Biblio

Security is playing a very important and crucial role in the field of network communication system and Internet. Kerberos Authentication Protocol is designed and developed by Massachusetts Institute of Technology (MIT) and it provides authentication by encrypting information and allow clients to access servers in a secure manner. This paper describes the design and implementation of Kerberos using Data Encryption Standard (DES). Data encryption standard (DES) is a private key cryptography system that provides the security in the communication system. Java Development Tool Kit as the front end and ms access as the back end are used for implementation.

Accelerated Processing Unit (APU) is a heterogeneous multicore processor that contains general-purpose CPU cores and a GPU in a single chip. It also supports Heterogeneous System Architecture (HSA) that provides coherent physically-shared memory between the CPU and the GPU. In this paper, we present the design and implementation of a high-performance IPsec gateway using a low-cost commodity embedded APU. The HSA supported by the APUs eliminates the data copy overhead between the CPU and the GPU, which is unavoidable in the previous discrete GPU approaches. The gateway is implemented in OpenCL to exploit the GPU and uses zero-copy packet I/O APIs in DPDK. The IPsec gateway handles the real-world network traffic where each packet has a different workload. The proposed packet scheduling algorithm significantly improves GPU utilization for such traffic. It works not only for APUs but also for discrete GPUs. With three CPU cores and one GPU in the APU, the IPsec gateway achieves a throughput of 10.36 Gbps with an average latency of 2.79 ms to perform AES-CBC+HMAC-SHA1 for incoming packets of 1024 bytes.

Developers and academics are constantly seeking to increase the speed and security of operating systems. Unfortunately, an increase in either one often comes at the cost of the other. In this paper, we present an operating system design that challenges a long-held tenet of multicore operating systems in order to produce an alternative architecture that has the potential to deliver both increased security and faster performance. In particular, we propose decoupling the operating system kernel from user processes by running each on completely separate processor cores instead of at different privilege levels within shared cores. Without using the hardware's privilege modes, virtualization and virtual memory contexts enforce the security policies necessary to maintain process isolation and protection. Our new kernel design paradigm offers the opportunity to simultaneously increase both performance and security; utilizing the hardware facilities for inter-core communication in place of those for privilege mode switching offers the opportunity for increased system call performance, while the hard separation between user processes and the kernel provides several strong security properties.

We introduce a system-level Simulation and Analysis Engine (SAE) framework based on dynamic binary instrumentation for fine-grained and customizable instruction-level introspection of everything that executes on the processor. SAE can instrument the BIOS, kernel, drivers, and user processes. It can also instrument multiple systems simultaneously using a single instrumentation interface, which is essential for studying scale-out applications. SAE is an x86 instruction set simulator designed specifically to enable rapid prototyping, evaluation, and validation of architectural extensions and program analysis tools using its flexible APIs. It is fast enough to execute full platform workloads–-a modern operating system can boot in a few minutes–-thus enabling research, evaluation, and validation of complex functionalities related to multicore configurations, virtualization, security, and more. To reach high speeds, SAE couples tightly with a virtual platform and employs both a just-in-time (JIT) compiler that helps simulate simple instructions efficiently and a fast interpreter for simulating new or complex instructions. We describe SAE's architecture and instrumentation engine design and show the framework's usefulness for single- and multi-system architectural and program analysis studies.

Modern multicore processors feature easily accessible temperature sensors that provide useful information for dynamic thermal management. These sensors were recently shown to be a potential security threat, since otherwise isolated applications can exploit them to establish a thermal covert channel and leak restricted information. Previous research showed experiments that document the feasibility of (low-rate) communication over this channel, but did not further analyze its fundamental characteristics. For this reason, the important questions of quantifying the channel capacity and achievable rates remain unanswered. To address these questions, we devise and exploit a new methodology that leverages both theoretical results from information theory and experimental data to study these thermal covert channels on modern multicores. We use spectral techniques to analyze data from two representative platforms and estimate the capacity of the channels from a source application to temperature sensors on the same or different cores. We estimate the capacity to be in the order of 300 bits per second (bps) for the same-core channel, i.e., when reading the temperature on the same core where the source application runs, and in the order of 50 bps for the 1-hop channel, i.e., when reading the temperature of the core physically next to the one where the source application runs. Moreover, we show a communication scheme that achieves rates of more than 45 bps on the same-core channel and more than 5 bps on the 1-hop channel, with less than 1% error probability. The highest rate shown in previous work was 1.33 bps on the 1-hop channel with 11% error probability.

Computed Tomography (CT) Image Reconstruction is an important technique used in a wide range of applications, ranging from explosive detection, medical imaging to scientific imaging. Among available reconstruction methods, Model Based Iterative Reconstruction (MBIR) produces higher quality images and allows for the use of more general CT scanner geometries than is possible with more commonly used methods. The high computational cost of MBIR, however, often makes it impractical in applications for which it would otherwise be ideal. This paper describes a new MBIR implementation that significantly reduces the computational cost of MBIR while retaining its benefits. It describes a novel organization of the scanner data into super-voxels (SV) that, combined with a super-voxel buffer (SVB), dramatically increase locality and prefetching, enable parallelism across SVs and lead to an average speedup of 187 on 20 cores.

Defense-in-depth is an important security architecture principle that has significant application to industrial control systems (ICS), cloud services, storehouses of sensitive data, and many other areas. We claim that an ideal defense-in-depth posture is 'deep', containing many layers of security, and 'narrow', the number of node independent attack paths is minimized. Unfortunately, accurately calculating both depth and width is difficult using standard graph algorithms because of a lack of independence between multiple vulnerability instances (i.e., if an attacker can penetrate a particular vulnerability on one host then they can likely penetrate the same vulnerability on another host). To address this, we represent known weaknesses and vulnerabilities as a type of colored attack graph. We measure depth and width through solving the shortest color path and minimum color cut problems. We prove both of these to be NP-Hard and thus for our solution we provide a suite of greedy heuristics. We then empirically apply our approach to large randomly generated networks as well as to ICS networks generated from a published ICS attack template. Lastly, we discuss how to use these results to help guide improvements to defense-in-depth postures.

Intel SGX is the latest processor architecture promising secure code execution despite large, complex and hence potentially vulnerable legacy operating systems (OSs). However, two recent works identified vulnerabilities that allow an untrusted management OS to extract secret information from Intel SGX's enclaves, and to violate their integrity by exploiting concurrency bugs. In this work, we re-investigate delayed preemption (DP) in the context of Intel SGX. DP is a mechanism originally proposed for L4-family microkernels as disable-interrupt replacement. Recapitulating earlier results on language-based information-flow security, we illustrate the construction of leakage-free code for enclaves. However, as long as adversaries have fine-grained control over preemption timing, these solutions are impractical from a performance/complexity perspective. To overcome this, we resort to delayed preemption, and sketch a software implementation for hypervisors providing enclaves as well as a hardware extension for systems like SGX. Finally, we illustrate how static analyses for SGX may be extended to check confidentiality of preemption-delaying programs.

This paper presents general techniques for verifying virtually synchronous distributed control systems with interconnected physical environments. Such cyber-physical systems (CPSs) are notoriously hard to verify, due to their combination of nontrivial continuous dynamics, network delays, imprecise local clocks, asynchronous communication, etc. To simplify their analysis, we first extend the PALS methodology–-that allows to abstract from the timing of events, asynchronous communication, network delays, and imprecise clocks, as long as the infrastructure guarantees bounds on the network delays and clock skews–-from real-time to hybrid systems. We prove a bisimulation equivalence between Hybrid PALS synchronous and asynchronous models. We then show how various verification problems for synchronous Hybrid PALS models can be reduced to SMT solving over nonlinear theories of the real numbers. We illustrate the Hybrid PALS modeling and verification methodology on a number of CPSs, including a control system for turning an airplane.

Software-defined networking (SDN) programs must simultaneously describe static forwarding behavior and dynamic updates in response to events. Event-driven updates are critical to get right, but difficult to implement correctly due to the high degree of concurrency in networks. Existing SDN platforms offer weak guarantees that can break application invariants, leading to problems such as dropped packets, degraded performance, security violations, etc. This paper introduces EVENT-DRIVEN CONSISTENT UPDATES that are guaranteed to preserve well-defined behaviors when transitioning between configurations in response to events. We propose NETWORK EVENT STRUCTURES (NESs) to model constraints on updates, such as which events can be enabled simultaneously and causal dependencies between events. We define an extension of the NetKAT language with mutable state, give semantics to stateful programs using NESs, and discuss provably-correct strategies for implementing NESs in SDNs. Finally, we evaluate our approach empirically, demonstrating that it gives well-defined consistency guarantees while avoiding expensive synchronization and packet buffering.

This paper addresses the problem of distributed multi-agent optimization in which each agent i has a local cost function hi(x), and the goal is to optimize a global cost function that aggregates the local cost functions. Such optimization problems are of interest in many contexts, including distributed machine learning, distributed resource allocation, and distributed robotics. We consider the distributed optimization problem in the presence of faulty agents. We focus primarily on Byzantine failures, but also briey discuss some results for crash failures. For the Byzantine fault-tolerant optimization problem, the ideal goal is to optimize the average of local cost functions of the non-faulty agents. However, this goal also cannot be achieved. Therefore, we consider a relaxed version of the fault-tolerant optimization problem. The goal for the relaxed problem is to generate an output that is an optimum of a global cost function formed as a convex combination of local cost functions of the non-faulty agents. More precisely, there must exist weights αi for i∈N such that αi ≥ 0 and ∑i≥ Nαi=1, and the output is an optimum of the cost function ∑i≥ N αihi(x). Ideally, we would like αi=1/textbarNtextbar for all i≥ N, however, this cannot be guaranteed due to the presence of faulty agents. In fact, the maximum number of nonzero weights (αi's) that can be guaranteed is textbarNtextbar-f, where f is the maximum number of Byzantine faulty agents. We present an iterative distributed algorithm that achieves optimal fault-tolerance. Specifically, it ensures that at least textbarNtextbar-f agents have weights that are bounded away from 0 (in particular, lower bounded by 1/2textbarNtextbar-f\vphantom\\). The proposed distributed algorithm has a simple iterative structure, with each agent maintaining only a small amount of local state. We show that the iterative algorithm ensures two properties as time goes to ∞: consensus (i.e., output of non-faulty agents becomes identical in the time limit), and optimality (in the sense that the output is the optimum of a suitably defined global cost function).

In today's multicore processors, the last-level cache is often shared by multiple concurrently running processes to make efficient use of hardware resources. However, previous studies have shown that a shared cache is vulnerable to timing channel attacks that leak confidential information from one process to another. Static cache partitioning can eliminate the cache timing channels but incurs significant performance overhead. In this paper, we propose Secure Dynamic Cache Partitioning (SecDCP), a partitioning technique that defeats cache timing channel attacks. The SecDCP scheme changes the size of cache partitions at run time for better performance while preventing insecure information leakage between processes. For cache-sensitive multiprogram workloads, our experimental results show that SecDCP improves performance by up to 43% and by an average of 12.5% over static cache partitioning.

Causality inference, such as dynamic taint anslysis, has many applications (e.g., information leak detection). It determines whether an event e is causally dependent on a preceding event c during execution. We develop a new causality inference engine LDX. Given an execution, it spawns a slave execution, in which it mutates c and observes whether any change is induced at e. To preclude non-determinism, LDX couples the executions by sharing syscall outcomes. To handle path differences induced by the perturbation, we develop a novel on-the-fly execution alignment scheme that maintains a counter to reflect the progress of execution. The scheme relies on program analysis and compiler transformation. LDX can effectively detect information leak and security attacks with an average overhead of 6.08% while running the master and the slave concurrently on separate CPUs, much lower than existing systems that require instruction level monitoring. Furthermore, it has much better accuracy in causality inference.

Cryptographic systems are vulnerable to random errors and injected faults. Soft errors can inadvertently happen in critical cryptographic modules and attackers can inject faults into systems to retrieve the embedded secret. Different schemes have been developed to improve the security and reliability of cryptographic systems. As the new SHA-3 standard, Keccak algorithm will be widely used in various cryptographic applications, and its implementation should be protected against random errors and injected faults. In this paper, we devise different parity checking methods to protect the operations of Keccak. Results show that our schemes can be easily implemented and can effectively protect Keccak system against random errors and fault attacks.

Failing to properly isolate components in the same address space has resulted in a substantial amount of vulnerabilities. Enforcing the least privilege principle for memory accesses can selectively isolate software components to restrict attack surface and prevent unintended cross-component memory corruption. However, the boundaries and interactions between software components are hard to reason about and existing approaches have failed to stop attackers from exploiting vulnerabilities caused by poor isolation. We present the secure memory views (SMV) model: a practical and efficient model for secure and selective memory isolation in monolithic multithreaded applications. SMV is a third generation privilege separation technique that offers explicit access control of memory and allows concurrent threads within the same process to partially share or fully isolate their memory space in a controlled and parallel manner following application requirements. An evaluation of our prototype in the Linux kernel (TCB textless 1,800 LOC) shows negligible runtime performance overhead in real-world applications including Cherokee web server (textless 0.69%), Apache httpd web server (textless 0.93%), and Mozilla Firefox web browser (textless 1.89%) with at most 12 LOC changes.

Cameras have become nearly ubiquitous with the rise of smartphones and laptops. New wearable devices, such as Google Glass, focus directly on using live video data to enable augmented reality and contextually enabled services. However, granting applications full access to video data exposes more information than is necessary for their functionality, introducing privacy risks. We propose a privilege-separation architecture for visual recognizer applications that encourages modularization and least privilege–-separating the recognizer logic, sandboxing it to restrict filesystem and network access, and restricting what it can extract from the raw video data. We designed and implemented a prototype that separates the recognizer and application modules and evaluated our architecture on a set of 17 computer-vision applications. Our experiments show that our prototype incurs low overhead for each of these applications, reduces some of the privacy risks associated with these applications, and in some cases can actually increase the performance due to increased parallelism and concurrency.

TLS and SSH are two of the most commonly used protocols for securing Internet traffic. Many of the implementations of these protocols rely on the cryptographic primitives provided in the OpenSSL library. In this work we disclose a vulnerability in OpenSSL, affecting all versions and forks (e.g. LibreSSL and BoringSSL) since roughly October 2005, which renders the implementation of the DSA signature scheme vulnerable to cache-based side-channel attacks. Exploiting the software defect, we demonstrate the first published cache-based key-recovery attack on these protocols: 260 SSH-2 handshakes to extract a 1024/160-bit DSA host key from an OpenSSH server, and 580 TLS 1.2 handshakes to extract a 2048/256-bit DSA key from an stunnel server.

The Physical Web is a project announced by Google's Chrome team that essentially provides a framework to discover "smart" physical objects (e.g. vending machines, classroom, conference room, cafeteria etc.) and interact with specific, contextual content without having to resort to downloading a specific app. A common app such as the open source and freely available Physical Web app on the Google Play Store or the BKON Browser on the Apple App Store, can access nearby beacons. A current work-in-progress at the University of Maui College is developing a campus-wide prototype of beacon technology using Eddystone-URL and EID protocol from various beacon vendors.

Wearable tracking devices have gained widespread usage and popularity because of the valuable services they offer, monitoring human's health parameters and, in general, assisting persons to take a better care of themselves. Nevertheless, the security risks associated with such devices can represent a concern among consumers, because of the sensitive information these devices deal with, like sleeping patterns, eating habits, heart rate and so on. In this paper, we analyse the key security and privacy features of two entry level health trackers from leading vendors (Jawbone and Fitbit), exploring possible attack vectors and vulnerabilities at several system levels. The results of the analysis show how these devices are vulnerable to several attacks (perpetrated with consumer-level devices equipped with just bluetooth and Wi-Fi) that can compromise users' data privacy and security, and eventually call the tracker vendors to raise the stakes against such attacks.

Cloud storage services such as Dropbox [1] and Google Drive [2] are becoming more and more popular. On the one hand, they provide users with mobility, scalability, and convenience. However, privacy issues arise when the storage becomes not fully controlled by users. Although modern encryption schemes are effective at protecting content of data, there are two drawbacks of the encryption-before-outsourcing approach: First, one kind of sensitive information, Access Pattern of the data is left unprotected. Moreover, encryption usually makes the data difficult to use. In this paper, we propose AIS (Access Indistinguishable Storage), the first client-side system that can partially conceal access pattern of the cloud storage in constant time. Besides data content, AIS can conceal information about the number of initial files, and length of each initial file. When it comes to the access phase after initiation, AIS can effectively conceal the behavior (read or write) and target file of the current access. Moreover, the existence and length of each file will remain confidential as long as there is no access after initiation. One application of AIS is SSE (Searchable Symmetric Encryption), which makes the encrypted data searchable. Based on AIS, we propose SBA (SSE Built on AIS). To the best of our knowledge, SBA is safer than any other SSE systems of the same complexity, and SBA is the first to conceal whether current keyword was queried before, the first to conceal whether current operation is an addition or deletion, and the first to support direct modification of files.

In this work, we give a lattice attack on the ECDSA implementation in the latest version of OpenSSL, which implement the scalar multiplication by windowed Non-Adjacent Form method. We propose a totally different but more efficient method of extracting and utilizing information from the side-channel results, remarkably improving the previous attacks. First, we develop a new efficient method, which can extract almost all information from the side-channel results, obtaining 105.8 bits of information per signature on average for 256-bit ECDSA. Then in order to make the utmost of our extracted information, we translate the problem of recovering secret key to the Extended Hidden Number Problem, which can be solved by lattice reduction algorithms. Finally, we introduce the methods of elimination, merging, most significant digit recovering and enumeration to improve the attack. Our attack is mounted to the \series secp256k1\ curve, and the result shows that only 4 signatures would be enough to recover the secret key if the Flush+Reload attack is implemented perfectly without any error,which is much better than the best known result needing at least 13 signatures.

Evolutionary Computation (EC) has been used with great success on various real-world problems. One domain abundant with numerous difficult problems is cryptology. Cryptology can be divided into cryptography, that informally speaking considers methods how to ensure secrecy (but also authenticity, privacy, etc.), and cryptanalysis, that deals with methods how to break cryptographic systems. Although not always in an obvious way, EC can be applied to problems from both domains. This tutorial will first give a brief introduction to cryptology intended for general audience (therefore, omitting proofs and mathematics behind many concepts). Afterwards, we concentrate on several topics from cryptography that are successfully tackled up to now with EC and discuss why those topics are suitable to apply EC. However, care must be taken since there exists a number of problems that seem to be impossible to solve with EC and one needs to realize the limitations of the heuristics. We will discuss the choice of appropriate EC techniques (GA, GP, CGP, ES, multi-objective optimization, etc) for various problems and evaluate on the importance of that choice. Furthermore, we will discuss the gap between the cryptographic community and EC community and what does that mean for the results. By doing that, we will give a special emphasis on the perspective that cryptography presents a source of benchmark problems for the EC community. To conclude, we will present a number of topics we consider to be a strong research choice that can have a real-world impact. In that part, we give a special attention to cryptographic problems where cryptographic community successfully applied EC, but where those problems remained out of the focus of EC community. This tutorial will also present some live demos of EC in action when dealing with cryptographic problems. We will present several problems, ways of encoding solutions, impact of the algorithms choice and finally, we will run some experiments to show the results and discuss how to assess them from cryptographic perspective.

A program subject to a Return-Oriented Programming (ROP) attack usually presents an execution trace with a high frequency of indirect branches. From this observation, several researchers have proposed to monitor the density of these instructions to detect ROP attacks. These techniques use universal thresholds: the density of indirect branches that characterizes an attack is the same for every application. This paper shows that universal thresholds are easy to circumvent. As an alternative, we introduce an inter-procedural semi-context-sensitive static code analysis that estimates the maximum density of indirect branches possible for a program. This analysis determines detection thresholds for each application; thus, making it more difficult for attackers to compromise programs via ROP. We have used an implementation of our technique in LLVM to find specific thresholds for the programs in SPEC CPU2006. By comparing these thresholds against actual execution traces of corresponding programs, we demonstrate the accuracy of our approach. Furthermore, our algorithm is practical: it finds an approximate solution to a theoretically undecidable problem, and handles programs with up to 700 thousand assembly instructions in 25 minutes.

Recommender systems have become quite popular recently. However, such systems are vulnerable to several types of attacks that target user ratings. One such attack is the Sybil attack where an entity masquerades as several identities with the intention of diverting user ratings. In this work, we propose evolutionary game theory as a possible solution to the Sybil attack in recommender systems. After modeling the attack, we use replicator dynamics to solve for evolutionary stable strategies. Our results show that under certain conditions that are easily achievable by a system administrator, the probability of an attack strategy drops to zero implying degraded fitness for Sybil nodes that eventually die out.

Sybil attacks, in which an adversary creates a large number of identities, present a formidable problem for the robustness of recommendation systems. One promising method of sybil detection is to use data from social network ties to implicitly infer trust. Previous work along this dimension typically a) assumes that it is difficult/costly for an adversary to create edges to honest nodes in the network; and b) limits the amount of damage done per such edge, using conductance-based methods. However, these methods fail to detect a simple class of sybil attacks which have been identified in online systems. Indeed, conductance-based methods seem inherently unable to do so, as they are based on the assumption that creating many edges to honest nodes is difficult, which seems to fail in real-world settings. We create a sybil defense system that accounts for the adversary's ability to launch such attacks yet provably withstands them by: Notassuminganyrestrictiononthenumberofedgesanadversarycanform,butinsteadmakingamuch weaker assumption that creating edges from sybils to most honest nodes is difficult, yet allowing that the remaining nodes can be freely connected to. Relaxing the goal from classifying all nodes as honest or sybil to the goal of classifying the "core" nodes of the network as honest; and classifying no sybil nodes as honest. Exploiting a new, for sybil detection, social network property, namely, that nodes can be embedded in low-dimensional spaces.