Biblio
Game theory is appropriate for studying cyber conflict because it allows for an intelligent and goal-driven adversary. Applications of game theory have led to a number of results regarding optimal attack and defense strategies. However, the overwhelming majority of applications explore overly simplistic games, often ones in which each participant's actions are visible to every other participant. These simplifications strip away the fundamental properties of real cyber conflicts: probabilistic alerting, hidden actions, unknown opponent capabilities. In this paper, we demonstrate that it is possible to analyze a more realistic game, one in which different resources have different weaknesses, players have different exploits, and moves occur in secrecy, but they can be detected. Certainly, more advanced and complex games are possible, but the game presented here is more realistic than any other game we know of in the scientific literature. While optimal strategies can be found for simpler games using calculus, case-by-case analysis, or, for stochastic games, Q-learning, our more complex game is more naturally analyzed using the same methods used to study other complex games, such as checkers and chess. We define a simple evaluation function and employ multi-step searches to create strategies. We show that such scenarios can be analyzed, and find that in cases of extreme uncertainty, it is often better to ignore one's opponent's possible moves. Furthermore, we show that a simple evaluation function in a complex game can lead to interesting and nuanced strategies that follow tactics that tend to select moves that are well tuned to the details of the situation and the relative probabilities of success.
Game theory is appropriate for studying cyber conflict because it allows for an intelligent and goal-driven adversary. Applications of game theory have led to a number of results regarding optimal attack and defense strategies. However, the overwhelming majority of applications explore overly simplistic games, often ones in which each participant's actions are visible to every other participant. These simplifications strip away the fundamental properties of real cyber conflicts: probabilistic alerting, hidden actions, unknown opponent capabilities. In this paper, we demonstrate that it is possible to analyze a more realistic game, one in which different resources have different weaknesses, players have different exploits, and moves occur in secrecy, but they can be detected. Certainly, more advanced and complex games are possible, but the game presented here is more realistic than any other game we know of in the scientific literature. While optimal strategies can be found for simpler games using calculus, case-by-case analysis, or, for stochastic games, Q-learning, our more complex game is more naturally analyzed using the same methods used to study other complex games, such as checkers and chess. We define a simple evaluation function and employ multi-step searches to create strategies. We show that such scenarios can be analyzed, and find that in cases of extreme uncertainty, it is often better to ignore one's opponent's possible moves. Furthermore, we show that a simple evaluation function in a complex game can lead to interesting and nuanced strategies that follow tactics that tend to select moves that are well tuned to the details of the situation and the relative probabilities of success.
This study focuses on the spatial context of hacking to networks of Honey-pots. We investigate the relationship between topological positions and geographic positions of victimized computers and system trespassers. We've deployed research Honeypots on the computer networks of two academic institutions, collected information on successful brute force attacks (BFA) and system trespassing events (sessions), and used Social Network Analysis (SNA) techniques, to depict and understand the correlation between spatial attributes (IP addresses) and hacking networks' topology. We mapped and explored hacking patterns and found that geography might set the behavior of the attackers as well as the topology of hacking networks. The contribution of this study stems from the fact that there are no prior studies of geographical influences on the topology of hacking networks and from the unique usage of SNA to investigate hacking activities. Looking ahead, our study can assist policymakers in forming effective policies in the field of cybercrime.
After more than a decade of research, web application security continues to be a challenge and the backend database the most appetizing target. The paper proposes preventing injection attacks against the database management system (DBMS) behind web applications by embedding protections in the DBMS itself. The motivation is twofold. First, the approach of embedding protections in operating systems and applications running on top of them has been effective to protect this software. Second, there is a semantic mismatch between how SQL queries are believed to be executed by the DBMS and how they are actually executed, leading to subtle vulnerabilities in prevention mechanisms. The approach – SEPTIC – was implemented in MySQL and evaluated experimentally with web applications written in PHP and Java/Spring. In the evaluation SEPTIC has shown neither false negatives nor false positives, on the contrary of alternative approaches, causing also a low performance overhead in the order of 2.2%.
The growing popularity of Android and the increasing amount of sensitive data stored in mobile devices have lead to the dissemination of Android ransomware. Ransomware is a class of malware that makes data inaccessible by blocking access to the device or, more frequently, by encrypting the data; to recover the data, the user has to pay a ransom to the attacker. A solution for this problem is to backup the data. Although backup tools are available for Android, these tools may be compromised or blocked by the ransomware itself. This paper presents the design and implementation of RANSOMSAFEDROID, a TrustZone based backup service for mobile devices. RANSOMSAFEDROID is protected from malware by leveraging the ARM TrustZone extension and running in the secure world. It does backup of files periodically to a secure local persistent partition and pushes these backups to external storage to protect them from ransomware. Initially, RANSOMSAFEDROID does a full backup of the device filesystem, then it does incremental backups that save the changes since the last backup. As a proof-of-concept, we implemented a RANSOMSAFEDROID prototype and provide a performance evaluation using an i.MX53 development board.
Modern websites use multiple authentication cookies to allow visitors to the site different levels of access. The complexity of modern web applications can make it difficult for a web application programmer to ensure that the use of authentication cookies does not introduce vulnerabilities. Even when a programmer has access to all of the source code, this analysis can be challenging; the problem becomes even more vexing when web programmers cobble together off-the-shelf libraries to implement authentication. We have assembled a checklist for modern web programmers to verify that the cookie based authentication mechanism is securely implemented. Then, we developed a tool, Newton, to help a web application programmer to identify authentication cookies for specific parts of the website and to verify that they are securely implemented according to the checklist. We used Newton to analyze 149 sites, including the Alexa top-200 and many other popular sites across a range of categories including search, shopping, and finance. We found that 113 of them–-including high-profile sites such as Yahoo, Amazon, and Fidelity–-were vulnerable to hijacking attacks. Many websites have already acknowledged and fixed the vulnerabilities that we found using Newton and reported to them.
In this paper, we propose a hierarchical monitoring intrusion detection system (HAMIDS) for industrial control systems (ICS). The HAMIDS framework detects the anomalies in both level 0 and level 1 of an industrial control plant. In addition, the framework aggregates the cyber-physical process data in one point for further analysis as part of the intrusion detection process. The novelty of this framework is its ability to detect anomalies that have a distributed impact on the cyber-physical process. The performance of the proposed framework evaluated as part of SWaT security showdown (S3) in which six international teams were invited to test the framework in a real industrial control system. The proposed framework outperformed other proposed academic IDS in term of detection of ICS threats during the S3 event, which was held from July 25-29, 2016 at Singapore University of Technology and Design.
With the development of cloud computing the topology properties of data center network are important to the computing resources. Recently a data center network structure - BCCC is proposed, which is recursively built structure with many good properties. and expandability. The Hamiltonian and expandability in data center network structure plays an extremely important role in network communication. This paper described the Hamiltonian and expandability of the expandable data center network for BCCC structure, the important role of Hamiltonian and expandability in network traffic.
In this paper, based on the Hamiltonian, an alternative interpretation about the iterative adaptive dynamic programming (ADP) approach from the perspective of optimization is developed for discrete time nonlinear dynamic systems. The role of the Hamiltonian in iterative ADP is explained. The resulting Hamiltonian driven ADP is able to evaluate the performance with respect to arbitrary admissible policies, compare two different admissible policies and further improve the given admissible policy. The convergence of the Hamiltonian ADP to the optimal policy is proven. Implementation of the Hamiltonian-driven ADP by neural networks is discussed based on the assumption that each iterative policy and value function can be updated exactly. Finally, a simulation is conducted to verify the effectiveness of the presented Hamiltonian-driven ADP.
The Advanced Encryption Standard (AES) enables secure transmission of confidential messages. Since its invention, there have been many proposed attacks against the scheme. For example, one can inject errors or faults to acquire the encryption keys. It has been shown that the AES algorithm itself does not provide a protection against these types of attacks. Therefore, additional techniques like error control codes (ECCs) have been proposed to detect active attacks. However, not all the proposed solutions show the adequate efficacy. For instance, linear ECCs have some critical limitations, especially when the injected errors are beyond their fault detection or tolerance capabilities. In this paper, we propose a new method based on a non-linear code to protect all four internal stages of the AES hardware implementation. With this method, the protected AES system is able to (a) detect all multiplicity of errors with a high probability and (b) correct them if the errors follow certain patterns or frequencies. Results shows that the proposed method provides much higher security and reliability to the AES hardware implementation with minimal overhead.
Distributed storage platforms draw much attention due to their high reliability and scalability for handling a massive amount of data. To protect user and data privacy, encryption is considered as a necessary feature for production systems like Storj. But it prohibits the nodes from performing content search. To preserve the functionality, we observe that a protocol of integration with searchable encryption and keyword search via distributed hash table allows the nodes in a network to search over encrypted and distributed data. However, this protocol does not address a practical threat in a fully distributed scenario. Malicious nodes would sabotage search results, and easily infiltrate the system as the network grows. Using primitives such as MAC and verifiable data structure may empower the users to verify the search result, but the robustness of the overall system can hardly be ensured. In this paper, we address this issue by proposing a protocol that is seamlessly incorporated to encrypted search in distributed network to attest and monitor nodes. From the moment a node joins the system, it will be attested and continuously monitored through verifiable search queries. The result of each attestation is determined via a standard quorum-based voting protocol, and then recorded on the blockchain as a consensus view of trusted nodes. Based on the proposed protocols, malicious nodes can be detected and removed by a majority of nodes in a self-determining manner. To demonstrate the security and efficiency, we conduct robustness analysis against several potential attacks, and perform performance and overhead evaluation on the proposed protocol.
Infrastructure-as-a-Service (IaaS) clouds such as OpenStack consist of two kinds of nodes in their infrastructure: control nodes and compute nodes. While control nodes run all critical services, compute nodes host virtual machines of customers. Given the large number of compute nodes, and the fact that they are hosting VMs of (possibly malicious) customers, it is possible that some of the compute nodes may be compromised. This paper examines the impact of such a compromise. We focus on OpenStack, a popular open-source cloud plat- form that is widely adopted. We show that attackers com- promising a single compute node can extend their controls over the entire cloud infrastructure. They can then gain free access to resources that they have not paid for, or even bring down the whole cloud to affect all customers. This startling result stems from the cloud platform's misplaced trust, which does not match today's threats. To overcome the weakness, we propose a new system, called SOS , for hardening OpenStack. SOS limits trust on compute nodes. SOS consists of a framework that can enforce a wide range of security policies. Specifically, we applied mandatory access control and capabilities to con- fine interactions among different components. Effective confinement policies are generated automatically. Furthermore, SOS requires no modifications to the OpenStack. This has allowed us to deploy SOS on multiple versions of OpenStack. Our experimental results demonstrate that SOS is scalable, incurs negligible overheads and offers strong protection.
In the distributed Internet of Things (IoT) architecture, sensors collect data from vehicles, home appliances and office equipment and other environments. Various objects contain the sensor which process data, cooperate and exchange information with other embedded devices and end users in a distributed network. It is important to provide end-to-end communication security and an authentication system to guarantee the security and reliability of the data in such a distributed system. Two-factor authentication is a solution to improve the security level of password-based authentication processes and immunized the system against many attacks. At the same time, the computational and storage overhead of an authentication method also needs to be considered in IoT scenarios. For this reason, many cryptographic schemes are designed especially for the IoT; however, we observe a lack of laboratory hardware test beds and modules, and universal authentication hardware modules. This paper proposes a design and analysis for a hardware module in the IoT which allows the use of two-factor authentication based on smart cards, while taking into consideration the limited processing power and energy reserves of nodes, as well as designing the system with scalability in mind.
We present a brief survey on the state-of-the-art design and verification techniques: IC obfuscation, watermarking, fingerprinting, metering, concurrent checking and verification, for mitigating supply chain security risks such as IC misusing, counterfeiting and overbuilding.
A lot of research in security of cyber physical systems focus on threat models where an attacker can spoof sensor readings by compromising the communication channel. A little focus is given to attacks on physical components. In this paper a method to detect potential attacks on physical components in a Cyber Physical System (CPS) is proposed. Physical attacks are detected through a comparison of noise pattern from sensor measurements to a reference noise pattern. If an adversary has physically modified or replaced a sensor, the proposed method issues an alert indicating that a sensor is probably compromised or is defective. A reference noise pattern is established from the sensor data using a deterministic model. This pattern is referred to as a fingerprint of the corresponding sensor. The fingerprint so derived is used as a reference to identify measured data during the operation of a CPS. Extensive experimentation with ultrasonic level sensors in a realistic water treatment testbed point to the effectiveness of the proposed fingerprinting method in detecting physical attacks.
In the last few decades, the relative simplicity of the logistic map made it a widely accepted point in the consideration of chaos, which is having the good properties of unpredictability, sensitiveness in the key values and ergodicity. Further, the system parameters fit the requirements of a cipher widely used in the field of cryptography, asymmetric and symmetric key chaos based cryptography, and for pseudorandom sequence generation. Also, the hardware-based embedded system is configured on FPGA devices for high performance. In this paper, a novel stream cipher using chaotic logistic map is proposed. The two chaotic logistic maps are coded using Verilog HDL and implemented on commercially available FPGA hardware using Xilinx device: XC3S250E for the part: FT256 and operated at frequency of 62.20 MHz to generate the non-recursive key which is used in key scheduling of pseudorandom number generation (PRNG) to produce the key stream. The realization of proposed cryptosystem in this FPGA device accomplishes the improved efficiency equal to 0.1186 Mbps/slice. Further, the generated binary sequence from the experiment is analyzed for X-power, thermal analysis, and randomness tests are performed using NIST statistical.
In spite of numerous advantages of biometrics-based personal authentication systems over traditional security systems based on token or knowledge, they are vulnerable to attacks that can decrease their security considerably. In this paper, we propose a new hardware solution to protect biometric templates such as fingerprint. The proposed scheme is based on chaotic N × N grid multi-scroll system and it is implemented on Xilinx FPGA. The hardware implementation is achieved by applying numerical solution methods in our study, we use EM (Euler Method). Simulation and experimental results show that the proposed scheme allows a low cost image encryption for embedded systems while still providing a good trade-off between performance and hardware resources. Indeed, security analysis performed to the our scheme, is strong against known different attacks, such as: brute force, statistical, differential, and entropy. Therefore, the proposed chaos-based multiscroll encryption algorithm is suitable for use in securing embedded biometric systems.