Visible to the public Biblio

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2020-01-20
Xiao, Kaiming, Zhu, Cheng, Xie, Junjie, Zhou, Yun, Zhu, Xianqiang, Zhang, Weiming.  2018.  Dynamic Defense Strategy against Stealth Malware Propagation in Cyber-Physical Systems. IEEE INFOCOM 2018 - IEEE Conference on Computer Communications. :1790–1798.
Stealth malware, a representative tool of advanced persistent threat (APT) attacks, in particular poses an increased threat to cyber-physical systems (CPS). Due to the use of stealthy and evasive techniques (e.g., zero-day exploits, obfuscation techniques), stealth malwares usually render conventional heavyweight countermeasures (e.g., exploits patching, specialized ant-malware program) inapplicable. Light-weight countermeasures (e.g., containment techniques), on the other hand, can help retard the spread of stealth malwares, but the ensuing side effects might violate the primary safety requirement of CPS. Hence, defenders need to find a balance between the gain and loss of deploying light-weight countermeasures. To address this challenge, we model the persistent anti-malware process as a shortest-path tree interdiction (SPTI) Stackelberg game, and safety requirements of CPS are introduced as constraints in the defender's decision model. Specifically, we first propose a static game (SSPTI), and then extend it to a multi-stage dynamic game (DSPTI) to meet the need of real-time decision making. Both games are modelled as bi-level integer programs, and proved to be NP-hard. We then develop a Benders decomposition algorithm to achieve the Stackelberg Equilibrium of SSPTI. Finally, we design a model predictive control strategy to solve DSPTI approximately by sequentially solving an approximation of SSPTI. The extensive simulation results demonstrate that the proposed dynamic defense strategy can achieve a balance between fail-secure ability and fail-safe ability while retarding the stealth malware propagation in CPS.
Ingols, Kyle, Chu, Matthew, Lippmann, Richard, Webster, Seth, Boyer, Stephen.  2009.  Modeling Modern Network Attacks and Countermeasures Using Attack Graphs. 2009 Annual Computer Security Applications Conference. :117–126.
By accurately measuring risk for enterprise networks, attack graphs allow network defenders to understand the most critical threats and select the most effective countermeasures. This paper describes substantial enhancements to the NetSPA attack graph system required to model additional present-day threats (zero-day exploits and client-side attacks) and countermeasures (intrusion prevention systems, proxy firewalls, personal firewalls, and host-based vulnerability scans). Point-to-point reachability algorithms and structures were extensively redesigned to support "reverse" reachability computations and personal firewalls. Host-based vulnerability scans are imported and analyzed. Analysis of an operational network with 84 hosts demonstrates that client-side attacks pose a serious threat. Experiments on larger simulated networks demonstrated that NetSPA's previous excellent scaling is maintained. Less than two minutes are required to completely analyze a four-enclave simulated network with more than 40,000 hosts protected by personal firewalls.
Sun, Xiaoyan, Dai, Jun, Liu, Peng, Singhal, Anoop, Yen, John.  2016.  Towards probabilistic identification of zero-day attack paths. 2016 IEEE Conference on Communications and Network Security (CNS). :64–72.
Zero-day attacks continue to challenge the enterprise network security defense. A zero-day attack path is formed when a multi-step attack contains one or more zero-day exploits. Detecting zero-day attack paths in time could enable early disclosure of zero-day threats. In this paper, we propose a probabilistic approach to identify zero-day attack paths and implement a prototype system named ZePro. An object instance graph is first built from system calls to capture the intrusion propagation. To further reveal the zero-day attack paths hiding in the instance graph, our system constructs an instance-graph-based Bayesian network. By leveraging intrusion evidence, the Bayesian network can quantitatively compute the probabilities of object instances being infected. The object instances with high infection probabilities reveal themselves and form the zero-day attack paths. The experiment results show that our system can effectively identify zero-day attack paths.
Musca, Constantin, Mirica, Emma, Deaconescu, Razvan.  2013.  Detecting and Analyzing Zero-Day Attacks Using Honeypots. 2013 19th International Conference on Control Systems and Computer Science. :543–548.
Computer networks are overwhelmed by self propagating malware (worms, viruses, trojans). Although the number of security vulnerabilities grows every day, not the same thing can be said about the number of defense methods. But the most delicate problem in the information security domain remains detecting unknown attacks known as zero-day attacks. This paper presents methods for isolating the malicious traffic by using a honeypot system and analyzing it in order to automatically generate attack signatures for the Snort intrusion detection/prevention system. The honeypot is deployed as a virtual machine and its job is to log as much information as it can about the attacks. Then, using a protected machine, the logs are collected remotely, through a safe connection, for analysis. The challenge is to mitigate the risk we are exposed to and at the same time search for unknown attacks.
Clark, Shane S., Paulos, Aaron, Benyo, Brett, Pal, Partha, Schantz, Richard.  2015.  Empirical Evaluation of the A3 Environment: Evaluating Defenses Against Zero-Day Attacks. 2015 10th International Conference on Availability, Reliability and Security. :80–89.
A3 is an execution management environment that aims to make network-facing applications and services resilient against zero-day attacks. A3 recently underwent two adversarial evaluations of its defensive capabilities. In one, A3 defended an App Store used in a Capture the Flag (CTF) tournament, and in the other, a tactically relevant network service in a red team exercise. This paper describes the A3 defensive technologies evaluated, the evaluation results, and the broader lessons learned about evaluations for technologies that seek to protect critical systems from zero-day attacks.
Bardia, Vivek, Kumar, C.R.S..  2017.  Process trees amp; service chains can serve us to mitigate zero day attacks better. 2017 International Conference on Data Management, Analytics and Innovation (ICDMAI). :280–284.
With technology at our fingertips waiting to be exploited, the past decade saw the revolutionizing Human Computer Interactions. The ease with which a user could interact was the Unique Selling Proposition (USP) of a sales team. Human Computer Interactions have many underlying parameters like Data Visualization and Presentation as some to deal with. With the race, on for better and faster presentations, evolved many frameworks to be widely used by all software developers. As the need grew for user friendly applications, more and more software professionals were lured into the front-end sophistication domain. Application frameworks have evolved to such an extent that with just a few clicks and feeding values as per requirements we are able to produce a commercially usable application in a few minutes. These frameworks generate quantum lines of codes in minutes which leaves a contrail of bugs to be discovered in the future. We have also succumbed to the benchmarking in Software Quality Metrics and have made ourselves comfortable with buggy software's to be rectified in future. The exponential evolution in the cyber domain has also attracted attackers equally. Average human awareness and knowledge has also improved in the cyber domain due to the prolonged exposure to technology for over three decades. As the attack sophistication grows and zero day attacks become more popular than ever, the suffering end users only receive remedial measures in spite of the latest Antivirus, Intrusion Detection and Protection Systems installed. We designed a software to display the complete services and applications running in users Operating System in the easiest perceivable manner aided by Computer Graphics and Data Visualization techniques. We further designed a study by empowering the fence sitter users with tools to actively participate in protecting themselves from threats. The designed threats had impressions from the complete threat canvas in some form or other restricted to systems functioning. Network threats and any sort of packet transfer to and from the system in form of threat was kept out of the scope of this experiment. We discovered that end users had a good idea of their working environment which can be used exponentially enhances machine learning for zero day threats and segment the unmarked the vast threat landscape faster for a more reliable output.
AfekYehuda, Bremler-BarrAnat, Landau, FeibishShir.  2019.  Zero-Day Signature Extraction for High-Volume Attacks. IEEE/ACM Transactions on Networking (TON).
We present a basic tool for zero day attack signature extraction. Given two large sets of messages, \$P\$ the messages captured in the network at peacetime i.e., mostly legitimate traffic and \$A\$ the...
Nicho, Mathew, McDermott, Christopher D..  2019.  Dimensions of ‘Socio’ Vulnerabilities of Advanced Persistent Threats. 2019 International Conference on Software, Telecommunications and Computer Networks (SoftCOM). :1–5.
Advanced Persistent Threats (APT) are highly targeted and sophisticated multi-stage attacks, utilizing zero day or near zero-day malware. Directed at internetworked computer users in the workplace, their growth and prevalence can be attributed to both socio (human) and technical (system weaknesses and inadequate cyber defenses) vulnerabilities. While many APT attacks incorporate a blend of socio-technical vulnerabilities, academic research and reported incidents largely depict the user as the prominent contributing factor that can weaken the layers of technical security in an organization. In this paper, our objective is to explore multiple dimensions of socio factors (non-technical vulnerabilities) that contribute to the success of APT attacks in organizations. Expert interviews were conducted with senior managers, working in government and private organizations in the United Arab Emirates (UAE) over a period of four years (2014 to 2017). Contrary to common belief that socio factors derive predominately from user behavior, our study revealed two new dimensions of socio vulnerabilities, namely the role of organizational management, and environmental factors which also contribute to the success of APT attacks. We show that the three dimensions postulated in this study can assist Managers and IT personnel in organizations to implement an appropriate mix of socio-technical countermeasures for APT threats.
Nguyen-Van, Thanh, Le, Tien-Dat, Nguyen-Anh, Tuan, Nguyen-Ho, Minh-Phuoc, Nguyen-Van, Tuong, Le-Tran, Minh-Quoc, Le, Quang Nhat, Pham, Harry, Nguyen-An, Khuong.  2019.  A System for Scalable Decentralized Random Number Generation. 2019 IEEE 23rd International Enterprise Distributed Object Computing Workshop (EDOCW). :100–103.

Generating public randomness has been significantly demanding and also challenging, especially after the introduction of the Blockchain Technology. Lotteries, smart contracts, and random audits are examples where the reliability of the randomness source is a vital factor. We demonstrate a system of random number generation service for generating fair, tamper-resistant, and verifiable random numbers. Our protocol together with this system is an R&D project aiming at providing a decentralized solution to random number generation by leveraging the blockchain technology along with long-lasting cryptographic primitives including homomorphic encryption, verifiable random functions. The system decentralizes the process of generating random numbers by combining each party's favored value to obtain the final random numbers. Our novel idea is to force each party to encrypt his contribution before making it public. With the help of homomorphic encryption, all encrypted contribution can be combined without performing any decryption. The solution has achieved the properties of unpredictability, tamper-resistance, and public-verifiability. In addition, it only offers a linear overall complexity with respect to the number of parties on the network, which permits great scalability.

Gollamudi, Anitha, Chong, Stephen, Arden, Owen.  2019.  Information Flow Control for Distributed Trusted Execution Environments. 2019 IEEE 32nd Computer Security Foundations Symposium (CSF). :304–30414.

Distributed applications cannot assume that their security policies will be enforced on untrusted hosts. Trusted execution environments (TEEs) combined with cryptographic mechanisms enable execution of known code on an untrusted host and the exchange of confidential and authenticated messages with it. TEEs do not, however, establish the trustworthiness of code executing in a TEE. Thus, developing secure applications using TEEs requires specialized expertise and careful auditing. This paper presents DFLATE, a core security calculus for distributed applications with TEEs. DFLATE offers high-level abstractions that reflect both the guarantees and limitations of the underlying security mechanisms they are based on. The accuracy of these abstractions is exhibited by asymmetry between confidentiality and integrity in our formal results: DFLATE enforces a strong form of noninterference for confidentiality, but only a weak form for integrity. This reflects the asymmetry of the security guarantees of a TEE: a malicious host cannot access secrets in the TEE or modify its contents, but they can suppress or manipulate the sequence of its inputs and outputs. Therefore DFLATE cannot protect against the suppression of high-integrity messages, but when these messages are delivered, their contents cannot have been influenced by an attacker.

Sui, Zhiyuan, de Meer, Hermann.  2019.  BAP: A Batch and Auditable Privacy Preservation Scheme for Demand-Response in Smart Grids. IEEE Transactions on Industrial Informatics. :1–1.
Advancing network technologies allows the setup of two-way communication links between energy providers and consumers. These developing technologies aim to enhance grid reliability and energy efficiency in smart grids. To achieve this goal, energy usage reports from consumers are required to be both trustworthy and confidential. In this paper, we construct a new data aggregation scheme in smart grids based on a homomorphic encryption algorithm. In the constructed scheme, obedient consumers who follow the instruction can prove its ajustment using a range proof protocol. Additionally, we propose a new identity-based signature algorithm in order to ensure authentication and integrity of the constructed scheme. By using this signature algorithm, usage reports are verified in real time. Extensive simulations demonstrate that our scheme outperforms other data aggregation schemes.
Liu, Donglan, Zhang, Hao, Wang, Wenting, Zhao, Yang, Zhao, Xiaohong, Yu, Hao, Lv, Guodong, Zhao, Yong.  2019.  Research on Protection for the Database Security Based on the Cloud of Smart Grid. 2019 IEEE 11th International Conference on Communication Software and Networks (ICCSN). :585–589.

As cloud services enter the Internet market, cloud security issues are gradually exposed. In the era of knowledge economy, the unique potential value of big data is being gradually explored. However, the control of data security is facing many challenges. According to the development status and characteristics of database within the cloud environment, this paper preliminary studies on the database security risks faced by the “three-clouds” of State Grid Corporation of China. Based on the mature standardization of information security, this paper deeply studies the database security requirements of cloud environment, and six-step method for cloud database protection is presented, which plays an important role in promoting development of security work for the cloud database. Four key technologies of cloud database security protection are introduced, including database firewall technology, sensitive data encryption, production data desensitization, and database security audit technology. It is helpful to the technology popularization of the grade protection in the security of the cloud database, and plays a great role in the construction of the security of the state grid.

De Capitani di Vimercati, Sabrina, Foresti, Sara, Livraga, Giovanni, Samarati, Pierangela.  2019.  Empowering Owners with Control in Digital Data Markets. 2019 IEEE 12th International Conference on Cloud Computing (CLOUD). :321–328.

We propose an approach for allowing data owners to trade their data in digital data market scenarios, while keeping control over them. Our solution is based on a combination of selective encryption and smart contracts deployed on a blockchain, and ensures that only authorized users who paid an agreed amount can access a data item. We propose a safe interaction protocol for regulating the interplay between a data owner and subjects wishing to purchase (a subset of) her data, and an audit process for counteracting possible misbehaviors by any of the interacting parties. Our solution aims to make a step towards the realization of data market platforms where owners can benefit from trading their data while maintaining control.

Zhu, Yan, Zhang, Yi, Wang, Jing, Song, Weijing, Chu, Cheng-Chung, Liu, Guowei.  2019.  From Data-Driven to Intelligent-Driven: Technology Evolution of Network Security in Big Data Era. 2019 IEEE 43rd Annual Computer Software and Applications Conference (COMPSAC). 2:103–109.

With the advent of the big data era, information systems have exhibited some new features, including boundary obfuscation, system virtualization, unstructured and diversification of data types, and low coupling among function and data. These features not only lead to a big difference between big data technology (DT) and information technology (IT), but also promote the upgrading and evolution of network security technology. In response to these changes, in this paper we compare the characteristics between IT era and DT era, and then propose four DT security principles: privacy, integrity, traceability, and controllability, as well as active and dynamic defense strategy based on "propagation prediction, audit prediction, dynamic management and control". We further discuss the security challenges faced by DT and the corresponding assurance strategies. On this basis, the big data security technologies can be divided into four levels: elimination, continuation, improvement, and innovation. These technologies are analyzed, combed and explained according to six categories: access control, identification and authentication, data encryption, data privacy, intrusion prevention, security audit and disaster recovery. The results will support the evolution of security technologies in the DT era, the construction of big data platforms, the designation of security assurance strategies, and security technology choices suitable for big data.

Wang, Ti, Ma, Hui, Zhou, Yongbin, Zhang, Rui, Song, Zishuai.  2019.  Fully Accountable Data Sharing for Pay-As-You-Go Cloud Scenes. IEEE Transactions on Dependable and Secure Computing. :1–1.
Many enterprises and individuals prefer to outsource data to public cloud via various pricing approaches. One of the most widely-used approaches is the pay-as-you-go model, where the data owner hires public cloud to share data with data consumers, and only pays for the actually consumed services. To realize controllable and secure data sharing, ciphertext-policy attribute-based encryption (CP-ABE) is a suitable solution, which can provide fine-grained access control and encryption functionalities simultaneously. But there are some serious challenges when applying CP-ABE in pay-as-you-go. Firstly, the decryption cost in ABE is too heavy for data consumers. Secondly, ABE ciphertexts probably suffer distributed denial of services (DDoS) attacks, but there is no solution that can eliminate the security risk. At last, the data owner should audit resource consumption to guarantee the transparency of charge, while the existing method is inefficient. In this work, we propose a general construction named fully accountable ABE (FA-ABE), which simultaneously solves all the challenges by supporting all-sided accountability in the pay-as-you-go model. We formally define the security model and prove the security in the standard model. Also, we implement an instantiate construction with the self-developed library libabe. The experiment results indicate the efficiency and practicality of our construction.
Oqaily, Momen, Jarraya, Yosr, Mohammady, Meisam, Majumdar, Suryadipta, Pourzandi, Makan, Wang, Lingyu, Debbabi, Mourad.  2019.  SegGuard: Segmentation-based Anonymization of Network Data in Clouds for Privacy-Preserving Security Auditing. IEEE Transactions on Dependable and Secure Computing. :1–1.
Security auditing allows cloud tenants to verify the compliance of cloud infrastructure with respect to desirable security properties, e.g., whether a tenant's virtual network is properly isolated from other tenants' networks. However, the input to such an auditing task, such as the detailed topology of the underlying cloud infrastructure, typically contains sensitive information which a cloud provider may be reluctant to hand over to a third party auditor. Additionally, auditing results intended for one tenant may inadvertently reveal private information about other tenants, e.g., another tenant's VM is reachable due to a misconfiguration. How to anonymize both the input data and the auditing results in order to prevent such information leakage is a novel challenge that has received little attention. Directly applying most of the existing anonymization techniques to such a context would either lead to insufficient protection or render the data unsuitable for auditing. In this paper, we propose SegGuard, a novel anonymization approach that prevents cross-tenant information leakage through per-tenant encryption, and prevents information leakage to auditors through hiding real input segments among fake ones; in addition, applying property-preserving encryption in an innovative way enables SegGuard to preserve the data utility for auditing while mitigating semantic attacks. We implement SegGuard based on OpenStack, and evaluate its effectiveness and overhead using both synthetic and real data. Our experimental results demonstrate that SegGuard can reduce the information leakage to a negligible level (e.g., less than 1% for an adversary with 50% pre-knowledge) with a practical response time (e.g., 62 seconds to anonymize a cloud infrastructure with 25,000 virtual machines).
2019-12-30
Shirasaki, Yusuke, Takyu, Osamu, Fujii, Takeo, Ohtsuki, Tomoaki, Sasamori, Fumihito, Handa, Shiro.  2018.  Consideration of security for PLNC with untrusted relay in game theoretic perspective. 2018 IEEE Radio and Wireless Symposium (RWS). :109–112.
A physical layer network coding (PLNC) is a highly efficient scheme for exchanging information between two nodes. Since the relay receives the interfered signal between two signals sent by two nodes, it hardly decodes any information from received signal. Therefore, the secure wireless communication link to the untrusted relay is constructed. The two nodes optimize the transmit power control for maximizing the secure capacity but these depend on the channel state information informed by the relay station. Therefore, the untrusted relay disguises the informed CSI for exploiting the information from two nodes. This paper constructs the game of two optimizations between the legitimate two nodes and the untrusted relay for clarifying the security of PLNC with untrusted relay.
Belavagi, Manjula C, Muniyal, Balachandra.  2016.  Game theoretic approach towards intrusion detection. 2016 International Conference on Inventive Computation Technologies (ICICT). 1:1–5.
Today's network is distributed and heterogeneous in nature and has numerous applications which affect day to day life, such as e-Banking, e-Booking of tickets, on line shopping etc. Hence the security of the network is crucial. Threats in the network can be due to intrusions. Such threats can be observed and handled using Intrusion Detection System. The security can be achieved using intrusion detection system, which observes the data traffic and identifies it as an intrusion or not. The objective of this paper is to design a model using game theoretic approach for intrusion detection. Game model is designed by defining players, strategies and utility functions to identify the Probe attacks. This model is tested with NSLKDD data set. The model is the Probe attacks are identified by dominated strategies elimination method. Experimental results shows that game model identifies the attacks with good detection rate.
Chen, Jing, Du, Ruiying.  2009.  Fault Tolerance and Security in Forwarding Packets Using Game Theory. 2009 International Conference on Multimedia Information Networking and Security. 2:534–537.
In self-organized wireless network, such as ad hoc network, sensor network or mesh network, nodes are independent individuals which have different benefit; Therefore, selfish nodes refuse to forward packets for other nodes in order to save energy which causes the network fault. At the same time, some nodes may be malicious, whose aim is to damage the network. In this paper, we analyze the cooperation stimulation and security in self-organized wireless networks under a game theoretic framework. We first analyze a four node wireless network in which nodes share the channel by relaying for others during its idle periods in order to help the other nodes, each node has to use a part of its available channel capacity. And then, the fault tolerance and security problem is modeled as a non-cooperative game in which each player maximizes its own utility function. The goal of the game is to maximize the utility function in the giving condition in order to get better network efficiency. At last, for characterizing the efficiency of Nash equilibria, we analyze the so called price of anarchy, as the ratio between the objective function at the worst Nash equilibrium and the optimal objective function. Our results show that the players can get the biggest payoff if they obey cooperation strategy.
Tootaghaj, Diman Zad, Farhat, Farshid, Pakravan, Mohammad-Reza, Aref, Mohammad-Reza.  2011.  Game-theoretic approach to mitigate packet dropping in wireless Ad-hoc networks. 2011 IEEE Consumer Communications and Networking Conference (CCNC). :163–165.
Performance of routing is severely degraded when misbehaving nodes drop packets instead of properly forwarding them. In this paper, we propose a Game-Theoretic Adaptive Multipath Routing (GTAMR) protocol to detect and punish selfish or malicious nodes which try to drop information packets in routing phase and defend against collaborative attacks in which nodes try to disrupt communication or save their power. Our proposed algorithm outranks previous schemes because it is resilient against attacks in which more than one node coordinate their misbehavior and can be used in networks which wireless nodes use directional antennas. We then propose a game theoretic strategy, ERTFT, for nodes to promote cooperation. In comparison with other proposed TFT-like strategies, ours is resilient to systematic errors in detection of selfish nodes and does not lead to unending death spirals.
Yang, Lei, Zhang, Mengyuan, He, Shibo, Li, Ming, Zhang, Junshan.  2018.  Crowd-Empowered Privacy-Preserving Data Aggregation for Mobile Crowdsensing. Proceedings of the Eighteenth ACM International Symposium on Mobile Ad Hoc Networking and Computing. :151–160.
We develop an auction framework for privacy-preserving data aggregation in mobile crowdsensing, where the platform plays the role as an auctioneer to recruit workers for a sensing task. In this framework, the workers are allowed to report privacy-preserving versions of their data to protect their data privacy; and the platform selects workers based on their sensing capabilities, which aims to address the drawbacks of game-theoretic models that cannot ensure the accuracy level of the aggregated result, due to the existence of multiple Nash Equilibria. Observe that in this auction based framework, there exists externalities among workers' data privacy, because the data privacy of each worker depends on both her injected noise and the total noise in the aggregated result that is intimately related to which workers are selected to fulfill the task. To achieve a desirable accuracy level of the data aggregation in a cost-effective manner, we explicitly characterize the externalities, i.e., the impact of the noise added by each worker on both the data privacy and the accuracy of the aggregated result. Further, we explore the problem structure, characterize the hidden monotonicity property of the problem, and determine the critical bid of workers, which makes it possible to design a truthful, individually rational and computationally efficient incentive mechanism. The proposed incentive mechanism can recruit a set of workers to approximately minimize the cost of purchasing private sensing data from workers subject to the accuracy requirement of the aggregated result. We validate the proposed scheme through theoretical analysis as well as extensive simulations.
Tzouramanis, Theodoros, Manolopoulos, Yannis.  2018.  Secure Reverse k-Nearest Neighbours Search over Encrypted Multi-dimensional Databases. Proceedings of the 22Nd International Database Engineering & Applications Symposium. :84–94.
The reverse k-nearest neighbours search is a fundamental primitive in multi-dimensional (i.e. multi-attribute) databases with applications in location-based services, online recommendations, statistical classification, pat-tern recognition, graph algorithms, computer games development, and so on. Despite the relevance and popularity of the query, no solution has yet been put forward that supports it in encrypted databases while protecting at the same time the privacy of both the data and the queries. With the outsourcing of massive datasets in the cloud, it has become urgent to find ways of ensuring the fast and secure processing of this query in untrustworthy cloud computing. This paper presents searchable encryption schemes which can efficiently and securely enable the processing of the reverse k-nearest neighbours query over encrypted multi-dimensional data, including index-based search schemes which can carry out fast query response that preserves data confidentiality and query privacy. The proposed schemes resist practical attacks operating on the basis of powerful background knowledge and their efficiency is confirmed by a theoretical analysis and extensive simulation experiments.
2019-12-17
Guo, Shengjian, Wu, Meng, Wang, Chao.  2018.  Adversarial Symbolic Execution for Detecting Concurrency-Related Cache Timing Leaks. Proceedings of the 2018 26th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering. :377-388.
The timing characteristics of cache, a high-speed storage between the fast CPU and the slow memory, may reveal sensitive information of a program, thus allowing an adversary to conduct side-channel attacks. Existing methods for detecting timing leaks either ignore cache all together or focus only on passive leaks generated by the program itself, without considering leaks that are made possible by concurrently running some other threads. In this work, we show that timing-leak-freedom is not a compositional property: a program that is not leaky when running alone may become leaky when interleaved with other threads. Thus, we develop a new method, named adversarial symbolic execution, to detect such leaks. It systematically explores both the feasible program paths and their interleavings while modeling the cache, and leverages an SMT solver to decide if there are timing leaks. We have implemented our method in LLVM and evaluated it on a set of real-world ciphers with 14,455 lines of C code in total. Our experiments demonstrate both the efficiency of our method and its effectiveness in detecting side-channel leaks.
Liu, Daiping, Zhang, Mingwei, Wang, Haining.  2018.  A Robust and Efficient Defense Against Use-after-Free Exploits via Concurrent Pointer Sweeping. Proceedings of the 2018 ACM SIGSAC Conference on Computer and Communications Security. :1635-1648.
Applications in C/C++ are notoriously prone to memory corruptions. With significant research efforts devoted to this area of study, the security threats posed by previously popular vulnerabilities, such as stack and heap overflows, are not as serious as before. Instead, we have seen the meteoric rise of attacks exploiting use-after-free (UaF) vulnerabilities in recent years, which root in pointers pointing to freed memory (i.e., dangling pointers). Although various approaches have been proposed to harden software against UaF, none of them can achieve robustness and efficiency at the same time. In this paper, we present a novel defense called pSweeper to robustly protect against UaF exploits with low overhead, and pinpoint the root-causes of UaF vulnerabilities with one safe crash. The success of pSweeper lies in its two unique and innovative design ideas, concurrent pointer sweeping (CPW) and object origin tracking (OOT). CPW exploits the increasingly available multi-cores on modern PCs and outsources the heavyweight security checks and enforcement to dedicated threads that can run on spare cores. Specifically, CPW iteratively sweeps all live pointers in a concurrent thread to find dangling pointers. This design is quite different from previous work that requires to track every pointer propagation to maintain accurate point-to relationship between pointers and objects. OOT can help to pinpoint the root-causes of UaF by informing developers of how a dangling pointer is created, i.e., how the problematic object is allocated and freed. We implement a prototype of pSweeper and validate its efficacy in real scenarios. Our experimental results show that pSweeper is effective in defeating real-world UaF exploits and efficient when deployed in production runs.
Huang, Bo-Yuan, Ray, Sayak, Gupta, Aarti, Fung, Jason M., Malik, Sharad.  2018.  Formal Security Verification of Concurrent Firmware in SoCs Using Instruction-Level Abstraction for Hardware*. 2018 55th ACM/ESDA/IEEE Design Automation Conference (DAC). :1-6.
Formal security verification of firmware interacting with hardware in modern Systems-on-Chip (SoCs) is a critical research problem. This faces the following challenges: (1) design complexity and heterogeneity, (2) semantics gaps between software and hardware, (3) concurrency between firmware/hardware and between Intellectual Property Blocks (IPs), and (4) expensive bit-precise reasoning. In this paper, we present a co-verification methodology to address these challenges. We model hardware using the Instruction-Level Abstraction (ILA), capturing firmware-visible behavior at the architecture level. This enables integrating hardware behavior with firmware in each IP into a single thread. The co-verification with multiple firmware across IPs is formulated as a multi-threaded program verification problem, for which we leverage software verification techniques. We also propose an optimization using abstraction to prevent expensive bit-precise reasoning. The evaluation of our methodology on an industry SoC Secure Boot design demonstrates its applicability in SoC security verification.