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Carvalho, M., Ford, R..  2014.  Moving-Target Defenses for Computer Networks. Security Privacy, IEEE. 12:73-76.

One of the criticisms of traditional security approaches is that they present a static target for attackers. Critics state, with good justification, that by allowing the attacker to reconnoiter a system at leisure to plan an attack, defenders are immediately disadvantaged. To address this, the concept of moving-target defense (MTD) has recently emerged as a new paradigm for protecting computer networks and systems.

Wei Peng, Feng Li, Chin-Tser Huang, Xukai Zou.  2014.  A moving-target defense strategy for Cloud-based services with heterogeneous and dynamic attack surfaces. Communications (ICC), 2014 IEEE International Conference on. :804-809.

Due to deep automation, the configuration of many Cloud infrastructures is static and homogeneous, which, while easing administration, significantly decreases a potential attacker's uncertainty on a deployed Cloud-based service and hence increases the chance of the service being compromised. Moving-target defense (MTD) is a promising solution to the configuration staticity and homogeneity problem. This paper presents our findings on whether and to what extent MTD is effective in protecting a Cloud-based service with heterogeneous and dynamic attack surfaces - these attributes, which match the reality of current Cloud infrastructures, have not been investigated together in previous works on MTD in general network settings. We 1) formulate a Cloud-based service security model that incorporates Cloud-specific features such as VM migration/snapshotting and the diversity/compatibility of migration, 2) consider the accumulative effect of the attacker's intelligence on the target service's attack surface, 3) model the heterogeneity and dynamics of the service's attack surfaces, as defined by the (dynamic) probability of the service being compromised, as an S-shaped generalized logistic function, and 4) propose a probabilistic MTD service deployment strategy that exploits the dynamics and heterogeneity of attack surfaces for protecting the service against attackers. Through simulation, we identify the conditions and extent of the proposed MTD strategy's effectiveness in protecting Cloud-based services. Namely, 1) MTD is more effective when the service deployment is dense in the replacement pool and/or when the attack is strong, and 2) attack-surface heterogeneity-and-dynamics awareness helps in improving MTD's effectiveness.

Marttinen, A., Wyglinski, A.M., Jantti, R..  2014.  Moving-target defense mechanisms against source-selective jamming attacks in tactical cognitive radio MANETs. Communications and Network Security (CNS), 2014 IEEE Conference on. :14-20.

In this paper, we propose techniques for combating source selective jamming attacks in tactical cognitive MANETs. Secure, reliable and seamless communications are important for facilitating tactical operations. Selective jamming attacks pose a serious security threat to the operations of wireless tactical MANETs since selective strategies possess the potential to completely isolate a portion of the network from other nodes without giving a clear indication of a problem. Our proposed mitigation techniques use the concept of address manipulation, which differ from other techniques presented in open literature since our techniques employ de-central architecture rather than a centralized framework and our proposed techniques do not require any extra overhead. Experimental results show that the proposed techniques enable communications in the presence of source selective jamming attacks. When the presence of a source selective jammer blocks transmissions completely, implementing a proposed flipped address mechanism increases the expected number of required transmission attempts only by one in such scenario. The probability that our second approach, random address assignment, fails to solve the correct source MAC address can be as small as 10-7 when using accurate parameter selection.

Lakshminarayana, Subhash, Belmega, E. Veronica, Poor, H. Vincent.  2019.  Moving-Target Defense for Detecting Coordinated Cyber-Physical Attacks in Power Grids. 2019 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm). :1–7.
This work proposes a moving target defense (MTD) strategy to detect coordinated cyber-physical attacks (CCPAs) against power grids. A CCPA consists of a physical attack, such as disconnecting a transmission line, followed by a coordinated cyber attack that injects false data into the sensor measurements to mask the effects of the physical attack. Such attacks can lead to undetectable line outages and cause significant damage to the grid. The main idea of the proposed approach is to invalidate the knowledge that the attackers use to mask the effects of the physical attack by actively perturbing the grid's transmission line reactances using distributed flexible AC transmission system (D-FACTS) devices. We identify the MTD design criteria in this context to thwart CCPAs. The proposed MTD design consists of two parts. First, we identify the subset of links for D-FACTS device deployment that enables the defender to detect CCPAs against any link in the system. Then, in order to minimize the defense cost during the system's operational time, we use a game-theoretic approach to identify the best subset of links (within the D-FACTS deployment set) to perturb which will provide adequate protection. Extensive simulations performed using the MATPOWER simulator on IEEE bus systems verify the effectiveness of our approach in detecting CCPAs and reducing the operator's defense cost.
Fleck, Daniel, Stavrou, Angelos, Kesidis, George, Nasiriani, Neda, Shan, Yuquan, Konstantopoulos, Takis.  2018.  Moving-Target Defense Against Botnet Reconnaissance and an Adversarial Coupon-Collection Model. 2018 IEEE Conference on Dependable and Secure Computing (DSC). :1—8.

We consider a cloud based multiserver system consisting of a set of replica application servers behind a set of proxy (indirection) servers which interact directly with clients over the Internet. We study a proactive moving-target defense to thwart a DDoS attacker's reconnaissance phase and consequently reduce the attack's impact. The defense is effectively a moving-target (motag) technique in which the proxies dynamically change. The system is evaluated using an AWS prototype of HTTP redirection and by numerical evaluations of an “adversarial” coupon-collector mathematical model, the latter allowing larger-scale extrapolations.

Wasserstein, Ronald, Schirm, Allen, Lazar, Nicole.  2019.  Moving to a World Beyond “p < 0.05”. American Statistician. 73:1-19.

Some of you exploring this special issue of The American Statistician might be wondering if it’s a scolding from pedantic statisticians lecturing you about what not to do with p-values, without offering any real ideas of what to do about the very hard problem of separating signal from noise in data and making decisions under uncertainty. Fear not. In this issue, thanks to 43 innovative and thought-provoking papers from forward-looking statisticians, help is on the way.

Sadeghi, Ahmad-Reza.  2017.  Moving Targets vs. Moving Adversaries: On the Effectiveness of System Randomization. Proceedings of the 2017 Workshop on Moving Target Defense. :51–52.
Memory-corruption vulnerabilities pose a severe threat on modern systems security. Although this problem is known for almost three decades it is unlikely to be solved in the near future because a large amount of modern software is still programmed in unsafe, legacy languages such as C/C++. With new vulnerabilities in popular software discovered almost every day, and with high third party demand for (purchasing) the corresponding exploits, runtime attacks are more prevalent than ever. Even perfect cryptography can easily be undermined by exploiting software vulnerabilities. Typically, one vulnerability in wide-spread software (e.g., Tor Browser) is sufficient for the adversary to compromise all users. Moving target approaches such as software diversity [2] and system randomization techniques [7] are considered to be effective and practical means to strongly reduce the scale of such attacks because ideally, the adversary would require to craft a unique exploit per user. However, recently it was shown that existing software-randomization schemes can be circumvented by practical exploitation techniques such as Just-In-Time Return Oriented Programming (JIT-ROP) that takes advantage of information leakage [1]. The attack demonstrated that even a single disclosed code pointer can be exploited to defeat any (fine-grained) code randomization scheme. Later, it was shown that there are various sources of information leakage that can be exploited such as virtual function pointers [4]. JIT-ROP motivated a number of subsequent works to prevent the adversary from reading code such as Readactor [3,5], or ASLR Guard [8]. For instance, Readactor and its successor Readactor++ [3,5] use various techniques to prevent direct and indirect code disclosure, which seems to be non-trivial in general [6]. The arms race will continue.
Chatfield, B., Haddad, R. J..  2017.  Moving Target Defense Intrusion Detection System for IPv6 based smart grid advanced metering infrastructure. SoutheastCon 2017. :1–7.

Conventional intrusion detection systems for smart grid communications rely heavily on static based attack detection techniques. In essence, signatures created from historical data are compared to incoming network traffic to identify abnormalities. In the case of attacks where no historical data exists, static based approaches become ineffective thus relinquishing system resilience and stability. Moving target defense (MTD) has shown to be effective in discouraging attackers by introducing system entropy to increase exploit costs. Increase in exploit cost leads to a decrease in profitability for an attacker. In this paper, a Moving Target Defense Intrusion Detection System (MTDIDS) is proposed for smart grid IPv6 based advanced metering infrastructure. The advantage of MTDIDS is the ability to detect anomalies across moving targets by means of planar keys thereupon increasing detection rate. Evaluation of MTDIDS was carried out in a smart grid advanced metering infrastructure simulated in MATLAB.

Pappa, A. C., Ashok, A., Govindarasu, M..  2017.  Moving target defense for securing smart grid communications: Architecture, implementation evaluation. 2017 IEEE Power Energy Society Innovative Smart Grid Technologies Conference (ISGT). :1–5.

Supervisory Control and Data Acquisition(SCADA) communications are often subjected to various sophisticated cyber-attacks mostly because of their static system characteristics, enabling an attacker for easier profiling of the target system(s) and thereby impacting the Critical Infrastructures(CI). In this Paper, a novel approach to mitigate such static vulnerabilities is proposed by implementing a Moving Target Defense (MTD) strategy in a power grid SCADA environment, leveraging the existing communication network with an end-to-end IP-Hopping technique among trusted peers. The main contribution involves the design and implementation of MTD Architecture on Iowa State's PowerCyber testbed for targeted cyber-attacks, without compromising the availability of a SCADA system and studying the delay and throughput characteristics for different hopping rates in a realistic environment. Finally, we study two cases and provide mitigations for potential weaknesses of the proposed mechanism. Also, we propose to incorporate port mutation to further increase attack complexity as part of future work.

Colbaugh, R., Glass, K..  2013.  Moving target defense for adaptive adversaries. Intelligence and Security Informatics (ISI), 2013 IEEE International Conference on. :50-55.

Machine learning (ML) plays a central role in the solution of many security problems, for example enabling malicious and innocent activities to be rapidly and accurately distinguished and appropriate actions to be taken. Unfortunately, a standard assumption in ML - that the training and test data are identically distributed - is typically violated in security applications, leading to degraded algorithm performance and reduced security. Previous research has attempted to address this challenge by developing ML algorithms which are either robust to differences between training and test data or are able to predict and account for these differences. This paper adopts a different approach, developing a class of moving target (MT) defenses that are difficult for adversaries to reverse-engineer, which in turn decreases the adversaries' ability to generate training/test data differences that benefit them. We leverage the coevolutionary relationship between attackers and defenders to derive a simple, flexible MT defense strategy which is optimal or nearly optimal for a broad range of security problems. Case studies involving two distinct cyber defense applications demonstrate that the proposed MT algorithm outperforms standard static methods, offering effective defense against intelligent, adaptive adversaries.

Venkatesan, S., Albanese, M., Amin, K., Jajodia, S., Wright, M..  2016.  A moving target defense approach to mitigate DDoS attacks against proxy-based architectures. 2016 IEEE Conference on Communications and Network Security (CNS). :198–206.

Distributed Denial of Service attacks against high-profile targets have become more frequent in recent years. In response to such massive attacks, several architectures have adopted proxies to introduce layers of indirection between end users and target services and reduce the impact of a DDoS attack by migrating users to new proxies and shuffling clients across proxies so as to isolate malicious clients. However, the reactive nature of these solutions presents weaknesses that we leveraged to develop a new attack - the proxy harvesting attack - which enables malicious clients to collect information about a large number of proxies before launching a DDoS attack. We show that current solutions are vulnerable to this attack, and propose a moving target defense technique consisting in periodically and proactively replacing one or more proxies and remapping clients to proxies. Our primary goal is to disrupt the attacker's reconnaissance effort. Additionally, to mitigate ongoing attacks, we propose a new client-to-proxy assignment strategy to isolate compromised clients, thereby reducing the impact of attacks. We validate our approach both theoretically and through simulation, and show that the proposed solution can effectively limit the number of proxies an attacker can discover and isolate malicious clients.

Venkatesan, Sridhar, Albanese, Massimiliano, Cybenko, George, Jajodia, Sushil.  2016.  A Moving Target Defense Approach to Disrupting Stealthy Botnets. Proceeding MTD '16 Proceedings of the 2016 ACM Workshop on Moving Target Defense Pages 37-46 .

Botnets are increasingly being used for exfiltrating sensitive data from mission-critical systems. Research has shown that botnets have become extremely sophisticated and can operate in stealth mode by minimizing their host and network footprint. In order to defeat exfiltration by modern botnets, we propose a moving target defense approach for dynamically deploying detectors across a network. Specifically, we propose several strategies based on centrality measures to periodically change the placement of detectors. Our objective is to increase the attacker's effort and likelihood of detection by creating uncertainty about the location of detectors and forcing botmasters to perform additional actions in an attempt to create detector-free paths through the network. We present metrics to evaluate the proposed strategies and an algorithm to compute a lower bound on the detection probability. We validate our approach through simulations, and results confirm that the proposed solution effectively reduces the likelihood of successful exfiltration campaigns.

Venkatesan, Sridhar, Albanese, Massimiliano, Cybenko, George, Jajodia, Sushil.  2016.  A Moving Target Defense Approach to Disrupting Stealthy Botnets. Proceedings of the 2016 ACM Workshop on Moving Target Defense. :37–46.

Botnets are increasingly being used for exfiltrating sensitive data from mission-critical systems. Research has shown that botnets have become extremely sophisticated and can operate in stealth mode by minimizing their host and network footprint. In order to defeat exfiltration by modern botnets, we propose a moving target defense approach for dynamically deploying detectors across a network. Specifically, we propose several strategies based on centrality measures to periodically change the placement of detectors. Our objective is to increase the attacker's effort and likelihood of detection by creating uncertainty about the location of detectors and forcing botmasters to perform additional actions in an attempt to create detector-free paths through the network. We present metrics to evaluate the proposed strategies and an algorithm to compute a lower bound on the detection probability. We validate our approach through simulations, and results confirm that the proposed solution effectively reduces the likelihood of successful exfiltration campaigns.

Wright, Mason, Venkatesan, Sridhar, Albanese, Massimiliano, Wellman, Michael P..  2016.  Moving Target Defense Against DDoS Attacks: An Empirical Game-Theoretic Analysis. Proceedings of the 2016 ACM Workshop on Moving Target Defense. :93–104.

Distributed denial-of-service attacks are an increasing problem facing web applications, for which many defense techniques have been proposed, including several moving-target strategies. These strategies typically work by relocating targeted services over time, increasing uncertainty for the attacker, while trying not to disrupt legitimate users or incur excessive costs. Prior work has not shown, however, whether and how a rational defender would choose a moving-target method against an adaptive attacker, and under what conditions. We formulate a denial-of-service scenario as a two-player game, and solve a restricted-strategy version of the game using the methods of empirical game-theoretic analysis. Using agent-based simulation, we evaluate the performance of strategies from prior literature under a variety of attacks and environmental conditions. We find evidence for the strategic stability of various proposed strategies, such as proactive server movement, delayed attack timing, and suspected insider blocking, along with guidelines for when each is likely to be most effective.

Khosravi-Farmad, M., Ramaki, A. A., Bafghi, A. G..  2018.  Moving Target Defense Against Advanced Persistent Threats for Cybersecurity Enhancement. 2018 8th International Conference on Computer and Knowledge Engineering (ICCKE). :280–285.
One of the main security concerns of enterprise-level organizations which provide network-based services is combating with complex cybersecurity attacks like advanced persistent threats (APTs). The main features of these attacks are being multilevel, multi-step, long-term and persistent. Also they use an intrusion kill chain (IKC) model to proceed the attack steps and reach their goals on targets. Traditional security solutions like firewalls and intrusion detection and prevention systems (IDPSs) are not able to prevent APT attack strategies and block them. Recently, deception techniques are proposed to defend network assets against malicious activities during IKC progression. One of the most promising approaches against APT attacks is Moving Target Defense (MTD). MTD techniques can be applied to attack steps of any abstraction levels in a networked infrastructure (application, host, and network) dynamically for disruption of successful execution of any on the fly IKCs. In this paper, after presentation and discussion on common introduced IKCs, one of them is selected and is used for further analysis. Also, after proposing a new and comprehensive taxonomy of MTD techniques in different levels, a mapping analysis is conducted between IKC models and existing MTD techniques. Finally, the effect of MTD is evaluated during a case study (specifically IP Randomization). The experimental results show that the MTD techniques provide better means to defend against IKC-based intrusion activities.
Li, Jason, Yackoski, Justin, Evancich, Nicholas.  2016.  Moving Target Defense: A Journey from Idea to Product. Proceedings of the 2016 ACM Workshop on Moving Target Defense. :69–79.

In today's enterprise networks, there are many ways for a determined attacker to obtain a foothold, bypass current protection technologies, and attack the intended target. Over several years we have developed the Self-shielding Dynamic Network Architecture (SDNA) technology, which prevents an attacker from targeting, entering, or spreading through an enterprise network by adding dynamics that present a changing view of the network over space and time. SDNA was developed with the support of government sponsored research and development and corporate internal resources. The SDNA technology was purchased by Cryptonite, LLC in 2015 and has been developed into a robust product offering called Cryptonite NXT. In this paper, we describe the journey and lessons learned along the course of feasibility demonstration, technology development, security testing, productization, and deployment in a production network.

Liu, S., Kosuru, R., Mugombozi, C. F..  2020.  A Moving Target Approach for Securing Secondary Frequency Control in Microgrids. 2020 IEEE Canadian Conference on Electrical and Computer Engineering (CCECE). :1–6.
Microgrids' dependency on communication links exposes the control systems to cyber attack threats. In this work, instead of designing reactive defense approaches, a proacitve moving target defense mechanism is proposed for securing microgrid secondary frequency control from denial of service (DoS) attack. The sensor data is transmitted by following a Markov process, not in a deterministic way. This uncertainty will increase the difficulty for attacker's decision making and thus significantly reduce the attack space. As the system parameters are constantly changing, a gain scheduling based secondary frequency controller is designed to sustain the system performance. Case studies of a microgrid with four inverter-based DGs show the proposed moving target mechanism can enhance the resiliency of the microgrid control systems against DoS attacks.
Zhang, Chi, Zheng, Jin, Zhang, Yugui, Zhang, Zhi.  2017.  Moving Object Detection Algorithm Based on Pixel Background Sample Sets in Panoramic Scanning Mode. Proceedings of the International Conference on Compute and Data Analysis. :171–175.

In order to overcome the excessive false detection of marginal noise and the object holes of the existing algorithm in outdoor panoramic surveillance, a moving object detection algorithm based on pixel background sample sets in panoramic scanning mode is proposed. In the light of the space distribution characteristics, neighborhood pixels have similar values. Therefore, a background sample set for each pixel is created by random sampling in the first scanning cycle which effectively avoids the false detection of marginal noise and reduces the time cost of background model establishment. The adjacent frame difference detection algorithm in the traditional camera motion mode is prone to object holes. To solve this problem, detection based on background sample sets is presented to obtain complete moving object region. The results indicate that the proposed moving object detection algorithm works more efficiently on reducing marginal noise interference, and obtains complete moving object information compared with the frame difference detection algorithm based on registration results in traditional camera motion mode, thereby meeting the needs of real-time detection as well as improving its accuracy.

Kathiravelu, P., Chiesa, M., Marcos, P., Canini, M., Veiga, L..  2018.  Moving Bits with a Fleet of Shared Virtual Routers. 2018 IFIP Networking Conference (IFIP Networking) and Workshops. :1—9.

The steady decline of IP transit prices in the past two decades has helped fuel the growth of traffic demands in the Internet ecosystem. Despite the declining unit pricing, bandwidth costs remain significant due to ever-increasing scale and reach of the Internet, combined with the price disparity between the Internet's core hubs versus remote regions. In the meantime, cloud providers have been auctioning underutilized computing resources in their marketplace as spot instances for a much lower price, compared to their on-demand instances. This state of affairs has led the networking community to devote extensive efforts to cloud-assisted networks - the idea of offloading network functionality to cloud platforms, ultimately leading to more flexible and highly composable network service chains.We initiate a critical discussion on the economic and technological aspects of leveraging cloud-assisted networks for Internet-scale interconnections and data transfers. Namely, we investigate the prospect of constructing a large-scale virtualized network provider that does not own any fixed or dedicated resources and runs atop several spot instances. We construct a cloud-assisted overlay as a virtual network provider, by leveraging third-party cloud spot instances. We identify three use case scenarios where such approach will not only be economically and technologically viable but also provide performance benefits compared to current commercial offerings of connectivity and transit providers.

Cai, Peixiang, Zhang, Yu, Wang, Xuesi, Pan, Changyong.  2018.  Motion-Aware Clock Synchronization for Mobile Ad-Hoc Networks. 2018 IEEE 88th Vehicular Technology Conference (VTC-Fall). :1–5.
Recently, mobile ad-hoc networks (MANET) have been widely used in several scenarios. Due to its generally high demands on clock synchronization accuracy, the conventional synchronization algorithms cannot be applied in many high-speed MANET applications. Hence, in this paper, a clock synchronization algorithm based on motion information such as the speed of nodes is proposed to eliminate the error of round-trip-time correction. Meanwhile, a simplified version of our algorithm is put forward to cope with some resource-constrained scenes. Our algorithm can perform well in most situations and effectively improve the clock synchronization accuracy with reasonable communication overhead, especially in high-speed scenes. Simulation results confirm the superior accuracy performance achieved by our algorithm.
Xu, R., Naman, A. T., Mathew, R., Rüfenacht, D., Taubman, D..  2015.  Motion estimation with accurate boundaries. 2015 Picture Coding Symposium (PCS). :184–188.

This paper investigates several techniques that increase the accuracy of motion boundaries in estimated motion fields of a local dense estimation scheme. In particular, we examine two matching metrics, one is MSE in the image domain and the other one is a recently proposed multiresolution metric that has been shown to produce more accurate motion boundaries. We also examine several different edge-preserving filters. The edge-aware moving average filter, proposed in this paper, takes an input image and the result of an edge detection algorithm, and outputs an image that is smooth except at the detected edges. Compared to the adoption of edge-preserving filters, we find that matching metrics play a more important role in estimating accurate and compressible motion fields. Nevertheless, the proposed filter may provide further improvements in the accuracy of the motion boundaries. These findings can be very useful for a number of recently proposed scalable interactive video coding schemes.

Iyengar, Varsha, Coleman, Grisha, Tinapple, David, Turaga, Pavan.  2016.  Motion, Captured: An Open Repository for Comparative Movement Studies. Proceedings of the 3rd International Symposium on Movement and Computing. :17:1–17:6.

This paper begins to describe a new kind of database, one that explores a diverse range of movement in the field of dance through capture of different bodies and different backgrounds - or what we are terming movement vernaculars. We re-purpose Ivan Illich's concept of 'vernacular work' [11] here to refer to those everyday forms of dance and organized movement that are informal, refractory (resistant to formal analysis), yet are socially reproduced and derived from a commons. The project investigates the notion of vernaculars in movement that is intentional and aesthetic through the development of a computational approach that highlights both similarities and differences, thereby revealing the specificities of each individual mover. This paper presents an example of how this movement database is used as a research tool, and how the fruits of that research can be added back to the database, thus adding a novel layer of annotation and further enriching the collection. Future researchers can then benefit from this layer, further refining and building upon these techniques. The creation of a robust, open source, movement lexicon repository will allow for observation, speculation, and contextualization - along with the provision of clean and complex data sets for new forms of creative expression.

Dey, A. K., Gel, Y. R., Poor, H. V..  2017.  Motif-Based Analysis of Power Grid Robustness under Attacks. 2017 IEEE Global Conference on Signal and Information Processing (GlobalSIP). :1015–1019.

Network motifs are often called the building blocks of networks. Analysis of motifs is found to be an indispensable tool for understanding local network structure, in contrast to measures based on node degree distribution and its functions that primarily address a global network topology. As a result, networks that are similar in terms of global topological properties may differ noticeably at a local level. In the context of power grids, this phenomenon of the impact of local structure has been recently documented in fragility analysis and power system classification. At the same time, most studies of power system networks still tend to focus on global topo-logical measures of power grids, often failing to unveil hidden mechanisms behind vulnerability of real power systems and their dynamic response to malfunctions. In this paper a pilot study of motif-based analysis of power grid robustness under various types of intentional attacks is presented, with the goal of shedding light on local dynamics and vulnerability of power systems.

Snyder, Peter, Taylor, Cynthia, Kanich, Chris.  2017.  Most Websites Don'T Need to Vibrate: A Cost-Benefit Approach to Improving Browser Security. Proceedings of the 2017 ACM SIGSAC Conference on Computer and Communications Security. :179–194.

Modern web browsers have accrued an incredibly broad set of features since being invented for hypermedia dissemination in 1990. Many of these features benefit users by enabling new types of web applications. However, some features also bring risk to users' privacy and security, whether through implementation error, unexpected composition, or unintended use. Currently there is no general methodology for weighing these costs and benefits. Restricting access to only the features which are necessary for delivering desired functionality on a given website would allow users to enforce the principle of lease privilege on use of the myriad APIs present in the modern web browser. However, security benefits gained by increasing restrictions must be balanced against the risk of breaking existing websites. This work addresses this problem with a methodology for weighing the costs and benefits of giving websites default access to each browser feature. We model the benefit as the number of websites that require the feature for some user-visible benefit, and the cost as the number of CVEs, lines of code, and academic attacks related to the functionality. We then apply this methodology to 74 Web API standards implemented in modern browsers. We find that allowing websites default access to large parts of the Web API poses significant security and privacy risks, with little corresponding benefit. We also introduce a configurable browser extension that allows users to selectively restrict access to low-benefit, high-risk features on a per site basis. We evaluated our extension with two hardened browser configurations, and found that blocking 15 of the 74 standards avoids 52.0% of code paths related to previous CVEs, and 50.0% of implementation code identified by our metric, without affecting the functionality of 94.7% of measured websites.

Boato, G., Dang-Nguyen, D., Natale, F. G. B. De.  2020.  Morphological Filter Detector for Image Forensics Applications. IEEE Access. 8:13549—13560.
Mathematical morphology provides a large set of powerful non-linear image operators, widely used for feature extraction, noise removal or image enhancement. Although morphological filters might be used to remove artifacts produced by image manipulations, both on binary and gray level documents, little effort has been spent towards their forensic identification. In this paper we propose a non-trivial extension of a deterministic approach originally detecting erosion and dilation of binary images. The proposed approach operates on grayscale images and is robust to image compression and other typical attacks. When the image is attacked the method looses its deterministic nature and uses a properly trained SVM classifier, using the original detector as a feature extractor. Extensive tests demonstrate that the proposed method guarantees very high accuracy in filtering detection, providing 100% accuracy in discriminating the presence and the type of morphological filter in raw images of three different datasets. The achieved accuracy is also good after JPEG compression, equal or above 76.8% on all datasets for quality factors above 80. The proposed approach is also able to determine the adopted structuring element for moderate compression factors. Finally, it is robust against noise addition and it can distinguish morphological filter from other filters.