Biblio

Multimedia authentication is an integral part of multimedia signal processing in many real-time and security sensitive applications, such as video surveillance. In such applications, a full-fledged video digital rights management (DRM) mechanism is not applicable due to the real time requirement and the difficulties in incorporating complicated license/key management strategies. This paper investigates the potential of multimedia authentication from a brand new angle by employing hardware-based security primitives, such as physical unclonable functions (PUFs). We show that the hardware security approach is not only capable of accomplishing the authentication for both the hardware device and the multimedia stream but, more importantly, introduce minimum performance, resource, and power overhead. We justify our approach using a prototype PUF implementation on Xilinx FPGA boards. Our experimental results on the real hardware demonstrate the high security and low overhead in multimedia authentication obtained by using hardware security approaches.

Cyber-attacks are cheap, easy to conduct and often pose little risk in terms of attribution, but their impact could be lasting. The low attribution is because tracing cyber-attacks is primitive in the current network architecture. Moreover, even when attribution is known, the absence of enforcement provisions in international law makes cyber attacks tough to litigate, and hence attribution is hardly a deterrent. Rather than attributing attacks, we can re-look at cyber-attacks as societal events associated with social, political, economic and cultural (SPEC) motivations. Because it is possible to observe SPEC motives on the internet, social media data could be valuable in understanding cyber attacks. In this research, we use sentiment in Twitter posts to observe country-to-country perceptions, and Arbor Networks data to build ground truth of country-to-country DDoS cyber-attacks. Using this dataset, this research makes three important contributions: a) We evaluate the impact of heightened sentiments towards a country on the trend of cyber-attacks received by the country. We find that, for some countries, the probability of attacks increases by up to 27% while experiencing negative sentiments from other nations. b) Using cyber-attacks trend and sentiments trend, we build a decision tree model to find attacks that could be related to extreme sentiments. c) To verify our model, we describe three examples in which cyber-attacks follow increased tension between nations, as perceived in social media.

The extremely rapid development of the Internet of Things brings growing attention to the information security issue. Realization of cryptographically strong pseudo random number generators (PRNGs), is crucial in securing sensitive data. They play an important role in cryptography and in network security applications. In this paper, we realize a comparative study of two pseudo chaotic number generators (PCNGs). The First pseudo chaotic number generator (PCNG1) is based on two nonlinear recursive filters of order one using a Skew Tent map (STmap) and a Piece-Wise Linear Chaotic map (PWLCmap) as non linear functions. The second pseudo chaotic number generator (PCNG2) consists of four coupled chaotic maps, namely: PWLCmaps, STmap, Logistic map by means a binary diffusion matrix [D]. A comparative analysis of the performance in terms of computation time (Generation time, Bit rate and Number of needed cycles to generate one byte) and security of the two PCNGs is carried out.

The purpose of this research is to propose architecture-driven, penetration testing equipped with a software reverse and forward engineering process. Although the importance of architectural risk analysis has been emphasized in software security, no methodology is shown to answer how to discover the architecture and abuse cases of a given insecure legacy system and how to modernize it to a secure target system. For this purpose, we propose an architecture-driven penetration testing methodology: 4+1 architectural views of the given insecure legacy system, documented to discover program paths for vulnerabilities through a reverse engineering process. Then, vulnerabilities are identified by using the discovered architecture abuse cases and countermeasures are proposed on identified vulnerabilities. As a case study, a telecommunication company's Identity Access Management (IAM) system is used for discovering its software architecture, identifying the vulnerabilities of its architecture, and providing possible countermeasures. Our empirical results show that functional suggestions would be relatively easier to follow up and less time-consuming work to fix; however, architectural suggestions would be more complicated to follow up, even though it would guarantee better security and take full advantage of OAuth 2.0 supporting communities.

Information Centric Networking (ICN) paradigms nicely fit the world of wireless sensors, whose devices have tight constraints. In this poster, we compare two alternative designs for secure association of new IoT devices in existing ICN deployments, which are based on asymmetric and symmetric cryptography respectively. While the security properties of both approaches are equivalent, an interesting trade-off arises between properties of the protocol vs properties of its implementation in current IoT boards. Indeed, while the asymmetric-keys based approach incurs a lower traffic overhead (of about 30%), we find that its implementation is significantly more energy- and time-consuming due to the cost of cryptographic operations (it requires up to 41x more energy and 8x more time).

The demand for trained cybersecurity operators is growing more quickly than traditional programs in higher education can fill. At the same time, unemployment for returning military veterans has become a nationally discussed problem. We describe the design and launch of New Skills for a New Fight (NSNF), an intensive, one-year program to train military veterans for the cybersecurity field. This non-traditional program, which leverages experience that veterans gained in military service, includes recruitment and selection, a base of knowledge in the form of four university courses in a simultaneous cohort mode, a period of hands-on cybersecurity training, industry certifications and a practical internship in a Security Operations Center (SOC). Twenty veterans entered this pilot program in January of 2016, and will complete in less than a year's time. Initially funded by a global financial services company, the program provides veterans with an expense-free preparation for an entry-level cybersecurity job.

Instead of developing single-server software system for the powerful computers, the software is turning from large single-server to multi-server system such as distributed system. This change introduces a new challenge for the software quality measurement, since the current software analysis methods for single-server software could not observe and assess the correlation among the components on different nodes. In this paper, a new dynamic cohesion approach is proposed for distributed system. We extend Calling Network model for distributed system by differentiating methods of components deployed on different nodes. Two new cohesion metrics are proposed to describe the correlation at component level, by extending the cohesion metric of single-server software system. The experiments, conducted on a distributed systems-Netflix RSS Reader, present how to trace the various system functions accomplished on three nodes, how to abstract dynamic behaviors using our model among different nodes and how to evaluate the software cohesion on distributed system.

Information-Centric Networking (ICN) is an emerging networking paradigm that focuses on content distribution and aims at replacing the current IP stack. Implementations of ICN have demonstrated its advantages over IP, in terms of network performance and resource requirements. Because of these advantages, ICN is also considered to be a good network paradigm candidate for the Internet-of-Things (IoT), especially in scenarios involving resource constrained devices. In this paper we propose OnboardICNg, the first secure protocol for on-boarding (authenticating and authorizing) IoT devices in ICN mesh networks. OnboardICNg can securely onboard resource constrained devices into an existing IoT network, outperforming the authentication protocol selected for the ZigBee-IP specification: EAP-PANA, i.e., the Protocol for carrying Authentication for Network Access (PANA) combined with the Extensible Authentication Protocol (EAP). In particular we show that, compared with EAP-PANA, OnboardICNg reduces the communication and energy consumption, by 87% and 66%, respectively.

Recent years have witnessed a flourish of hands-on cybersecurity labs and competitions. The information technology (IT) education community has recognized their significant role in boosting students' interest in security and enhancing their security knowledge and skills. Compared to the focus on individual based education materials, much less attention has been paid to the development of tools and materials suitable for team-based security practices, which, however, prevail in real-world environments. One major bottleneck is lack of suitable platforms for this type of practices in IT education community. In this paper, we propose a low-cost, team-oriented cybersecurity practice platform called Platoon. The Platoon platform allows for quickly and automatically creating one or more virtual networks that mimic real-world corporate networks using a regular computer. The virtual environment created by Platoon is suitable for both cybersecurity labs, competitions, and projects. The performance data and user feedback collected from our cyber-defense exercises indicate that Platoon is practical and useful for enhancing students' security learning outcomes.

Friends, family and colleagues at work may repeatedly observe how their peers unlock their smartphones. These "insiders" may combine multiple partial observations to form a hypothesis of a target's secret. This changing landscape requires that we update the methods used to assess the security of unlocking mechanisms against human shoulder surfing attacks. In our paper, we introduce a methodology to study shoulder surfing risks in the insider threat model. Our methodology dissects the authentication process into minimal observations by humans. Further processing is based on simulations. The outcome is an estimate of the number of observations needed to break a mechanism. The flexibility of this approach benefits the design of new mechanisms. We demonstrate the application of our methodology by performing an analysis of the SwiPIN scheme published at CHI 2015. Our results indicate that SwiPIN can be defeated reliably by a majority of the population with as few as 6 to 11 observations.

While the potential advantages of geographic forwarding in wireless sensor networks (WSN) have been demonstrated for a while now, research in applying Information Centric Networking (ICN) has only gained momentum in the last few years. In this paper, we bridge these two worlds by proposing an ICN-compliant and secure implementation of geographic forwarding for ICN. We implement as a proof of concept the Greedy Perimeter Stateless Routing (GPSR) algorithm and compare its performance to that of vanilla ICN forwarding. We also evaluate the cost of security in 802.15.4 networks in terms of energy, memory and CPU footprint. We show that in sparse but large networks, GPSR outperforms vanilla ICN forwarding in both memory footprint and CPU consumption. However, GPSR is more energy intensive because of the cost of communications.

Technological changes bring great efficiencies and opportunities; however, they also bring new threats and dangers that users are often ill prepared to handle. Some individuals have training at work or school while others have family or friends to help them. However, there are few widely known or ubiquitous educational programs to inform and motivate users to develop safe cybersecurity practices. Additionally, little is known about learning strategies in this domain. Understanding how active Internet users have learned their security practices can give insight into more effective learning methods. I surveyed 800 online labor workers to discover their learning processes. They shared how they had to construct their own schema and negotiate meaning in a complex domain. Findings suggest a need to help users build a dynamic mental model of security. Participants recommend encouraging participatory and constructive learning, multi-model dissemination, and ubiquitous opportunities for learning security behaviors.

This panel will discuss and debate what role(s) the information technology discipline should have in cybersecurity. Diverse viewpoints will be considered including current and potential ACM curricular recommendations, current and potential ABET and NSA accreditation criteria, the emerging cybersecurity discipline(s), consideration of government frameworks, the need for a multi-disciplinary approach to cybersecurity, and what aspects of cybersecurity should be under information technology's purview.

Contemporary cloud environments are built on low-assurance components, so they cannot provide a high level of assurance about the isolation and protection of information. A ``multi-level'' secure cloud environment thus typically consists of multiple, isolated clouds, each of which handles data of only one security level. Not only are such environments duplicative and costly, data ``sharing'' must be implemented by massive, wasteful copying of data from low-level domains to high-level domains. The requirements for certifiable, scalable, multi-level cloud security are threefold: 1) To have trusted, high-assurance components available for use in creating a multi-level secure cloud environment; 2) To design a cloud architecture that efficiently uses the high-assurance components in a scalable way, and 3) To compose the secure components within the scalable architecture while still verifiably maintaining the system security properties. This paper introduces a trusted, high-assurance file server and architecture that satisfies all three requirements. The file server is built on mature technology that was previously certified and deployed across domains from TS/SCI to Unclassified and that supports high-performance, low-to-high and high-to-low file sharing with verifiable security.

Zero-day attack is a critical network attack. The zero-day attack period (ZDAP) is the period from the release of malware/exploit until a patch becomes available. IDS/IPS cannot effectively block zero-day attacks because they use pattern-based signatures in general. This paper proposes a Prophetic Defender (PD) by which ZDAP can be minimized. Prior to actual attack, hackers scan networks to identify hosts with vulnerable ports. If this port scanning can be detected early, zero-day attacks will become detectable. PD architecture makes use of a honeypot-based pseudo server deployed to detect malicious port scans. A port-scanning honeypot was operated by us in 6 years from 2009 to 2015. By analyzing the 6-year port-scanning log data, we understand that PD is effective for detecting and blocking zero-day attacks. The block rate of the proposed architecture is 98.5%.

Platform as a Service (PaaS) provides middleware resources to cloud customers. As demand for PaaS services increases, so do concerns about the security of PaaS. This paper discusses principal PaaS security and integrity requirements, and vulnerabilities and the corresponding countermeasures. We consider three core cloud elements: multi-tenancy, isolation, and virtualization and how they relate to PaaS services and security trends and concerns such as user and resource isolation, side-channel vulnerabilities in multi-tenant environments, and protection of sensitive data

The optimal design of a fault-tolerant quantum computer involves finding an appropriate balance between the burden of large-scale integration of noisy components and the load of improving the reliability of hardware technology. This balance can be evaluated by quantitatively modeling the execution of quantum logic operations on a realistic quantum hardware containing limited computational resources. In this work, we report a complete performance simulation software tool capable of (1) searching the hardware design space by varying resource architecture and technology parameters, (2) synthesizing and scheduling a fault-tolerant quantum algorithm within the hardware constraints, (3) quantifying the performance metrics such as the execution time and the failure probability of the algorithm, and (4) analyzing the breakdown of these metrics to highlight the performance bottlenecks and visualizing resource utilization to evaluate the adequacy of the chosen design. Using this tool, we investigate a vast design space for implementing key building blocks of Shor’s algorithm to factor a 1,024-bit number with a baseline budget of 1.5 million qubits. We show that a trapped-ion quantum computer designed with twice as many qubits and one-tenth of the baseline infidelity of the communication channel can factor a 2,048-bit integer in less than 5 months.

The smart grid changes the way energy is produced and distributed. In addition both, energy and information is exchanged bidirectionally among participating parties. Therefore heterogeneous systems have to cooperate effectively in order to achieve a common high-level use case, such as smart metering for billing or demand response for load curtailment. Furthermore, a substantial amount of personal data is often needed for achieving that goal. Capturing and processing personal data in the smart grid increases customer concerns about privacy and in addition, certain statutory and operational requirements regarding privacy aware data processing and storage have to be met. An increase of privacy constraints, however, often limits the operational capabilities of the system. In this paper, we present an approach that automates the process of finding an optimal balance between privacy requirements and operational requirements in a smart grid use case and application scenario. This is achieved by formally describing use cases in an abstract model and by finding an algorithm that determines the optimum balance by forward mapping privacy and operational impacts. For this optimal balancing algorithm both, a numeric approximation and - if feasible - an analytic assessment are presented and investigated. The system is evaluated by applying the tool to a real-world use case from the University of Southern California (USC) microgrid.

This article proposes Probabilistic Replacement Policy (PRP), a novel replacement policy that evicts the line with minimum estimated hit probability under optimal replacement instead of the line with maximum expected reuse distance. The latter is optimal under the independent reference model of programs, which does not hold for last-level caches (LLC). PRP requires 7% and 2% metadata overheads in the cache and DRAM respectively. Using a sampling scheme makes DRAM overhead negligible, with minimal performance impact. Including detailed overhead modeling and equal cache areas, PRP outperforms SHiP, a state-of-the-art LLC replacement algorithm, by 4% for memory-intensive SPEC-CPU2006 benchmarks.

Ever-growing performance of supercomputers nowadays brings demanding requirements of energy efficiency and resilience, due to rapidly expanding size and duration in use of the large-scale computing systems. Many application/architecture-dependent parameters that determine energy efficiency and resilience individually have causal effects with each other, which directly affect the trade-offs among performance, energy efficiency and resilience at scale. To enable high-efficiency management for large-scale High-Performance Computing (HPC) systems nowadays, quantitatively understanding the entangled effects among performance, energy efficiency, and resilience is thus required. While previous work focuses on exploring energy-saving and resilience-enhancing opportunities separately, little has been done to theoretically and empirically investigate the interplay between energy efficiency and resilience at scale. In this article, by extending the Amdahl’s Law and the Karp-Flatt Metric, taking resilience into consideration, we quantitatively model the integrated energy efficiency in terms of performance per Watt and showcase the trade-offs among typical HPC parameters, such as number of cores, frequency/voltage, and failure rates. Experimental results for a wide spectrum of HPC benchmarks on two HPC systems show that the proposed models are accurate in extrapolating resilience-aware performance and energy efficiency, and capable of capturing the interplay among various energy-saving and resilience factors. Moreover, the models can help find the optimal HPC configuration for the highest integrated energy efficiency, in the presence of failures and applied resilience techniques.

The security of Android depends on the timely delivery of updates to fix critical vulnerabilities. In this paper we map the complex network of players in the Android ecosystem who must collaborate to provide updates, and determine that inaction by some manufacturers and network operators means many handsets are vulnerable to critical vulnerabilities. We define the FUM security metric to rank the performance of device manufacturers and network operators, based on their provision of updates and exposure to critical vulnerabilities. Using a corpus of 20 400 devices we show that there is significant variability in the timely delivery of security updates across different device manufacturers and network operators. This provides a comparison point for purchasers and regulators to determine which device manufacturers and network operators provide security updates and which do not. We find that on average 87.7% of Android devices are exposed to at least one of 11 known critical vulnerabilities and, across the ecosystem as a whole, assign a FUM security score of 2.87 out of 10. In our data, Nexus devices do considerably better than average with a score of 5.17; and LG is the best manufacturer with a score of 3.97.

The growth of ICTs and the resulting data explosion could pave the way for the surveillance of our lives and diminish our democratic freedoms, at an unimaginable scale. Consumer mistrust of an organization's ability to safeguard their data is at an all time high and this has negative implications for Big Data. The timing is right to be proactive about designing privacy into technologies, business processes and networked infrastructures. Inclusiveness of all objectives can be achieved through consultation, co-operation, and collaboration (3 C's). If privacy is the default, without diminishing functionality or other legitimate interests, then trust will be preserved and innovation will flourish.

Due to the noise in the images, the edges extracted from these noisy images are always discontinuous and inaccurate by traditional operators. In order to solve these problems, this paper proposes multi-direction edge detection operator to detect edges from noisy images. The new operator is designed by introducing the shear transformation into the traditional operator. On the one hand, the shear transformation can provide a more favorable treatment for directions, which can make the new operator detect edges in different directions and overcome the directional limitation in the traditional operator. On the other hand, all the single pixel edge images in different directions can be fused. In this case, the edge information can complement each other. The experimental results indicate that the new operator is superior to the traditional ones in terms of the effectiveness of edge detection and the ability of noise rejection.

The smart grid aims to improve the efficiency, reliability and safety of the electric system via modern communication system, it's necessary to utilize cloud computing to process and store the data. In fact, it's a promising paradigm to integrate smart grid into cloud computing. However, access to cloud computing system also brings data security issues. This paper focuses on the protection of user privacy in smart meter system based on data combination privacy and trusted third party. The paper demonstrates the security issues for smart grid communication system and cloud computing respectively, and illustrates the security issues for the integration. And we introduce data chunk storage and chunk relationship confusion to protect user privacy. We also propose a chunk information list system for inserting and searching data.

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.