Biblio

A number of small Open Source projects let independent providers measure different aspects of their quality that would otherwise be hard to see. This paper describes this observation as the pattern Quality Attestation. Quality Attestation belongs to a family of Open Source patterns written by various authors.

Scientific advancement is fueled by solid fundamental research, followed by replication, meta-analysis, and theory building. To support such advancement, researchers and government agencies have been working towards a "science of security". As in other sciences, security science requires high-quality fundamental research addressing important problems and reporting approaches that capture the information necessary for replication, meta-analysis, and theory building. The goal of this paper is to aid security researchers in establishing a baseline of the state of scientific reporting in security through an analysis of indicators of scientific research as reported in top security conferences, specifically the 2015 ACM CCS and 2016 IEEE S&P proceedings. To conduct this analysis, we employed a series of rubrics to analyze the completeness of information reported in papers relative to the type of evaluation used (e.g. empirical study, proof, discussion). Our findings indicated some important information is often missing from papers, including explicit documentation of research objectives and the threats to validity. Our findings show a relatively small number of replications reported in the literature. We hope that this initial analysis will serve as a baseline against which we can measure the advancement of the science of security.

We show that elliptic-curve cryptography implementations on mobile devices are vulnerable to electromagnetic and power side-channel attacks. We demonstrate full extraction of ECDSA secret signing keys from OpenSSL and CoreBitcoin running on iOS devices, and partial key leakage from OpenSSL running on Android and from iOS's CommonCrypto. These non-intrusive attacks use a simple magnetic probe placed in proximity to the device, or a power probe on the phone's USB cable. They use a bandwidth of merely a few hundred kHz, and can be performed cheaply using an audio card and an improvised magnetic probe.

Embedded Systems (ES) are an integral part of Cyber-Physical Systems (CPS), the Internet of Things (IoT), and consumer devices like smartphones. ES often have limited resources, and - if used in CPS and IoT - have to satisfy real time requirements. Therefore, ES rarely employ the security measures established for computer systems and networks. Due to the growth of both CPS and IoT it is important to identify ongoing attacks on ES without interfering with realtime constraints. Furthermore, security solutions that can be retrofit to legacy systems are desirable, especially when ES are used in Industrial Control Systems (ICS) that often maintain the same hardware for decades. To tackle this problem, several researchers have proposed using side-channels (i.e., physical emanations accompanying cyber processes) to detect such attacks. While prior work focuses on the anomaly detection approach, this might not always be sufficient, especially in complex ES whose behavior depends on the input data. In this paper, we determine whether one of the most common attacks - a buffer overflow attack - generates distinct side-channel signatures if executed on a vulnerable ES. We only consider the power consumption side-channel. We collect and analyze power traces from normal program operation and four cases of buffer overflow attack categories: (i) crash program execution, (ii) injection of executable code, (iii) return to existing function, and (iv) Return Oriented Programming (ROP) with gadgets. Our analysis shows that for some of these cases a power signature-based detection of a buffer overflow attack is possible.

While attacks on information systems have for most practical purposes binary outcomes (information was manipulated/eavesdropped, or not), attacks manipulating the sensor or control signals of Industrial Control Systems (ICS) can be tuned by the attacker to cause a continuous spectrum in damages. Attackers that want to remain undetected can attempt to hide their manipulation of the system by following closely the expected behavior of the system, while injecting just enough false information at each time step to achieve their goals. In this work, we study if attack-detection can limit the impact of such stealthy attacks. We start with a comprehensive review of related work on attack detection schemes in the security and control systems community. We then show that many of those works use detection schemes that are not limiting the impact of stealthy attacks. We propose a new metric to measure the impact of stealthy attacks and how they relate to our selection on an upper bound on false alarms. We finally show that the impact of such attacks can be mitigated in several cases by the proper combination and configuration of detection schemes. We demonstrate the effectiveness of our algorithms through simulations and experiments using real ICS testbeds and real ICS systems.

In this paper, we propose a practical and efficient word and phrase proximity searchable encryption protocols for cloud based relational databases. The proposed advanced searchable encryption protocols are provably secure. We formalize the security assurance with cryptographic security definitions and prove the security of our searchable encryption protocols under Shannon's perfect secrecy assumption. We have tested the proposed protocols comprehensively on Amazon's high performance computing server using mysql database and presented the results. The proposed protocols ensure that there is zero overhead of space and communication because cipher text size being equal to plaintext size. For the same reason, the database schema also does not change for existing applications. In this paper, we also present results of comprehensive analysis for Song, Wagner, and Perrig scheme.

Riding on the success of SDN for enterprise and data center networks, recently researchers have shown much interest in applying SDN for critical infrastructures. A key concern, however, is the vulnerability of the SDN controller as a single point of failure. In this paper, we develop a cyber-physical simulation platform that interconnects Mininet (an SDN emulator), hardware SDN switches, and PowerWorld (a high-fidelity, industry-strength power grid simulator). We report initial experiments on how a number of representative controller faults may impact the delay of smart grid communications. We further evaluate how this delay may affect the performance of the underlying physical system, namely automatic gain control (AGC) as a fundamental closed-loop control that regulates the grid frequency to a critical nominal value. Our results show that when the fault-induced delay reaches seconds (e.g., more than four seconds in some of our experiments), degradation of the AGC becomes evident. Particularly, the AGC is most vulnerable when it is in a transient following say step changes in loading, because the significant state fluctuations will exacerbate the effects of using a stale system state in the control.

A key requirement for most security solutions is to provide secure cryptographic key storage in a way that will easily scale in the age of the Internet of Things. In this paper, we focus on providing such a solution based on Physical Unclonable Functions (PUFs). To this end, we focus on microelectromechanical systems (MEMS)-based gyroscopes and show via wafer-level measurements and simulations, that it is feasible to use the physical and electrical properties of these sensors for cryptographic key generation. After identifying the most promising features, we propose a novel quantization scheme to extract bit strings from the MEMS analog measurements. We provide upper and lower bounds for the minimum entropy of the derived bit strings and fully analyze the intra- and inter-class distributions across the operation range of the MEMS device. We complement these measurements via Monte-Carlo simulations based on the distributions of the parameters measured on actual devices. We also propose and evaluate a complete cryptographic key generation chain based on fuzzy extractors. We derive a full entropy 128-bit key using the obtained min-entropy estimates, requiring 1219 bits of helper data with an (authentication) failure probability of 4 . 10-7. In addition, we propose a dedicated MEMS-PUF design, which is superior to our measured sensor, in terms of chip area, quality and quantity of key seed features.

We develop a systematic approach for analyzing client-server applications that aim to hide sensitive user data from untrusted servers. We then apply it to Mylar, a framework that uses multi-key searchable encryption (MKSE) to build Web applications on top of encrypted data. We demonstrate that (1) the Popa-Zeldovich model for MKSE does not imply security against either passive or active attacks; (2) Mylar-based Web applications reveal users' data and queries to passive and active adversarial servers; and (3) Mylar is generically insecure against active attacks due to system design flaws. Our results show that the problem of securing client-server applications against actively malicious servers is challenging and still unsolved. We conclude with general lessons for the designers of systems that rely on property-preserving or searchable encryption to protect data from untrusted servers.

This paper introduces a novel graph-analytic approach for detecting anomalies in network flow data called GraphPrints. Building on foundational network-mining techniques, our method represents time slices of traffic as a graph, then counts graphlets–-small induced subgraphs that describe local topology. By performing outlier detection on the sequence of graphlet counts, anomalous intervals of traffic are identified, and furthermore, individual IPs experiencing abnormal behavior are singled-out. Initial testing of GraphPrints is performed on real network data with an implanted anomaly. Evaluation shows false positive rates bounded by 2.84% at the time-interval level, and 0.05% at the IP-level with 100% true positive rates at both.

The relevance of identity data leaks on the Internet is more present than ever. Almost every month we read about leakage of databases with more than a million users in the news. Smaller but not less dangerous leaks happen even multiple times a day. The public availability of such leaked data is a major threat to the victims, but also creates the opportunity to learn not only about security of service providers but also the behavior of users when choosing passwords. Our goal is to analyze this data and generate knowledge that can be used to increase security awareness and security, respectively. This paper presents a novel approach to automatic analysis of a vast majority of bigger and smaller leaks. Our contribution is the concept and a prototype implementation of a parser, composed of a syntactic and a semantic module, and a data analyzer for identity leaks. In this context, we deal with the two major challenges of a huge amount of different formats and the recognition of leaks' unknown data types. Based on the data collected, this paper reveals how easy it is for criminals to collect lots of passwords, which are plain text or only weakly hashed.

Modern operating systems use hardware support to protect against control-flow hijacking attacks such as code-injection attacks. Typically, write access to executable pages is prevented and kernel mode execution is restricted to kernel code pages only. However, current CPUs provide no protection against code-reuse attacks like ROP. ASLR is used to prevent these attacks by making all addresses unpredictable for an attacker. Hence, the kernel security relies fundamentally on preventing access to address information. We introduce Prefetch Side-Channel Attacks, a new class of generic attacks exploiting major weaknesses in prefetch instructions. This allows unprivileged attackers to obtain address information and thus compromise the entire system by defeating SMAP, SMEP, and kernel ASLR. Prefetch can fetch inaccessible privileged memory into various caches on Intel x86. It also leaks the translation-level for virtual addresses on both Intel x86 and ARMv8-A. We build three attacks exploiting these properties. Our first attack retrieves an exact image of the full paging hierarchy of a process, defeating both user space and kernel space ASLR. Our second attack resolves virtual to physical addresses to bypass SMAP on 64-bit Linux systems, enabling ret2dir attacks. We demonstrate this from unprivileged user programs on Linux and inside Amazon EC2 virtual machines. Finally, we demonstrate how to defeat kernel ASLR on Windows 10, enabling ROP attacks on kernel and driver binary code. We propose a new form of strong kernel isolation to protect commodity systems incuring an overhead of only 0.06-5.09%.

Vehicle localization is important in many applications of vehicular networks. The Global Positioning System (GPS) has been critical for vehicle localization. However, the case where the GPS is spoofed through a false data injection attack can be lead to devastating consequences, especially in localization solutions that make use of cooperation among multiple vehicles. Hence, resilient localization algorithms are needed that can achieve a baseline of performance in the case of a false data injection attack. This poster presents preliminary results of an inter-vehicle communication assisted localization algorithm that is resilient to false data injection attacks for the vehicles not directly attacked. The algorithm makes use of V2V and V2I communication – along with on-board GPS receiver, odometer, and compass – to achieve precise localization results.

Physical layer security can ensure secure communication over noisy channels in the presence of an eavesdropper with unlimited computational power. We adopt an information theoretic variant of semantic-security (SS) (a cryptographic gold standard), as our secrecy metric and study the open problem of the type II wiretap channel (WTC II) with a noisy main channel is, whose secrecy-capacity is unknown even under looser metrics than SS. Herein the secrecy-capacity is derived and shown to be equal to its SS capacity. In this setting, the legitimate users communicate via a discrete-memory less (DM) channel in the presence of an eavesdropper that has perfect access to a subset of its choosing of the transmitted symbols, constrained to a fixed fraction of the block length. The secrecy criterion is achieved simultaneously for all possible eavesdropper subset choices. On top of that, SS requires negligible mutual information between the message and the eavesdropper's observations even when maximized over all message distributions. A key tool for the achievability proof is a novel and stronger version of Wyner's soft covering lemma. Specifically, the lemma shows that a random codebook achieves the soft-covering phenomenon with high probability. The probability of failure is doubly-exponentially small in the block length. Since the combined number of messages and subsets grows only exponentially with the block length, SS for the WTC II is established by using the union bound and invoking the stronger soft-covering lemma. The direct proof shows that rates up to the weak-secrecy capacity of the classic WTC with a DM erasure channel (EC) to the eavesdropper are achievable. The converse follows by establishing the capacity of this DM wiretap EC as an upper bound for the WTC II. From a broader perspective, the stronger soft-covering lemma constitutes a tool for showing the existence of codebooks that satisfy exponentially many constraints, a beneficial ability for many other applications in information theoretic security.

For many wiretap channel models asymptotically optimal coding schemes are known, but less effort has been put into actual realizations of wiretap codes for practical parameters. Bounds on the mutual information and error probability when using coset coding on a Rayleigh fading channel were recently established by Oggier and Belfiore, and the results in this paper build on their work. However, instead of using their ultimate inverse norm sum approximation, a more precise expression for the eavesdropper's probability of correct decision is used in order to determine a general class of good coset codes. The code constructions are based on well-rounded lattices arising from simple geometric criteria. In addition to new coset codes and simulation results, novel number-theoretic results on well-rounded ideal lattices are presented.

The relevance of identity data leaks on the Internet is more present than ever. Almost every month we read about leakage of databases with more than a million users in the news. Smaller but not less dangerous leaks happen even multiple times a day. The public availability of such leaked data is a major threat to the victims, but also creates the opportunity to learn not only about security of service providers but also the behavior of users when choosing passwords. Our goal is to analyze this data and generate knowledge that can be used to increase security awareness and security, respectively. This paper presents a novel approach to automatic analysis of a vast majority of bigger and smaller leaks. Our contribution is the concept and a prototype implementation of a parser, composed of a syntactic and a semantic module, and a data analyzer for identity leaks. In this context, we deal with the two major challenges of a huge amount of different formats and the recognition of leaks' unknown data types. Based on the data collected, this paper reveals how easy it is for criminals to collect lots of passwords, which are plain text or only weakly hashed.

Physical layer security can ensure secure communication over noisy channels in the presence of an eavesdropper with unlimited computational power. We adopt an information theoretic variant of semantic-security (SS) (a cryptographic gold standard), as our secrecy metric and study the open problem of the type II wiretap channel (WTC II) with a noisy main channel is, whose secrecy-capacity is unknown even under looser metrics than SS. Herein the secrecy-capacity is derived and shown to be equal to its SS capacity. In this setting, the legitimate users communicate via a discrete-memory less (DM) channel in the presence of an eavesdropper that has perfect access to a subset of its choosing of the transmitted symbols, constrained to a fixed fraction of the block length. The secrecy criterion is achieved simultaneously for all possible eavesdropper subset choices. On top of that, SS requires negligible mutual information between the message and the eavesdropper's observations even when maximized over all message distributions. A key tool for the achievability proof is a novel and stronger version of Wyner's soft covering lemma. Specifically, the lemma shows that a random codebook achieves the soft-covering phenomenon with high probability. The probability of failure is doubly-exponentially small in the block length. Since the combined number of messages and subsets grows only exponentially with the block length, SS for the WTC II is established by using the union bound and invoking the stronger soft-covering lemma. The direct proof shows that rates up to the weak-secrecy capacity of the classic WTC with a DM erasure channel (EC) to the eavesdropper are achievable. The converse follows by establishing the capacity of this DM wiretap EC as an upper bound for the WTC II. From a broader perspective, the stronger soft-covering lemma constitutes a tool for showing the existence of codebooks that satisfy exponentially many constraints, a beneficial ability for many other applications in information theoretic security.
 

For many wiretap channel models asymptotically optimal coding schemes are known, but less effort has been put into actual realizations of wiretap codes for practical parameters. Bounds on the mutual information and error probability when using coset coding on a Rayleigh fading channel were recently established by Oggier and Belfiore, and the results in this paper build on their work. However, instead of using their ultimate inverse norm sum approximation, a more precise expression for the eavesdropper's probability of correct decision is used in order to determine a general class of good coset codes. The code constructions are based on well-rounded lattices arising from simple geometric criteria. In addition to new coset codes and simulation results, novel number-theoretic results on well-rounded ideal lattices are presented.
 

To help establish a more scientific basis for security science, which will enable the development of fundamental theories and move the field from being primarily reactive to primarily proactive, it is important for research results to be reported in a scientifically rigorous manner. Such reporting will allow for the standard pillars of science, namely replication, meta-analysis, and theory building. In this paper we aim to establish a baseline of the state of scientific work in security through the analysis of indicators of scientific research as reported in the papers from the 2015 IEEE Symposium on Security and Privacy. To conduct this analysis, we developed a series of rubrics to determine the completeness of the papers relative to the type of evaluation used (e.g. case study, experiment, proof). Our findings showed that while papers are generally easy to read, they often do not explicitly document some key information like the research objectives, the process for choosing the cases to include in the studies, and the threats to validity. We hope that this initial analysis will serve as a baseline against which we can measure the advancement of the science of security.

To help establish a more scientific basis for security science, which will enable the development of fundamental theories and move the field from being primarily reactive to primarily proactive, it is important for research results to be reported in a scientifically rigorous manner. Such reporting will allow for the standard pillars of science, namely replication, meta-analysis, and theory building. In this paper we aim to establish a baseline of the state of scientific work in security through the analysis of indicators of scientific research as reported in the papers from the 2015 IEEE Symposium on Security and Privacy. To conduct this analysis, we developed a series of rubrics to determine the completeness of the papers relative to the type of evaluation used (e.g. case study, experiment, proof). Our findings showed that while papers are generally easy to read, they often do not explicitly document some key information like the research objectives, the process for choosing the cases to include in the studies, and the threats to validity. We hope that this initial analysis will serve as a baseline against which we can measure the advancement of the science of security.

Keystroke dynamics analysis has been applied successfully to password or fixed short texts verification as a means to reduce their inherent security limitations, because their length and the fact of being typed often makes their characteristic timings fairly stable. On the other hand, free text analysis has been neglected until recent years due to the inherent difficulties of dealing with short term behavioral noise and long term effects over the typing rhythm. In this paper we examine finite context modeling of keystroke dynamics in free text and report promising results for user verification over an extensive data set collected from a real world environment outside the laboratory setting that we make publicly available.

Now-a-days for most of the organizations across the globe, two important IT initiatives are: Big Data Analytics and Cloud Computing. Big Data Analytics can provide valuables insight that can create competitiveness and generate increased revenues. Cloud Computing can enhance productivity and efficiencies thus reducing cost. Cloud Computing offers groups of servers, storages and various networking resources. It enables environment of Big Data to processes voluminous, high velocity and varied formats of Big Data.

Honeypot is a common method of attack capture, can maximize the reduction of cyber-attacks. However, its limited application layer simulation makes it impossible to use effectively in power system. Through research on sandboxing technology, this article implements the simulated power manager applications by packaging real power manager applications, in order to expand the honeypot applied range.

A novel approach is developed for analyzing power system vulnerability related to extraordinary events. Vulnerability analyses are necessary for identification of barriers to prevent such events and as a basis for the emergency preparedness. Identification of cause and effect relationships to reveal vulnerabilities related to extraordinary events is a complex and difficult task. In the proposed approach, the analysis starts by identifying the critical consequences. Then the critical contingencies and operating states, and which external threats and causes that may result in such severe consequences, are identified. This is opposed to the traditional risk and vulnerability analysis which starts by analyzing threats and what can happen as a chain of events. The vulnerability analysis methodology is tested and demonstrated on real systems.

Food safety policies have aim to promote and develop feeding and nutrition in society. This paper presents a system dynamics model that studies the dynamic behavior between transport infrastructure and the food supply chain in the city of Bogotá. The results show that an adequate transport infrastructure is more effective to improve the service to the customer in the food supply chain. The system dynamics model allows analyze the behavior of transport infrastructure and supply chains of fruits and vegetables, groceries, meat and dairy. The study has gone some way towards enhancing our understanding of food security impact, food supply chain and transport infrastructure.