Biblio

Summary & Conclusions: The work described addresses assurance of a planning and execution software system being added to an in-orbit CubeSat to demonstrate autonomous control of that spacecraft. Our focus was on how to develop assurance of the correct operation of the added software in its operational context, our approach to which was to use an assurance case to guide and organize the information involved. The relatively manageable magnitude of the CubeSat and its autonomy demonstration experiment made it plausible to try out our assurance approach in a relatively short timeframe. Additionally, the time was ripe to inject useful assurance results into the ongoing development and testing of the autonomy demonstration. In conducting this, we sought to answer several questions about our assurance approach. The questions, and the conclusions we reached, are as follows: 1. Question: Would our approach to assurance apply to the introduction of a planning and execution software into an existing system? Conclusion: Yes. The use of an assurance case helped focus our attention on the more challenging aspects, notably the interactions between the added software and the existing software system into which it was being introduced. This guided us to choose a hazard analysis method specifically for software interactions. In addition, we were able to automate generation of assurance case elements from the hazard analysis' tabular representation. 2. Question: Would our methods prove understandable to the software engineers tasked with integrating the software into the CubeSat's existing system? Conclusion: Somewhat. In interim discussions with the software engineers we found the assurance case style, of decomposing an argument into smaller pieces, to be useful and understandable to organize discussion. Ultimately however we did not persuade them to adopt assurance cases as the means to present review information. We attribute this to reluctance to deviate from JPL's tried and true style of holding reviews. For the CubeSat project as a whole, hosting an autonomy demonstration was already a novelty. Combining this with presentation of review information via an assurance case, with which our reviewers would be unaccustomed, would have exacerbated the unfamiliarity. 3. Question: Would conducting our methods prove to be compatible with the (limited) time available of the software engineers? Conclusion: Yes. We used a series of six brief meetings (approximately one hour each) with the development team to first identify the interactions as the area on which to focus, and to then perform the hazard analysis on those interactions. We used the meetings to confirm, or correct as necessary, our understanding of the software system and the spacecraft context. Between meetings we studied the existing software documentation, did preliminary analyses by ourselves, and documented the results in a concise form suitable for discussion with the team. 4. Question: Would our methods yield useful results to the software engineers? Conclusion: Yes. The hazard analysis systematically confirmed existing hazards' mitigations, and drew attention to a mitigation whose implementation needed particular care. In some cases, the analysis identified potential hazards - and what to do about them - should some of the more sophisticated capabilities of the planning and execution software be used. These capabilities, not exercised in the initial experiments on the CubeSat, may be used in future experiments. We remain involved with the developers as they prepare for these future experiments, so our analysis results will be of benefit as these proceed.

Cloud security is one of the major issues that worry individuals and organizations about cloud computing. Therefore, defending cloud systems against attacks such asinsiders' attacks has become a key demand. This paper investigates insider threat in cloud relational database systems(cloud RDMS). It discusses some vulnerabilities in cloud computing structures that may enable insiders to launch attacks, and shows how load balancing across multiple availability zones may facilitate insider threat. To prevent such a threat, the paper suggests three models, which are Peer-to-Peer model, Centralized model and Mobile-Knowledgebase model, and addresses the conditions under which they work well.

Insider threats result from legitimate users abusing their privileges, causing tremendous damage or losses. Malicious insiders can be the main threats to an organization. This paper presents an anomaly detection system for detecting insider threat activities in an organization using an ensemble that consists of negative selection algorithms (NSA). The proposed system classifies a selected user activity into either of two classes: "normal" or "malicious." The effectiveness of our proposed detection system is evaluated using case studies from the computer emergency response team (CERT) synthetic insider threat dataset. Our results show that the proposed method is very effective in detecting insider threats.

Insider threat makes great damage to the security of information system, traditional security methods are extremely difficult to work. Insider attack identification plays an important role in insider threat detection. Monitoring user's abnormal behavior is an effective method to detect impersonation, this method is applied to insider threat identification, to built user's behavior attribute information database based on weights changeable feedback tree augmented Bayes network, but data is massive, using the dimensionality reduction based on rough set, to establish the process information model of user's behavior attribute. Using the minimum risk Bayes decision can effectively identify the real identity of the user when user's behavior departs from the characteristic model.

Taking care of security at the cloud is a major issue that needs to be carefully considered and solved for both individuals as well as organizations. Organizations usually expect more trust from employees as well as customers in one hand. On the other hand, cloud users expect their private data is maintained and secured. Although this must be case, however, some malicious outsiders of the cloud as well as malicious insiders who are cloud internal users tend to disclose private data for their malicious uses. Although outsiders of the cloud should be a concern, however, the more serious problems come from Insiders whose malicious actions are more serious and sever. Hence, insiders' threats in the cloud should be the top most problem that needs to be tackled and resolved. This paper aims to find a proper solution for the insider threat problem in the cloud. The paper presents a Mobile Edge Computing (MEC) mitigation model as a solution that suits the specialized nature of this problem where the solution needs to be very close to the place where insiders reside. This in fact gives real-time responses to attack, and hence, reduces the overhead in the cloud.

Substantial portions of attacks on the security of enterprises are perpetrated by Insiders having authorized privileges. Thus insider threat and attack detection is an important aspect of Security management. In the published literature, efforts are on to model the insider threats based on the behavioral traits of employees. The psycho-social behaviors are hard to encode in the software systems. Also, in some cases, there are privacy issues involved. In this paper, the human and non-human agents in a system are described in a novel unified model. The enterprise is described as an automaton and its states are classified secure, safe, unsafe and compromised. The insider agents and threats are modeled on the basis of the automaton and the model is validated using a case study.

Insider attacks is a well-known problem acknowledged as a threat as early as 1980s. The threat is attributed to legitimate users who take advantage of familiarity with the computational environment and abuse their privileges, can easily cause significant damage or losses. In this paper, we present an active defense model and framework of insider threat detection and sense. Firstly, we describe the hierarchical framework which deal with insider threat from several aspects, and subsequently, show a hierarchy-mapping based insider threats model, the kernel of the threats detection, sense and prediction. The experiments show that the model and framework could sense the insider threat in real-time effectively.

This paper explores low cost technical solutions that can help organizations prevent, detect, and respond to insider incidents. Features and functionality associated with insider risk mitigation are presented. A taxonomy for high-level categories of insider threat tools is presented. A discussion of the relationship between the types of tools points out the nuances of insider threat control deployment, and considerations for selecting, implementing, and operating insider threat tools are provided.

The lack of standardization of the terms insider and insider threat has been a noted problem for researchers in the insider threat field. This paper describes the investigation of 42 different definitions of the terms insider and insider threat, with the goal of better understanding the current conceptual model of insider threat and facilitating communication in the research community.

Information Security in cloud storage is a key trepidation with regards to Degree of Trust and Cloud Penetration. Cloud user community needs to ascertain performance and security via QoS. Numerous models have been proposed [2] [3] [6][7] to deal with security concerns. Detection and prevention of insider threats are concerns that also need to be tackled. Since the attacker is aware of sensitive information, threats due to cloud insider is a grave concern. In this paper, we have proposed an authentication mechanism, which performs authentication based on verifying facial features of the cloud user, in addition to username and password, thereby acting as two factor authentication. New QoS has been proposed which is capable of monitoring and detection of insider threats using Machine Learning Techniques. KNN Classification Algorithm has been used to classify users into legitimate, possibly legitimate, possibly not legitimate and not legitimate groups to verify image authenticity to conclude, whether there is any possible insider threat. A threat detection model has also been proposed for insider threats, which utilizes Facial recognition and Monitoring models. Security Method put forth in [6] [7] is honed to include threat detection QoS to earn higher degree of trust from cloud user community. As a recommendation, Threat detection module should be harnessed in private cloud deployments like Defense and Pharma applications. Experimentation has been conducted using open source Machine Learning libraries and results have been attached in this paper.

This paper describes results of a study seeking to identify observable events related to insider sabotage. We collected information from actual insider threat cases, created chronological timelines of the incidents, identified key points in each timeline such as when attack planning began, measured the time between key events, and looked for specific observable events or patterns that insiders held in common that may indicate insider sabotage is imminent or likely. Such indicators could be used by security experts to potentially identify malicious activity at or before the time of attack. Our process included critical steps such as identifying the point of damage to the organization as well as any malicious events prior to zero hour that enabled the attack but did not immediately cause harm. We found that nearly 71% of the cases we studied had either no observable malicious action prior to attack, or had one that occurred less than one day prior to attack. Most of the events observed prior to attack were behavioral, not technical, especially those occurring earlier in the case timelines. Of the observed technical events prior to attack, nearly one third involved installation of software onto the victim organizations IT systems.

The information-theoretic approach to security entails harnessing the correlated randomness available in nature to establish security. It uses tools from information theory and coding and yields provable security, even against an adversary with unbounded computational power. However, the feasibility of this approach in practice depends on the development of efficiently implementable schemes. In this paper, we review a special class of practical schemes for information-theoretic security that are based on 2-universal hash families. Specific cases of secret key agreement and wiretap coding are considered, and general themes are identified. The scheme presented for wiretap coding is modular and can be implemented easily by including an extra preprocessing layer over the existing transmission codes.

In this paper, a wireless multicast scenario is considered in which the transmitter sends a common message to a group of client receivers through quasi-static Rayleigh fading channel in the presence of an eavesdropper. The communication between transmitter and each client receiver is said to be secured if the eavesdropper is unable to decode any information. On the basis of an information-theoretic formulation of the confidential communications between transmitter and a group of client receivers, we define the expected secrecy sum-mutual information in terms of secure outage probability and provide a complete characterization of maximum transmission rate at which the eavesdropper is unable to decode any information. Moreover, we find the probability of non-zero secrecy mutual information and present an analytical expression for ergodic secrecy multicast mutual information of the proposed model.

Infrastructural systems such as the electricity grid, healthcare, and transportation networks today rely increasingly on the joint functioning of networked information systems and physical components, in short, on cyber-physical architectures. Despite tremendous advances in cryptography, physical-layer security and authentication, information attacks, both passive such as eavesdropping, and active such as unauthorized data injection, continue to thwart the reliable functioning of networked systems. In systems with joint cyber-physical functionality, the ability of an adversary to monitor transmitted information or introduce false information can lead to sensitive user data being leaked or result in critical damages to the underlying physical system. This paper investigates two broad challenges in information security in cyber-physical systems (CPSs): preventing retrieval of internal physical system information through monitored external cyber flows, and limiting the modification of physical system functioning through compromised cyber flows. A rigorous analytical framework grounded on information-theoretic security is developed to study these challenges in a general stochastic control system abstraction-a theoretical building block for CPSs-with the objectives of quantifying the fundamental tradeoffs between information security and physical system performance, and through the process, designing provably secure controller policies. Recent results are presented that establish the theoretical basis for the framework, in addition to practical applications in timing analysis of anonymous systems, and demand response systems in a smart electricity grid.

Many important security informatics problems require consideration of dynamical phenomena for their solution; examples include predicting the behavior of individuals in social networks and distinguishing malicious and innocent computer network activities based on activity traces. While information theory offers powerful tools for analyzing dynamical processes, to date the application of information-theoretic methods in security domains has focused on static analyses (e.g., cryptography, natural language processing). This paper leverages information-theoretic concepts and measures to quantify the similarity of pairs of stochastic dynamical systems, and shows that this capability can be used to solve important problems which arise in security applications. We begin by presenting a concise review of the information theory required for our development, and then address two challenging tasks: 1.) characterizing the way influence propagates through social networks, and 2.) distinguishing malware from legitimate software based on the instruction sequences of the disassembled programs. In each application, case studies involving real-world datasets demonstrate that the proposed techniques outperform standard methods.

Quantitative analysis of security properties in wireless communication systems is an important issue; it helps us get a comprehensive view of security and can be used to compare the security performance of different systems. This paper analyzes the security of future wireless communication system from an information-theoretic point of view and proposes an overall security metric. We demonstrate that the proposed metric is more reasonable than some existing metrics and it is highly sensitive to some basic parameters and helpful to do fine-grained tuning of security performance.

To contest the rapidly developing cyber-attacks, numerous collaborative security schemes, in which multiple security entities can exchange their observations and other relevant data to achieve more effective security decisions, are proposed and developed in the literature. However, the security-related information shared among the security entities may contain some sensitive information and such information exchange can raise privacy concerns, especially when these entities belong to different organizations. With such consideration, the interplay between the attacker and the collaborative entities is formulated as Quantitative Information Flow (QIF) games, in which the QIF theory is adapted to measure the collaboration gain and the privacy loss of the entities in the information sharing process. In particular, three games are considered, each corresponding to one possible scenario of interest in practice. Based on the game-theoretic analysis, the expected behaviors of both the attacker and the security entities are obtained. In addition, the simulation results are presented to validate the analysis.

We investigate the potential of an information-spectrum approach to information-theoretic security. We show how this approach provides conceptually simple yet powerful results that can be used to investigate complex communication scenarios. In particular, we illustrate the usefulness of information-spectrum methods by analyzing the effect of channel state information (CSI) on the secure rates achievable over wiretap channels. We establish a formula for secrecy capacity, which we then specialize to compute achievable rates for ergodic fading channels in the presence of imperfect CSI. Our results confirm the importance of having some knowledge about the eavesdropper's channel, but also show that imperfect CSI does not necessarily preclude security.

This paper considers the transmission of confidential data over wireless channels. Based on an information-theoretic formulation of the problem, in which two legitimates partners communicate over a quasi-static fading channel and an eavesdropper observes their transmissions through a second independent quasi-static fading channel, the important role of fading is characterized in terms of average secure communication rates and outage probability. Based on the insights from this analysis, a practical secure communication protocol is developed, which uses a four-step procedure to ensure wireless information-theoretic security: (i) common randomness via opportunistic transmission, (ii) message reconciliation, (iii) common key generation via privacy amplification, and (iv) message protection with a secret key. A reconciliation procedure based on multilevel coding and optimized low-density parity-check (LDPC) codes is introduced, which allows to achieve communication rates close to the fundamental security limits in several relevant instances. Finally, a set of metrics for assessing average secure key generation rates is established, and it is shown that the protocol is effective in secure key renewal-even in the presence of imperfect channel state information.

In this paper we consider the pollution attack in network coded systems where network nodes are computationally limited. We consider the combined use of cryptographic signature based security and information theoretic network error correction and propose a fountain-like network error correction code construction suitable for this purpose.

While information-theoretic security is stronger than computational security, it has long been considered impractical. In this work, we provide new insights into the design of practical information-theoretic cryptosystems. Firstly, from a theoretical point of view, we give a brief introduction into the existing information theoretic security criteria, such as the notions of Shannon's perfect/ideal secrecy in cryptography, and the concept of strong secrecy in coding theory. Secondly, from a practical point of view, we propose the concept of ideal secrecy outage and define a outage probability. Finally, we show how such probability can be made arbitrarily small in a practical cryptosystem.

Summary form only given. We discuss information-theoretic methods to prove the security of cryptosystems. We study what is called, unconditionally secure (or information-theoretically secure) cryptographic schemes in search for a system that can provide long-term security and that does not impose limits on the adversary's computational power.

This paper analyzes the formalizations of information-theoretic security for the fundamental primitives in cryptography: symmetric-key encryption and key agreement. Revisiting the previous results, we can formalize information-theoretic security using different methods, by extending Shannon's perfect secrecy, by information-theoretic analogues of indistinguishability and semantic security, and by the frameworks for composability of protocols. We show the relationships among the security formalizations and obtain the following results. First, in the case of encryption, there are significant gaps among the formalizations, and a certain type of relaxed perfect secrecy or a variant of information-theoretic indistinguishability is the strongest notion. Second, in the case of key agreement, there are significant gaps among the formalizations, and a certain type of relaxed perfect secrecy is the strongest notion. In particular, in both encryption and key agreement, the formalization of composable security is not stronger than any other formalizations. Furthermore, as an application of the relationships in encryption and key agreement, we simultaneously derive a family of lower bounds on the size of secret keys and security quantities required under the above formalizations, which also implies the importance and usefulness of the relationships.

This paper studies Wireless Information-Theoretic Security for low-speed mobility in autonomic networks. More specifically, the impact of user movement on the Probability of Non-Zero Secrecy Capacity and Outage Secrecy Capacity for different channel conditions has been investigated. This is accomplished by establishing a link between different user locations and the boundaries of information-theoretic secure communication. Human mobility scenarios are considered, and its impact on physical layer security is examined, considering quasi-static Rayleigh channels for the fading phenomena. Simulation results have shown that the Secrecy Capacity depends on the relative distance of legitimate and illegitimate (eavesdropper) users in reference to the given transmitter.

In the past, two main approaches for the purpose of authentication, including information-theoretic authentication codes and complexity-theoretic message authentication codes (MACs), were almost independently developed. In this paper, we consider to construct new MACs, which are both computationally secure and information-theoretically secure. Essentially, we propose a new cryptographic primitive, namely, artificial-noise-aided MACs (ANA-MACs), where artificial noise is used to interfere with the complexity-theoretic MACs and quantization is further employed to facilitate packet-based transmission. With a channel coding formulation of key recovery in the MACs, the generation of standard authentication tags can be seen as an encoding process for the ensemble of codes, where the shared key between Alice and Bob is considered as the input and the message is used to specify a code from the ensemble of codes. Then, we show that artificial noise in ANA-MACs can be well employed to resist the key recovery attack even if the opponent has an unlimited computing power. Finally, a pragmatic approach for the analysis of ANA-MACs is provided, and we show how to balance the three performance metrics, including the completeness error, the false acceptance probability, and the conditional equivocation about the key. The analysis can be well applied to a class of ANA-MACs, where MACs with Rijndael cipher are employed.