Enhancing Cloud Security by a Series of Mobile Applications That Provide Timely and Process Level Intervention of Real-Time Attacks

Cyber threat indicators that can be instantly shared in real-time may often be the only mitigating factor between preventing and succumbing to a cyber-attack. Detecting threats in cloud computing environment can be even more of a challenge given the dynamic and complex nature of hosts as well as the services running. Information security professionals have long relied on automated tools such as intrusion detection/prevention systems, SIEM (security information and event management), and vulnerability scanners to report system, application and architectural weaknesses. Although these mechanisms are widely accepted and considered effective at helping organizations stay more secure, each can also have unique limitations that can hinder in this regard. Therefore, in addition to utilizing these resources, a more proactive approach must be incorporated to bring to light possible attack vectors and hidden places where hackers may infiltrate. This paper shares an insightful example of such lessor known attack vectors by closely examining a host routing table cache, which unveiled a great deal of information that went unrecognized by an intrusion detection system. Furthermore, the author researched and developed a robust mobile app tool that has a multitude of functions which can provide the information security community with a low-cost countermeasure that can be used in a variety of infrastructures (e.g. cloud, host-based etc.). The designed mobile app also illustrates how system administrators and other IT leaders can be alerted of brute force attacks and other rogue processes by quickly identifying and blocking the attacking IP addresses. Furthermore, it is an Android based application that also uses logs created by the Fail2Ban intrusion prevention framework for Linux. Additionally, the paper will also familiarize readers with indirect detection techniques, ways to tune and protect the routing cache, the impact of low and slow hacking techniques, as well as the need for mobile app management in a cloud

Information Resilience in a Network of Caches with Perturbations

Caching in a network of caches has been widely investigated for improving information/content delivery efficiency (e.g., for reducing content delivery latency, server load and bandwidth utilization). In this work, we look into another dimension of network of caches – enhancing resilience in information dissemination rather than improving delivery efficiency. The underlying premise is that when information is cached at more locations, its availability is increased and thus, in turn, improve information delivery resiliency. This is especially important for networks with perturbations (e.g., node failures). Considering a general network of caches, we present a collaborative caching framework for maximizing the availability of the information. Specifically, we formulate an optimization problem for maximizing the joint utility of caching nodes in serving content requests in perturbed networks. We first solve the centralized version of the problem and then propose a distributed caching algorithm that approximates the centralized solution. We compare our proposal against different caching schemes under a range of parameters, using both real-world and synthetic network topologies. The results show that our algorithm can significantly improve the joint utility of caching nodes. With our distributed caching algorithm, the achieved caching utility is up to five times higher than greedy caching scheme. Furthermore, our scheme is found to be robust against increasing node failure rate, even for networks with a high number of vulnerable nodes

On the design of efficient caching systems

Content distribution is currently the prevalent Internet use case, accounting for the majority of global Internet traffic and growing exponentially. There is general consensus that the most effective method to deal with the large amount of content demand is through the deployment of massively distributed caching infrastructures as the means to localise content delivery traffic. Solutions based on caching have been already widely deployed through Content Delivery Networks. Ubiquitous caching is also a fundamental aspect of the emerging Information-Centric Networking paradigm which aims to rethink the current Internet architecture for long term evolution. Distributed content caching systems are expected to grow substantially in the future, in terms of both footprint and traffic carried and, as such, will become substantially more complex and costly. This thesis addresses the problem of designing scalable and cost-effective distributed caching systems that will be able to efficiently support the expected massive growth of content traffic and makes three distinct contributions. First, it produces an extensive theoretical characterisation of sharding, which is a widely used technique to allocate data items to resources of a distributed system according to a hash function. Based on the findings unveiled by this analysis, two systems are designed contributing to the abovementioned objective. The first is a framework and related algorithms for enabling efficient load-balanced content caching. This solution provides qualitative advantages over previously proposed solutions, such as ease of modelling and availability of knobs to fine-tune performance, as well as quantitative advantages, such as 2x increase in cache hit ratio and 19-33% reduction in load imbalance while maintaining comparable latency to other approaches. The second is the design and implementation of a caching node enabling 20 Gbps speeds based on inexpensive commodity hardware. We believe these contributions advance significantly the state of the art in distributed caching systems