Biblio

Data loss is perceived as one of the major threats for cloud storage. Consequently, the security community developed several challenge-response protocols that allow a user to remotely verify whether an outsourced file is still intact. However, two important practical problems have not yet been considered. First, clients commonly outsource multiple files of different sizes, raising the question how to formalize such a scheme and in particular ensuring that all files can be simultaneously audited. Second, in case auditing of the files fails, existing schemes do not provide a client with any method to prove if the original files are still recoverable. We address both problems and describe appropriate solutions. The first problem is tackled by providing a new type of "Proofs of Retrievability" scheme, enabling a client to check all files simultaneously in a compact way. The second problem is solved by defining a novel procedure called "Proofs of Recoverability", enabling a client to obtain an assurance whether a file is recoverable or irreparably damaged. Finally, we present a combination of both schemes allowing the client to check the recoverability of all her original files, thus ensuring cloud storage file recoverability.

Recent architectures for the advanced metering infrastructure (AMI) have incorporated several back-end systems that handle billing and other smart grid control operations. The non-availability of metering data when needed or the untimely delivery of data needed for control operations will undermine the activities of these back-end systems. Unfortunately, there are concerns that cyber attacks such as distributed denial of service (DDoS) will manifest in magnitude and complexity in a smart grid AMI network. Such attacks will range from a delay in the availability of end user's metering data to complete denial in the case of a grounded network. This paper proposes a cloud-based (IaaS) firewall for the mitigation of DDoS attacks in a smart grid AMI network. The proposed firewall has the ability of not only mitigating the effects of DDoS attack but can prevent the attack before they are launched. Our proposed firewall system leverages on cloud computing technology which has an added advantage of reducing the burden of data computations and storage for smart grid AMI back-end systems. The openflow firewall proposed in this study is a better security solution with regards to the traditional on-premises DoS solutions which cannot cope with the wide range of new attacks targeting the smart grid AMI network infrastructure. Simulation results generated from the study show that our model can guarantee the availability of metering/control data and could be used to improve the QoS of the smart grid AMI network under a DDoS attack scenario.

Organizations face the issue of how to best allocate their security resources. Thus, they need an accurate method for assessing how many new vulnerabilities will be reported for the operating systems (OSs) they use in a given time period. Our approach consists of clustering vulnerabilities by leveraging the text information within vulnerability records, and then simulating the mean value function of vulnerabilities by relaxing the monotonic intensity function assumption, which is prevalent among the studies that use software reliability models (SRMs) and nonhomogeneous Poisson process (NHPP) in modeling. We applied our approach to the vulnerabilities of four OSs: Windows, Mac, IOS, and Linux. For the OSs analyzed in terms of curve fitting and prediction capability, our results, compared to a power-law model without clustering issued from a family of SRMs, are more accurate in all cases we analyzed.

In the era of globalized Integrated Circuit (IC) design and manufacturing flow, a rising issue to the silicon industry is various attacks on hardware intellectual property (IP). As a measure to ensure security along the supply chain against IP piracy, tampering and reverse engineering, hardware obfuscation is considered a reliable defense mechanism. Sequential and combinational obfuscations are the primary classes of obfuscation, and multiple methods have been proposed in each type in recent years. This paper presents an overview of obfuscation techniques and a qualitative comparison of the two major types.

In recent years a wide range of wearable IoT healthcare applications have been developed and deployed. The rapid increase in wearable devices allows the transfer of patient personal information between different devices, at the same time personal health and wellness information of patients can be tracked and attacked. There are many techniques that are used for protecting patient information in medical and wearable devices. In this research a comparative study of the complexity for cyber security architecture and its application in IoT healthcare industry has been carried out. The objective of the study is for protecting healthcare industry from cyber attacks focusing on IoT based healthcare devices. The design has been implemented on Xilinx Zynq-7000, targeting XC7Z030 - 3fbg676 FPGA device.

Cloud computing emerged in the last years to handle systems with large-scale services sharing between vast numbers of users. It provides enormous storage for data and computing power to users over the Internet. There are many issues with the high growth of data. Data security is one of the most important issues in cloud computing. There are many algorithms and implementation for data security. These algorithms provided various encryption methods. In this work, We present a comprehensive study between Symmetric key and Asymmetric key encryption algorithms that enhanced data security in cloud computing system. We discuss AES, DES, 3DES and Blowfish for symmetric encryption algorithms, and RSA, DSA, Diffie-Hellman and Elliptic Curve, for asymmetric encryption algorithms.

Power grid operations rely on the trustworthy operation of critical control center functionalities, including the so-called Economic Dispatch (ED) problem. The ED problem is a large-scale optimization problem that is periodically solved by the system operator to ensure the balance of supply and load while maintaining reliability constraints. In this paper, we propose a semantics-based attack generation and implementation approach to study the security of the ED problem.1 Firstly, we generate optimal attack vectors to transmission line ratings to induce maximum congestion in the critical lines, resulting in the violation of capacity limits. We formulate a bilevel optimization problem in which the attacker chooses manipulations of line capacity ratings to maximinimize the percentage line capacity violations under linear power flows. We reformulate the bilevel problem as a mixed integer linear program that can be solved efficiently. Secondly, we describe how the optimal attack vectors can be implemented in commercial energy management systems (EMSs). The attack explores the dynamic memory space of the EMS, and replaces the true line capacity ratings stored in data regions with the optimal attack vectors. In contrast to the well-known false data injection attacks to control systems that require compromising distributed sensors, our approach directly implements attacks to the control center server. Our experimental results on benchmark power systems and five widely utilized EMSs show the practical feasibility of our attack generation and implementation approach.

Power grid operations rely on the trustworthy operation of critical control center functionalities, including the so-called Economic Dispatch (ED) problem. The ED problem is a large-scale optimization problem that is periodically solved by the system operator to ensure the balance of supply and load while maintaining reliability constraints. In this paper, we propose a semantics-based attack generation and implementation approach to study the security of the ED problem.1 Firstly, we generate optimal attack vectors to transmission line ratings to induce maximum congestion in the critical lines, resulting in the violation of capacity limits. We formulate a bilevel optimization problem in which the attacker chooses manipulations of line capacity ratings to maximinimize the percentage line capacity violations under linear power flows. We reformulate the bilevel problem as a mixed integer linear program that can be solved efficiently. Secondly, we describe how the optimal attack vectors can be implemented in commercial energy management systems (EMSs). The attack explores the dynamic memory space of the EMS, and replaces the true line capacity ratings stored in data regions with the optimal attack vectors. In contrast to the well-known false data injection attacks to control systems that require compromising distributed sensors, our approach directly implements attacks to the control center server. Our experimental results on benchmark power systems and five widely utilized EMSs show the practical feasibility of our attack generation and implementation approach.

Verifying the integrity of outsourced data is a classic, well-studied problem. However current techniques have fundamental performance and concurrency limitations for update-heavy workloads. In this paper, we investigate the potential advantages of deferred and batched verification rather than the per-operation verification used in prior work. We present Concerto, a comprehensive key-value store designed around this idea. Using Concerto, we argue that deferred verification preserves the utility of online verification and improves concurrency resulting in orders-of-magnitude performance improvement. On standard benchmarks, the performance of Concerto is within a factor of two when compared to state-of-the-art key-value stores without integrity.

There is no doubt that security issues are on the rise and defense mechanisms are becoming one of the leading subjects for academic and industry experts. In this paper, we focus on the security domain and envision a new way of looking at the security life cycle. We utilize our vision to propose an asset-based approach to countermeasure zero day attacks. To evaluate our proposal, we built a prototype. The initial results are promising and indicate that our prototype will achieve its goal of detecting zero-day attacks.

In Distributed Denial of Service (DDoS) attacks, an attacker tries to disable a service with a flood of seemingly legitimate requests from multiple devices; this is usually accompanied by a sharp spike in the number of distinct IP addresses / flows accessing the system in a short time frame. Hence, the number of distinct elements over sliding windows is a fundamental signal in DDoS identification. Additionally, assessing whether a specific flow has recently accessed the system, known as the Set Membership problem, can help us identify the attacking parties. Here, we show how to extend the functionality of a state of the art algorithm for set membership over a W elements sliding window. We now also support estimation of the distinct flow count, using as little as log2 (W) additional bits.

In this paper, we scrutinize a way through which covert messages are sent and received using the Network Time Protocol (NTP), which is not easily detected since NTP should be present in most environment to synchronize the clock between clients and servers using at least one time server. We also present a proof of concept and investigate the throughput and robustness of this covert channel. This channel will use the 32 bits of fraction of seconds in timestamp to send the covert message. It also uses "Peer Clock Precision" field to track the messages between sender and receiver.

Extracting patterns and deriving insights from spatio-temporal data finds many target applications in various domains, such as in urban planning and computational sustainability. Due to their inherent capability of simultaneously modeling the spatial and temporal aspects of multiple instances, tensors have been successfully used to analyze such spatio-temporal data. However, standard tensor factorization approaches often result in components that are highly overlapping, which hinders the practitioner's ability to interpret them without advanced domain knowledge. In this work, we tackle this challenge by proposing a tensor factorization framework, called CP-ORTHO, to discover distinct and easily-interpretable patterns from multi-modal, spatio-temporal data. We evaluate our approach on real data reflecting taxi drop-off activity. CP-ORTHO provides more distinct and interpretable patterns than prior art, as measured via relevant quantitative metrics, without compromising the solution's accuracy. We observe that CP-ORTHO is fast, in that it achieves this result in 5x less time than the most accurate competing approach.

We present Clio, an information flow control (IFC) system that transparently incorporates cryptography to enforce confidentiality and integrity policies on untrusted storage. Clio insulates developers from explicitly manipulating keys and cryptographic primitives by leveraging the policy language of the IFC system to automatically use the appropriate keys and correct cryptographic operations. We prove that Clio is secure with a novel proof technique that is based on a proof style from cryptography together with standard programming languages results. We present a prototype Clio implementation and a case study that demonstrates Clio's practicality.

Cyber anonymity tools have attracted wide attention in resisting network traffic censorship and surveillance, and have played a crucial role for open communications over the Internet. The Onion Routing (Tor) is considered the prevailing technique for circumventing the traffic surveillance and providing cyber anonymity. Tor operates by tunneling a traffic through a series of relays, making such traffic to appear as if it originated from the last relay in the traffic path, rather than from the original user. However, Tor faced some obstructions in carrying out its goal effectively, such as insufficient performance and limited capacity. This paper presents a cyber anonymity technique based on software-defined networking; named SOR, which builds onion-routed tunnels across multiple anonymity service providers. SOR architecture enables any cloud tenants to participate in the anonymity service via software-defined networking. Our proposed architecture leverages the large capacity and robust connectivity of the commercial cloud networks to elevate the performance of the cyber anonymity service.

In this paper, an industrial testbed is proposed utilizing commercial-off-the-shelf equipment, and it is used to study the weakness of industrial Ethernet, i.e., PROFINET. The investigation is based on observation of the principles of operation of PROFINET and the functionality of industrial control systems.

This brief paper reports on an early stage ongoing PhD project in the field of cyber-physical security in health care critical infrastructures. The research overall aims to develop a methodology that will increase the ability of secure recovery of health critical infrastructures. This ambitious or reckless attempt, as it is currently at an early stage, in this paper, tries to answer why cyber-physical security for health care infrastructures is important and of scientific interest. An initial PhD project methodology and expected outcomes are also discussed. The report concludes with challenges that emerge and possible future directions.

Industrial control systems (ICS) used in industrial plants are vulnerable to cyber-attacks that can cause fatal damage to the plants. Intrusion detection systems (IDSs) monitor ICS network traffic and detect suspicious activities. However, many IDSs overlook sophisticated cyber-attacks because it is hard to make a complete database of cyber-attacks and distinguish operational anomalies when compared to an established baseline. In this paper, a discriminant model between normal and anomalous packets was constructed with a support vector machine (SVM) based on an ICS communication profile, which represents only packet intervals and length, and an IDS with the applied model is proposed. Furthermore, the proposed IDS was evaluated using penetration tests on our cyber security test bed. Although the IDS was constructed by the limited features (intervals and length) of packets, the IDS successfully detected cyber-attacks by monitoring the rate of predicted attacking packets.

The gradual deployment of intelligent and coordinated devices in the electrical power system needs careful investigation of the interactions between the various domains involved. Especially due to the coupling between ICT and power systems a holistic approach for testing and validating is required. Taking existing (quasi-) standardised smart grid system and test specification methods as a starting point, we are developing a holistic testing and validation approach that allows a very flexible way of assessing the system level aspects by various types of experiments (including virtual, real, and mixed lab settings). This paper describes the formal holistic test case specification method and applies it to a particular co-simulation experimental setup. The various building blocks of such a simulation (i.e., FMI, mosaik, domain-specific simulation federates) are covered in more detail. The presented method addresses most modeling and specification challenges in cyber-physical energy systems and is extensible for future additions such as uncertainty quantification.