted attacks on information systems of criminogenic objects. The architectural design includes such basic elements as the functional component, the registrar of events occurring in the system and the protector. The key features of the proposed Honeypot system are considered, and the functional purpose of its main components is described. The proposed system can find its application in providing information security of institutions, organizations and enterprises, it can be used in the development of information security systems.
2019-01-21
Ayoade, G., Chandra, S., Khan, L., Hamlen, K., Thuraisingham, B..  2018.  Automated Threat Report Classification over Multi-Source Data. 2018 IEEE 4th International Conference on Collaboration and Internet Computing (CIC). :236–245.

With an increase in targeted attacks such as advanced persistent threats (APTs), enterprise system defenders require comprehensive frameworks that allow them to collaborate and evaluate their defense systems against such attacks. MITRE has developed a framework which includes a database of different kill-chains, tactics, techniques, and procedures that attackers employ to perform these attacks. In this work, we leverage natural language processing techniques to extract attacker actions from threat report documents generated by different organizations and automatically classify them into standardized tactics and techniques, while providing relevant mitigation advisories for each attack. A naïve method to achieve this is by training a machine learning model to predict labels that associate the reports with relevant categories. In practice, however, sufficient labeled data for model training is not always readily available, so that training and test data come from different sources, resulting in bias. A naïve model would typically underperform in such a situation. We address this major challenge by incorporating an importance weighting scheme called bias correction that efficiently utilizes available labeled data, given threat reports, whose categories are to be automatically predicted. We empirically evaluated our approach on 18,257 real-world threat reports generated between year 2000 and 2018 from various computer security organizations to demonstrate its superiority by comparing its performance with an existing approach.

Tsuda, Y., Nakazato, J., Takagi, Y., Inoue, D., Nakao, K., Terada, K..  2018.  A Lightweight Host-Based Intrusion Detection Based on Process Generation Patterns. 2018 13th Asia Joint Conference on Information Security (AsiaJCIS). :102–108.
Advanced persistent threat (APT) has been considered globally as a serious social problem since the 2010s. Adversaries of this threat, at first, try to penetrate into targeting organizations by using a backdoor which is opened with drive-by-download attacks, malicious e-mail attachments, etc. After adversaries' intruding, they usually execute benign applications (e.g, OS built-in commands, management tools published by OS vendors, etc.) for investigating networks of targeting organizations. Therefore, if they penetrate into networks once, it is difficult to rapidly detect these malicious activities only by using anti-virus software or network-based intrusion systems. Meanwhile, enterprise networks are managed well in general. That means network administrators have a good grasp of installed applications and routinely used applications for employees' daily works. Thereby, in order to find anomaly behaviors on well-managed networks, it is effective to observe changes executing their applications. In this paper, we propose a lightweight host-based intrusion detection system by using process generation patterns. Our system periodically collects lists of active processes from each host, then the system constructs process trees from the lists. In addition, the system detects anomaly processes from the process trees considering parent-child relationships, execution sequences and lifetime of processes. Moreover, we evaluated the system in our organization. The system collected 2, 403, 230 process paths in total from 498 hosts for two months, then the system could extract 38 anomaly processes. Among them, one PowerShell process was also detected by using an anti-virus software running on our organization. Furthermore, our system could filter out the other 18 PowerShell processes, which were used for maintenance of our network.
Khosravi-Farmad, M., Ramaki, A. A., Bafghi, A. G..  2018.  Moving Target Defense Against Advanced Persistent Threats for Cybersecurity Enhancement. 2018 8th International Conference on Computer and Knowledge Engineering (ICCKE). :280–285.
One of the main security concerns of enterprise-level organizations which provide network-based services is combating with complex cybersecurity attacks like advanced persistent threats (APTs). The main features of these attacks are being multilevel, multi-step, long-term and persistent. Also they use an intrusion kill chain (IKC) model to proceed the attack steps and reach their goals on targets. Traditional security solutions like firewalls and intrusion detection and prevention systems (IDPSs) are not able to prevent APT attack strategies and block them. Recently, deception techniques are proposed to defend network assets against malicious activities during IKC progression. One of the most promising approaches against APT attacks is Moving Target Defense (MTD). MTD techniques can be applied to attack steps of any abstraction levels in a networked infrastructure (application, host, and network) dynamically for disruption of successful execution of any on the fly IKCs. In this paper, after presentation and discussion on common introduced IKCs, one of them is selected and is used for further analysis. Also, after proposing a new and comprehensive taxonomy of MTD techniques in different levels, a mapping analysis is conducted between IKC models and existing MTD techniques. Finally, the effect of MTD is evaluated during a case study (specifically IP Randomization). The experimental results show that the MTD techniques provide better means to defend against IKC-based intrusion activities.
2019-01-16
Turaev, H., Zavarsky, P., Swar, B..  2018.  Prevention of Ransomware Execution in Enterprise Environment on Windows OS: Assessment of Application Whitelisting Solutions. 2018 1st International Conference on Data Intelligence and Security (ICDIS). :110–118.

Application whitelisting software allows only examined and trusted applications to run on user's machine. Since many malicious files don't require administrative privileges in order for them to be executed, whitelisting can be the only way to block the execution of unauthorized applications in enterprise environment and thus prevent infection or data breach. In order to assess the current state of such solutions, the access to three whitelisting solution licenses was obtained with the purpose to test their effectiveness against different modern types of ransomware found in the wild. To conduct this study a virtual environment was used with Windows Server and Enterprise editions installed. The objective of this paper is not to evaluate each vendor or make recommendations of purchasing specific software but rather to assess the ability of application control solutions to block execution of ransomware files, as well as assess the potential for future research. The results of the research show the promise and effectiveness of whitelisting solutions.

2018-09-12
Weintraub, E..  2017.  Estimating Target Distribution in security assessment models. 2017 IEEE 2nd International Verification and Security Workshop (IVSW). :82–87.
Organizations are exposed to various cyber-attacks. When a component is exploited, the overall computed damage is impacted by the number of components the network includes. This work is focuses on estimating the Target Distribution characteristic of an attacked network. According existing security assessment models, Target Distribution is assessed by using ordinal values based on users' intuitive knowledge. This work is aimed at defining a formula which enables measuring quantitatively the attacked components' distribution. The proposed formula is based on the real-time configuration of the system. Using the proposed measure, firms can quantify damages, allocate appropriate budgets to actual real risks and build their configuration while taking in consideration the risks impacted by components' distribution. The formula is demonstrated as part of a security continuous monitoring system.
2018-09-05
Turnley, J., Wachtel, A., Muñoz-Ramos, K., Hoffman, M., Gauthier, J., Speed, A., Kittinger, R..  2017.  Modeling human-technology interaction as a sociotechnical system of systems. 2017 12th System of Systems Engineering Conference (SoSE). :1–6.
As system of systems (SoS) models become increasingly complex and interconnected a new approach is needed to capture the effects of humans within the SoS. Many real-life events have shown the detrimental outcomes of failing to account for humans in the loop. This research introduces a novel and cross-disciplinary methodology for modeling humans interacting with technologies to perform tasks within an SoS specifically within a layered physical security system use case. Metrics and formulations developed for this new way of looking at SoS termed sociotechnical SoS allow for the quantification of the interplay of effectiveness and efficiency seen in detection theory to measure the ability of a physical security system to detect and respond to threats. This methodology has been applied to a notional representation of a small military Forward Operating Base (FOB) as a proof-of-concept.
2018-07-06
Sun, R., Yuan, X., Lee, A., Bishop, M., Porter, D. E., Li, X., Gregio, A., Oliveira, D..  2017.  The dose makes the poison \#x2014; Leveraging uncertainty for effective malware detection. 2017 IEEE Conference on Dependable and Secure Computing. :123–130.

Malware has become sophisticated and organizations don't have a Plan B when standard lines of defense fail. These failures have devastating consequences for organizations, such as sensitive information being exfiltrated. A promising avenue for improving the effectiveness of behavioral-based malware detectors is to combine fast (usually not highly accurate) traditional machine learning (ML) detectors with high-accuracy, but time-consuming, deep learning (DL) models. The main idea is to place software receiving borderline classifications by traditional ML methods in an environment where uncertainty is added, while software is analyzed by time-consuming DL models. The goal of uncertainty is to rate-limit actions of potential malware during deep analysis. In this paper, we describe Chameleon, a Linux-based framework that implements this uncertain environment. Chameleon offers two environments for its OS processes: standard - for software identified as benign by traditional ML detectors - and uncertain - for software that received borderline classifications analyzed by ML methods. The uncertain environment will bring obstacles to software execution through random perturbations applied probabilistically on selected system calls. We evaluated Chameleon with 113 applications from common benchmarks and 100 malware samples for Linux. Our results show that at threshold 10%, intrusive and non-intrusive strategies caused approximately 65% of malware to fail accomplishing their tasks, while approximately 30% of the analyzed benign software to meet with various levels of disruption (crashed or hampered). We also found that I/O-bound software was three times more affected by uncertainty than CPU-bound software.

2018-06-20
Singh, E. P..  2017.  Re-joining of authorized nodes in MANETs using EGSR scheme and detection of internal attacks using 2ACK scheme. 2017 IEEE 8th Annual Ubiquitous Computing, Electronics and Mobile Communication Conference (UEMCON). :306–311.

One of the specially designated versatile networks, commonly referred to as MANET, performs on the basics that each and every one grouping in nodes totally operate in self-sorting out limits. In any case, performing in a group capacity maximizes quality and different sources. Mobile ad hoc network is a wireless infrastructureless network. Due to its unique features, various challenges are faced under MANET when the role of routing and its security comes into play. The review has demonstrated that the impact of failures during the information transmission has not been considered in the existing research. The majority of strategies for ad hoc networks just determines the path and transmits the data which prompts to packet drop in case of failures, thus resulting in low dependability. The majority of the existing research has neglected the use of the rejoining processing of the root nodes network. Most of the existing techniques are based on detecting the failures but the use of path re-routing has also been neglected in the existing methods. Here, we have proposed a method of path re-routing for managing the authorized nodes and managing the keys for group in ad hoc environment. Securing Schemes, named as 2ACK and the EGSR schemes have been proposed, which may be truly interacted to most of the routing protocol. The path re-routing has the ability to reduce the ratio of dropped packets. The comparative analysis has clearly shown that the proposed technique outperforms the available techniques in terms of various quality metrics.

2018-05-09
Jillepalli, A. A., Leon, D. C. d, Steiner, S., Sheldon, F. T., Haney, M. A..  2017.  Hardening the Client-Side: A Guide to Enterprise-Level Hardening of Web Browsers. 2017 IEEE 15th Intl Conf on Dependable, Autonomic and Secure Computing, 15th Intl Conf on Pervasive Intelligence and Computing, 3rd Intl Conf on Big Data Intelligence and Computing and Cyber Science and Technology Congress(DASC/PiCom/DataCom/CyberSciTech). :687–692.
Today, web browsers are a major avenue for cyber-compromise and data breaches. Web browser hardening, through high-granularity and least privilege tailored configurations, can help prevent or mitigate many of these attack avenues. For example, on a classic client desktop infrastructure, an enforced configuration that enables users to use one browser to connect to critical and trusted websites and a different browser for un-trusted sites, with the former restricted to trusted sites and the latter with JavaScript and Plugins disabled by default, may help prevent most JavaScript and Plugin-based attacks to critical enterprise sites. However, most organizations, today, still allow web browsers to run with their default configurations and allow users to use the same browser to connect to trusted and un-trusted sites alike. In this article, we present detailed steps for remotely hardening multiple web browsers in a Windows-based enterprise, for Internet Explorer and Google Chrome. We hope that system administrators use this guide to jump-start an enterprise-wide strategy for implementing high-granularity and least privilege browser hardening. This will help secure enterprise systems at the front-end in addition to the network perimeter.