Emotional support dialogue systems aim to reduce help-seekers' distress and help them overcome challenges.While human values-core beliefs that shape an individual's prioritiesare increasingly emphasized in contemporary psychological therapy for their role in fostering internal transformation and long-term emotional well-being, their integration into emotional support systems remains underexplored.To bridge this gap, we present a value-driven method for training emotional support dialogue systems designed to reinforce positive values in seekers.Notably, our model identifies which values to reinforce at each turn and how to do so, by leveraging online support conversations from Reddit.We evaluate the method across support skills, seekers' emotional intensity, and value reinforcement.Our method consistently outperforms various baselines, effectively exploring and eliciting values from seekers.Additionally, leveraging crowd knowledge from Reddit significantly enhances its effectiveness.Therapists highlighted its ability to validate seekers' challenges and emphasize positive aspects of their situations-both crucial elements of value reinforcement.Our work, being the first to integrate value reinforcement into emotional support systems, demonstrates its promise and establishes a foundation for future research.

ARM Memory Tagging Extension (MTE) is a new hardware feature introduced in ARMv8.5-A architecture, aiming to detect memory corruption vulnerabilities. The low overhead of MTE makes it an attractive solution to mitigate memory corruption attacks in modern software systems and is considered the most promising path forward for improving C/C++ software security. This paper explores the potential security risks posed by speculative execution attacks against MTE. Specifically, this paper identifies new Tiktag gadgets capable of leaking the MTE tags from arbitrary memory addresses through speculative execution. With Tiktag gadgets, attackers can bypass the probabilistic defense of MTE, increasing the attack success rate by close to 100%. We demonstrate that Tiktag gadgets can be used to bypass MTE-based mitigations in real-world systems, Google Chrome and the Linux kernel. Experimental results show that Tiktag gadgets can successfully leak an MTE tag with a success rate higher than 95% in less than 4 seconds. We further propose new defense mechanisms to mitigate the security risks posed by Tiktag gadgets.

Data-only attacks are emerging as a new threat to the security of modern operating systems. As a typical data-only attack, memory corruption attacks can compromise the integrity of kernel data, which effectively breaks the premises of access control systems. Unfortunately, the prevalence of memory corruption vulnerabilities allows attackers to exploit them and bypass access control mechanisms. Given the arbitrary memory access capability, attackers can overwrite access control policies or illegally access the kernel resources protected by the access control systems.

Bus riders desire precision and accuracy when using the transit system. While the transit system is responsible for maintaining and delivering public transportation services for the city residents, they rely on idealized assumptions regarding real-world bus driving conditions. The published bus schedule seems to assume that the buses move at a uniform speed at all times, which leads to bus arrival times that are imprecise and inaccurate. Busses can arrive early, late, or on time. Given that bus stops cannot have a dynamic schedule, it is logical to create a schedule accounting for the changes in traffic patterns. Hence, in this paper, we present a transportation analytics solution. It captures imprecision via fuzzy logic. It takes in account lane closures (for construction sites) and traffic count when predicting bus on-time performance via regression. Evaluation on real-life data covering close to 6,000 bus stops in the Canadian city of Winnipeg demonstrates the practicality of our fuzzy logic- and regression-based transportation analytics solution in predicting whether buses arrive the bus stops early, on time, or late in various time periods of the day. This helps in building a smart city.

In this paper, we propose a downlink resource sharing strategy in two-tier networks with the co-channel femtocell deployment. The proposed resource sharing strategy adopts the fractional frequency reuse (FFR) framework to maximize the spectral efficiency and overcome the femto-to-macro interference (FMI) problem at the same time. In the proposed strategy, resource units in each frequency partition (FP) are divided into a macro-privileged group and a femto-dedicated group. To protect the macrocell from the FMI, the resource usage of the femtocells is controlled according to the FP assignments of the nearby macrocell users. In addition, the per-FP resource division is determined to maximize the spectral efficiency while balancing macrocell/femtocell user throughputs. Simulation results show that the proposed resource sharing strategy can achieve high spectral efficiency while suppressing the FMI effectively.

A practical resource allocation in cellular networks should take into consideration inter-cell information exchange overhead, user channel feedback overhead, and adaptability to network status variations such as user distribution and traffic load. This paper presents two practical resource allocation techniques for the fractional frequency reuse (FFR) operation in IEEE 802.16m networks. Firstly, we propose a power allocation technique where the transmission powers across frequency partitions (FPs) are gradually adapted in a distributed way. The gradual power adaptation is derived from analysis of the optimal power allocation problem. Secondly, base station guided FP selection is proposed to obtain load balanced FP assignment with minimal feedback overhead. Simulation results show that the proposed techniques can enhance the spectral efficiency for the FFR under various network status.

In IEEE 802.16 Wireless MANs supporting OFDMA- PHY, random access with CDMA-based mechanism is proposed to request bandwidth for uplink data. Collision, which increases the Round Trip Time (RTT), is not avoided due to random access during requesting bandwidth among subscriber stations (SSs). In this paper, we propose an efficient resource allocation for Transmission Control Protocol (TCP) services with resolving RTT increasing problem caused by the wireless access of the best effort service and enhancing network performance in IEEE 802.16 Wireless MANs supporting OFDMA-PHY. The proposed resource allocation estimates the uplink traffic of SS based on the downlink traffic to the SS and allocates the resource to the SS, which transmits uplink traffic with the allocated resource. Our simulation results show that the proposed scheme provides better performance.